By Dr. Louise Muhdi

Polycrisis is rewriting the rules of competitive advantage. Organizations clinging to siloed operations are losing ground to competitors who have mastered collaboration across functions and ecosystems. Here, Louise Muhdi presents a five-dimensional framework for transforming collaboration from aspiration into measurable advantage.

In an era defined by polycrisis — AI disruption, geopolitical fragmentation, climate transition, and supply chain regionalization – companies that fail to embed collaboration (both internal cross‑functional and across their ecosystem, such as suppliers and value‑chain partners) risk irrelevance. Research from McKinsey & Company shows that organizations with strong collaboration, from cross-functional teams linking product development, procurement, manufacturing, and services to supplier and ecosystem partnerships, consistently outperform siloed peers.^1,2,3,4,5 Companies that collaborate closely with suppliers and value-chain partners achieve higher growth, lower costs, and greater profitability, while those engaging in broader ecosystem models can unlock new revenue streams and strengthen their competitive position.

Internal optimization — streamlining operations or improving efficiency — is necessary, but no longer sufficient. Sustainable growth now requires a shift from siloed execution to integrated collaboration across functions, partners, and ecosystems. Organizations that formalize collaboration as a strategic capability accelerate innovation, enhance resilience, and unlock new sources of value both inside and beyond the enterprise.

The AI Transformation Multiplier

Generative AI is fundamentally reshaping how organizations collaborate. Cross-functional AI teams are becoming essential as companies deploy AI across operations, requiring data scientists, domain experts, ethicists, and business leaders to co-create solutions. AI itself is becoming a collaboration enabler, breaking down language barriers, synthesizing insights across silos, and accelerating knowledge transfer. Yet AI also raises the collaboration stakes; without strong cross-functional alignment, AI implementations fragment, creating competing systems and eroding rather than building organizational capability. Organizations that master collaborative AI deployment gain compounding advantages in speed, learning, and adaptation.

The Collaboration Imperative

Whether deploying AI, navigating geopolitical shifts, or building sustainable supply chains, the imperative is the same: internal collaboration keeps an organization running; ecosystem collaboration keeps it winning. Departments and partner networks that operate in isolation hinder innovation and responsiveness. The traditional silo mentality slows decision-making, blocks knowledge flows, and limits adaptation and growth potential. Organizations that embrace integrated collaboration are not only faster and more innovative; they are also more resilient in the face of disruption.

The critical leadership question is: how do you cultivate a collaborative culture that turns aspiration into measurable competitive advantage? The answer lies in a five-dimension framework, anchored by trust, the essential enabler of every successful collaboration.

1. Vision Alignment: Creating Shared Purpose

Collaboration begins with a clear, compelling vision that unites internal teams and external partners. Without it, even well-intentioned initiatives falter.

Key practices:

• Define a shared, inspiring vision: This “north star” should unify employees and partners around a common purpose.
• Prioritize initiatives strategically: Focus resources on the most critical initiatives to avoid collaboration sprawl.
• Communicate relentlessly: Repetition and clarity energize teams and attract like-minded partners.
• Example: Schneider Electric’s “Life Is On” vision exemplifies alignment. The company unites employees, partners, and customers around the mission of empowering everyone to optimize energy and resources. By embedding this vision into leadership discussions, strategic initiatives, and global communications, Schneider Electric ensures coordinated action, innovation, and a consistent market presence that reinforces its brand promise.

Reflective questions:

• Does your organization have a clearly articulated and compelling vision that unites teams and partners?
• Are there gaps between stated vision and day-to-day decisions?

2. Structural Innovation: Redesign for Co-Creation Across Boundaries

Traditional hierarchies often reinforce silos, slowing the flow of ideas and decisions. Leading organizations rethink structures to enable seamless co-creation internally and with ecosystem partners.

Key practices:

• Cross-functional co-creation teams: Integrate diverse expertise from project inception.
• Embedded external integration: Bring suppliers, customers, and ecosystem partners into development and decision-making processes – from the start.
• Innovation hubs and collaboration platforms: Physical and virtual spaces that act as magnets for experimentation and knowledge exchange.
• Example: IKEA’s Co-Create Hubs bring em–ployees, designers, startups, suppliers, and customers together from the start of product ideation and development. This structure accelerates innovation, ensures alignment on sustainability and design goals, and encourages diverse perspectives to shape products that resonate with the market.

Reflective questions:

• Are your structures enabling or blocking cross-functional collaboration?
• How integrated are partners in your development and innovation processes?

3. Process Excellence: Seamless Knowledge and Data Flows

Collaboration falters without efficient sha-red processes. Structured workflows and knowledge-sharing systems are critical for fast, transparent decision-making.

Key practices:

• Collaborative workflows: Engage all relevant teams early to reduce hand-off delays.
• Knowledge-sharing systems: Capture and disseminate insights across teams and partners.
• Digital integration platforms: Provide real-time visibility into key data across the value chain.
• Example: Veja’s Collaborative Value Chain integrates Brazilian recycling cooperatives with downstream manufacturing teams. Structured workflows ensure transparent knowledge flows, real-time traceability, and coordinated decision-making, enabling Veja to deliver sustainable footwear efficiently while maximizing social and environmental impact.

Reflective questions:

• Do workflows support fast, transparent collaboration and co-creation?
• Are lessons learned captured effectively and applied across teams and partners?

4. Aligned Incentives: Shared Success Through Joint Metrics

Collaboration fails when goals conflict. Aligning incentives ensures that participants act toward shared outcomes.

Key practices:

• Shared targets: Align goals with partner capabilities and market opportunities.
• Transparent performance measurement: Provide visibility into progress against joint objectives.
• Capability building: Equip partners to succeed through training and resources.
• Example: In an era of supply chain regionalization and friend-shoring, Unilever’s Supplier Climate Programme, launched in 2021, demonstrates how ecosystem collaboration creates resilience. The company has set joint targets with 300 suppliers whose materials contribute 42-44 per cent of its Scope 3 emissions. By requiring suppliers to adopt shared, science-based GHG reduction targets, share data, and report progress publicly, Unilever aligns incentives across its ecosystem, driving measurable sustainability while building the supplier relationships and transparency that buffer against geopolitical disruption.

Reflective questions:

• Are incentives aligned with organizational and ecosystem goals?
• How transparent are performance metrics across teams and partners?

5. Collaborative Leadership: Building Capabilities Across Boundaries

Command-and-control leadership cannot deliver collaboration at scale. Leaders must orchestrate ecosystems, balance diverse interests, and create value beyond formal authority.

Key practices:

• Shift from hierarchical to networked leadership: Empower self-leadership, autonomy, and trust.
• Orchestrate multi-stakeholder initiatives: Navigate complexity while aligning interests.
• Cultivate resilience and adaptability: Maintain clarity amid ambiguity.
• Example: Roche’s VACC Framework (Visionaries, Architects, Coaches, Catalysts)⁶ fosters collaborative leadership at scale. Leaders inspire purpose, design adaptive systems, nurture talent, and accelerate change across silos. This boundary-spanning approach allows teams to co-create value across organizational and partner networks.

Reflective questions:

• Do leaders foster trust, autonomy, and empowerment across teams and partners?
• Are leaders equipped to navigate complexity and drive collaborative outcomes?

The Trust Foundation: Building the Collaboration Enabler

Stop thinking of trust as a bonus; start seeing it as the engine of collaboration. It’s the foundation for all successful collaboration. When trust is absent, even well-designed teams and strong incentives fall apart. Trust must be earned through ongoing, purposeful interactions fueled by real commitment and active engagement.

Here’s how trust grows:

• Reliability: Do what you say you will do, every time. This consistency builds confidence.
• Transparency: Be open with information, even when things go wrong, to cement your integrity.
• Competence: Demonstrate a clear ability to perform the task. This is the root of credibility.
• Vulnerability: Have the courage to admit when you don’t know something and ask for support. It’s how connections deepen.
• Shared Risk: Commit joint resources or time. This investment is the ultimate signal of
  mutual dedication.

In practice, trust-building requires deliberate action. Companies like Patagonia have built supplier trust through multi-year contracts and advance payments that share financial risk. Microsoft’s collaborative culture rests on “Model, Coach, Care” leadership behaviors that explicitly build psychological safety and is a central part of their leadership approach to empower employees and foster a growth mindset. The EU’s CSRD reporting requirements are forcing companies to deepen supplier relationships and data transparency, inadvertently accelerating trust-building across value chains.

Trust measurement matters. Organizations can track trust through employee and partner surveys, collaboration velocity (how quickly cross-functional decisions happen), knowledge-sharing metrics, and innovation output from collaborative initiatives. When trust erodes, these indicators provide early warning.

Reflective questions:

• How strong is trust across teams, functions, and external partners?
• What systematic practices build trust in your organization?
• Do you measure trust and its impact on collaboration outcomes?
• How quickly can you mobilize cross-functional or ecosystem responses to unexpected challenges?

The Cost of Collaboration Failure

The absence of these collaboration dimensions carries measurable costs. Consider the automotive industry’s struggles with electric vehicle transitions. Traditional automakers with siloed R&D, manufacturing, and software teams have watched Tesla and Chinese EV makers capture market share. Their challenge wasn’t technological capability; it was collaboration failure. Engineering teams designed vehicles while software teams worked in isolation, battery suppliers weren’t integrated into design decisions, and hierarchical leadership slowed adaptation. The result: fragmented products, delayed launches, and eroding competitive position.

Collaboration is not an abstract goal; it is a strategic capability requiring prioritization and systematic practice.

Similarly, many European companies’ ESG-reporting struggles under CSRD stem from collaboration gaps: sustainability teams lack access to supplier data, finance teams haven’t integrated ESG metrics, and external partners weren’t engaged early in measurement system design. The regulatory deadline doesn’t shift; the collaboration capability gap determines who leads and who lags.

Strategic Implications: Your Collaboration Road Map

Collaboration is not an abstract goal; it is a strategic capability requiring prioritization and systematic practice. Organizations ready to act can begin with these steps:

• Audit collaboration readiness: Assess your organization against the five dimensions. Where are the critical gaps?
• Prioritize one ecosystem relationship: Choose a strategic supplier, customer, or partner relationship and systematically strengthen it across all five dimensions.
• Measure what matters: Establish baseline metrics for collaboration velocity, trust levels, and innovation output from collaborative initiatives.
• Develop collaborative leadership: Invest in the orchestration, empathy, problem-solving, and systems-thinking skills essential for networked leadership.
• Start with trust: Focus initial efforts on transparency, shared risk, and relationship deepening, the foundation that makes all other collaboration possible.

Organizations that fail to act risk exclusion from the ecosystems where innovation and growth concentrate. In automotive, energy, pharmaceuticals, and consumer goods, ecosystem orchestrators are already choosing partners based on collaborative capability, not just technical competence.

The choice is clear: remain trapped in siloed thinking and risk irrelevance, or embrace strategic collaboration to unlock innovation, resilience, and sustainable competitive advantage.

In a world defined by polycrisis, collaboration is not optional. It is imperative.

About the Author

Dr. Louise Muhdi is a global innovation strategist, author, and advisor. Former IMD Business School Professor and ex-Global Head of Innovation Strategy at Givaudan, she specializes in strategic innovation and business transformation. She empowers executives across industries to accelerate transformation and drive positive change.

References

1. McKinsey & Company, “Transform the whole business, not just the parts,” https://www.mckinsey.com/capabilities/operations/our-insights/transform-the-whole-business-not-just-the-parts

2. McKinsey & Company, “Making collaboration across functions a reality,” https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/making-collaboration-across-functions-a-reality

3. McKinsey & Company, “Taking supplier collaboration to the next level,” https://www.mckinsey.com/capabilities/operations/our-insights/taking-supplier-collaboration-to-the-next-level

4. McKinsey & Company, “How great supply-chain organizations work,” https://www.mckinsey.com/capabilities/operations/our-insights/how-great-supply-chain-organizations-work

5. McKinsey & Company, “How a digital B2B ecosystem can help manufacturers create value,” https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/radically-rethink-your-strategy-how-digital-b2b-ecosystems-can-help-traditional-manufacturers-create-and-protect-value

6. The Case Centre, “Future-proofing Roche: Transforming for Agility and Empowerment,” https://www.thecasecentre.org/products/view?id=193797

The post Collaboration as Strategy: Five Dimensions for Winning in an Age of Polycrisis appeared first on The European Business Review.

By Jacques Bughin

If you’re quietly patting yourself on the back for finally getting a grip on AI and its impact on your organization, here’s a reality check. It turns out there is more to AI than GenAI. Agentic AI is coming our way – and this time, it’s REALLY big!

The last two years have been dominated by generative AI, LLMs that produce text, code, and images at unprecedented speed. But the frontier has shifted. A new wave is forming, one that is less about generating content and far more about taking action. This wave is agentic AI,¹ systems that plan, decide, execute, coordinate with other agents, and interface with real-world tools, software, or machines. And, unlike the previous transitions, this one fundamentally reshapes entire industries, labor markets, and the competitive landscape of AI firms.

Unlike the previous transitions, this one fundamentally reshapes entire industries, labor markets, and the competitive landscape of AI firms.

To understand why, one must look beyond the hype and examine what the emerging players are actually doing. Across the world, we see the foundational pieces of an agentic economy being assembled. Some companies—Moveworks,² ServiceNow, OpenAI, Anthropic, CrewAI, LangGraph—are building the orchestration and multi-agent fabric. Others—Alibaba DingTalk, Tencent, ByteDance, Baidu—are deploying agents at societal scale. In Europe, Siemens and ABB are embedding agents inside factories, robots, and supply chains. Yet, while the surface impression is progress, the deeper truth is that the global market is still mono-agent, doing tool calls rather than cooperation. True multi-agent systems, agents coordinating as teams, are only in their infancy.

However, the direction of travel is now known; we are entering a world where most workflow, coordination, planning, and even knowledge work will be executed by agentic systems, not by generative models. And this shift will be bigger and more transformative than the GenAI wave for three reasons:

1. agency automates tasks, not content;
2. agency scales labor;
3. agency restructures firms, workflows, and entire industries.

GenAI revolutionized output creation. Agentic AI is the wave we need to revolutionize the entire concept of work.

1. The emerging agentic market: still mono-agent, but crystallizing fast

Although the industry uses the language of “multi-agent AI,” today’s systems are, bluntly, one-agent wrappers around LLMs. Moveworks, the leader in enterprise AI service management, provides a single enterprise assistant that resolves tickets, completes HR workflows, and updates internal systems. It behaves like a highly competent internal employee: it resets passwords, rewrites policies, updates CRM fields, books travel, and links to Jira or Workday. But all this flows from a single agent orchestrating many tool calls. It is not yet coordinating with other autonomous agents; rather, it is acting as a “meta-employee” for the enterprise.

The same is true for Microsoft’s Autogen-based internal systems, and for Google’s Gemini Code Assist. They are not yet multi-agent societies; they are intelligent single execution loops with planning sequences.

Only a few players push into real multi-agent autonomy. CrewAI is an open-source Python library which allows the orchestration of multiple AI agents as a real project team. Instead of settling for a single generalist assistant, one can create a squad of specialized AIs, each with a role, a mission, and the ability to communicate with their colleagues. The agents are powered by LLMs such as GPT-4o or Claude. Each agent acts within their field, collaborates with others, and contributes to advancing the mission. Everything is coordinated by a manager agent who orchestrates the team. What makes CrewAI so powerful is its role-based agents, its shared contextual memory system, and its ability to handle complex inter-agent conversations. LangGraph is another case in point as an orchestration framework designed for building multi-agent AI systems with large language models. It allows developers to create complex, dynamic workflows as graph structures where multiple AI agents interact, collaborate, and maintain context and state over long-running tasks. LangGraph excels in managing multi-agent communications with fine-grained control over application flow, enabling reliable, customizable, and scalable agentic AI applications, including conversational agents, task automation, and decision-making systems.

But even here, most use is experimental. Agents cooperate to write reports, run simulations, or perform market analysis, not to autonomously run supply chains or operate financial systems. China is the exception. Its industrial platforms—DingTalk, Tencent’s scenario platforms, Baidu’s Apollo, ByteDance’s commerce systems—use multi-agent structures, because the underlying digital ecosystems are unified. DingTalk agents negotiate task assignments and approval flows. ByteDance’s HiAgent allows pricing, logistics, advertising, and inventory agents to coordinate asynchronously. Baidu Apollo’s self-driving system is multi-agent by necessity, allowing vehicles to learn from collective driving experiences and scenario data. This distributed multi-agent structure enables scalability and fleet-level optimization, supporting real-time scenario simulation, validation, and model updates that enhance safety and performance. The necessity for this multi-agent approach stems from the complexity and safety-critical demands of autonomous driving. No single monolithic model can efficiently and reliably handle the wide range of subtasks required in diverse driving environments. Instead, modular agents specializing in perception, mapping, prediction, and planning enable parallel processing, robustness, and modular upgrades. Real-time interaction of these agents ensures continuous adaptation to changing conditions, while fleet-wide coordination facilitates system improvements on a large scale.

2. Why agentic AI is the next wave

(and bigger than generative AI)

To understand why agentic AI will overshadow generative AI, we must look at what it fundamentally changes. Generative AI produces content. That is powerful; coding assistants like Cursor or ChatGPT can generate boilerplate, transform legacy systems, and help developers. But content generation has natural limits: content is the output of tasks, not the tasks themselves.

Agentic AI flips this relationship. It automates the task, not the output. Instead of generating an email, the agent reads the email, opens Salesforce, retrieves context, drafts a response, updates the opportunity, books a meeting, and files a ticket. Instead of summarizing policy documents, the agent updates compliance workflows, sends approval requests, writes the audit trail, and coordinates with five other internal systems.

An agent is not a “smart model”; it is a worker. And when workers scale, so does value creation. This shift has three systemic implications:

First, agentic AI attacks the coordination costs of the firm, the deepest cost structure identified by Coase. If an agent can schedule meetings, allocate resources, file claims, run ETL pipelines, reconcile invoices, and coordinate inventory, the firm transforms from a hierarchy of labor into a network of autonomous processes. Productivity is no longer linked to headcount.

Second, agentic AI enables stacked multipliers: one agent helps sales; ten agents run an entire sales pipeline; fifty agents automate a supply chain. Generative models do not scale this way.

Third, agentic AI displaces GenAI-native companies because generation is commoditized. Once agents automate tasks directly, the value shifts from content to execution. Cursor helped developers write code; agentic systems automate the entire issue lifecycle: triage → fix → test → deploy → notify stakeholders. The more agentic systems mature, the weaker the standalone GenAI-only products become.

3. Why agentic AI will reshape employment

(more than GenAI ever could)

Predictive AI affected forecasters and analysts. GenAI affected writers, coders, and creatives. Agentic AI affects everyone, because it automates the workflows that make up jobs.

Moreover, multi-agent systems will automate coordination, the highest-level human activity in firms.

Moveworks and ServiceNow already demonstrate that a single agent can absorb 40–70 percent of IT and HR tickets. In major companies, this is the equivalent of replacing dozens of support staff. ByteDance HiAgent coordinates advertising, logistics, and customer support, reducing labor requirements across multiple domains simultaneously. DingTalk agents in China automate HR, finance, and purchasing workflows for millions of SMEs. Unlike GenAI, which “augments,” agentic AI executes. It can read emails, log into systems, reason over multi-step workflows, call APIs and make decisions

Moreover, multi-agent systems will automate coordination, the highest-level human activity in firms: resource allocation, scheduling, negotiation, prioritization. This is why the shift is more profound than the move to GenAI. GenAI replaced creation, but agentic AI replaces coordination, which is what managers, administrators, and entire corporate functions are paid to do.

4. Agentic AI may oblige GenAI-only startups to reinvent

The GenAI SaaS wave (2020–3) produced an explosion of startups offering “smart content.” But the economics of agentic AI destroy that value proposition. A GenAI-only product generates a document, a query, or a piece of code. An agentic AI system reads the requirement, executes the task, interacts with systems, and completes the process.

Cursor is already facing this reality. Although it is a brilliant coding assistant, agentic systems like Devin or GPT-based Code Agents can automate entire tickets end to end, making a coding editor assistant insufficient. Jasper and Copy.ai have declined sharply in usage because marketing agents can now plan campaigns, test variants, analyze CTR, adjust budgets, and post on social media, not just generate copy. The more agentic AI improves, the more GenAI-only tools lose relevance. Why use a coding assistant when an agent can build, test, deploy, and monitor features? Why use a customer-service chatbot when an agent can resolve the case?

GenAI tools focused on “generation” become components, not products. Agentic AI is not a new product category; it is a platform shift that absorbs generation entirely.

As an example, consider Moveworks. It represents the first generation of enterprise agentic platforms, a single agent with deep enterprise integration and thousands of pretrained workflows. Its competitive strength lies in the density of integrations, not the intelligence of the model. It is a mono-agent that behaves like an entire tier-1 support team. This is why ServiceNow acquired Moveworks: it fits into a broader agentic vision where each enterprise function gets an autonomous system.

CrewAI and LangGraph represent the second generation—multi-agent orchestration frameworks, where different agents assume different roles, negotiate tasks, and pass control. These frameworks are early, messy, and experimental, but they are the seeds of a future where enterprises run dozens or hundreds of cooperating agents across departments. In China, DingTalk and ByteDance are already moving toward multi-agent ecosystems with specialized agents that cooperate across logistics, finance, inventory, marketing, and HR. In many ways, China is executing the true multi-agent vision earlier, because its digital ecosystems are unified.

Conclusion: The age of agency will restructure the economy; be ready for it

The next wave of AI is not about models but about actions. It is not about intelligence but about coordination. It is not about content but about workflows. Agentic AI will reshape firms, collapse coordination costs, create new digital labor forces, disrupt GenAI-only companies, and permanently alter labor markets.

Mono-agent systems will dominate in the short term, but multi-agent cooperation will define the long-term landscape. China is ahead in deployment, the US in frameworks, and Europe in industrial integration, if it can lower its cost of deployment. Agentic AI is not the next step after GenAI. It is likely a replacement for it. The era of autonomous work besides simple robotics has begun.

Managers must shift from supervising workflows to owning outcomes, because agentic AI automates the coordination tasks that once defined managerial work. Their role becomes that of system architect, not task allocator, designing which workflows agents execute, setting guardrails, and auditing AI decisions. They must manage constraints, not steps: accuracy thresholds, compliance logic, escalation paths, and risk boundaries. Data stewardship becomes central, since agentic AI’s performance depends on clean data flows, standardized processes, and interoperable systems. Metrics move from micro-monitoring humans to macro-monitoring system productivity, error vectors, and escalation patterns. Managers must redeploy humans into high-judgment roles: exception handling, negotiation, creativity, and cross-functional sense-making. They must also master AI risk management through audits, drift monitoring, red-teaming, and scenario testing.

Ultimately, managers evolve into hybrid orchestrators of humans and agents, responsible for strategic alignment, workflow design, constraint definition, and organizational learning. The quantity of managerial labor declines, but the strategic intensity of what remains increases sharply.

About the Author

Jacques Bughin is the CEO of MachaonAdvisory and a former professor of Management. He retired from McKinsey as a senior partner and director of the McKinsey Global Institute. He advises Antler and Fortino Capital, two major VC /PE firms, and serves on the board of several companies.

The post The Next Wave of AI: from Generation to Agency appeared first on The European Business Review.

The engineering and construction sector faces a striking paradox: digital tools are proven to boost performance, yet adoption remains low. In this article, Pedro Hidalgo Insua explores how forward-thinking EPCs can turn this gap into an advantage, using AI, integrated data ecosystems, and modern commissioning tools to outperform slow-digitalizing competitors and strengthen long-term project success.

A report published at the end of 2024 by the Royal Institution of Chartered Surveyors highlights a paradox in which the engineering and construction industry finds itself – globally, particularly in Europe.

Here’s the paradox: most professionals agree that digital tools improve project delivery. When asked which areas would benefit most from digitalization, 63% identify cost estimation, prediction, planning and control; 57% cite developing an asset lifecycle or “whole-of-life” perspective and 55% pointed to better progress monitoring. In each case, almost all agree upon the benefits of digitalization.

Yet actual adoption remains stubbornly low. In fact, the share of firms not using any digital technologies on projects increases each year, rising from 40 to 43% between 2021 and 2023. European firms believe in the value of digitalization but are now the least likely to use them in comparison to companies in the Americas, the Middle East or APAC.

Putting Value on a Paradox

So, how much does this contradiction between this belief and the lack of progress in practice cost European firms?

When trying to answer this question, one can focus on project performance. The Boston Consulting Group found that the use of digital technologies by E&C firms tended to reduce construction time by 15%-30% and cut lifetime costs by 20%.

But that’s only part of the equation. With several countries such as the UK, Germany, France and Spain mandating the use of BIM or digital twins in public-sector tenders, low digital adoption also represents loss of revenue. Lack of digital capabilities for project selection or project controls can also lead teams to avoid valuable projects by excess of pessimism or conservatism, or to submit uncompetitive bids because of poor cost or risk estimates and lack of benchmark data.

So how can forward-looking EPCs turn this situation to their advantage? The following are four concrete digital strategies that not only address the common barriers to adoption but also build a clear competitive edge over slow adopters.

#1 Leveraging AI to Strengthen Project Controls and Progress Measurement

When surveying large engineering and construction firms (for example, as part of our research into high-performing projects), one consistent finding is that firms fall into one of three groups. Roughly a third deliver on their time and budget commitments in 80% of their projects or more. Another third does so between 50-80% of the time.

This disparity highlights a profound challenge in project controls. Major projects across multiple sectors suffer massive financial losses due to inefficiencies, often stemming from inadequate control mechanisms. A 2021 study by KPMG revealed that major projects, on average, experienced $100 million USD in losses due to waste, with inadequate controls identified as the leading cause. This waste is often rooted in a reliance on manual data entry, subjective status reports and siloed spreadsheets, which collectively create poor visibility into true progress until it is too late to course-correct.

To address this pain point, leading EPCs are automating data capture and shifting toward approaches like Enterprise Project Performance (EPP) that can now be enriched with Artificial Intelligence. This shift replaces traditional subjective measurements, which often suffer from optimism bias and inconsistency, with objective data. For example, construction schedules are now being directly linked with real-time indicators such as quantities installed (via barcode or RFID scans) or actual work completed. AI and Machine Learning then analyze these patterns to predict potential outcomes, which allows for proactive intervention; for example, by flagging that a project is likely to slip a key milestone or suggesting more efficient resource allocation.

Platforms like Hexagon’s EcoSys exemplify this modern approach. As a leading EPP solution, EcoSys addresses poor progress visibility by integrating all key project functions, including scheduling, cost control and resource management, as well as connecting to diverse data sources like ERP systems and field applications. This integration establishes a single source of truth for project performance, injecting the necessary objectivity and consistency into decision-making.

It should be noted, however, that the shift requires more than just the software. True performance uplift is dependent on foundational organizational changes, including process standardization, robust data governance frameworks and a profound cultural shift toward data-driven decision-making across the organization.

When these systems are properly implemented, the impact on success rates is significant. According to a 2022 survey by Logikal, while only 5% of projects fully automate their project controls data, those projects report a 79% success rate in meeting targets.

#2 Collecting, Structuring and Contextualizing Project Data Within a Single Interface

Slow adopters tend to treat project data in a fragmentary way— each phase and department generates its own trove of emails, documents and spreadsheets that often vanish into archives after project close-out.

Three numbers demonstrate how doomed this strategy is: the World Economic Forum found that, on average, a single large infrastructure project today could produce 130 million emails, 55 million document and 12 million work orders. Keeping this volume of information buried in individual inboxes or disparate systems means thousands of hours wasted searching for information. It also leads workers to rely on memory or intuition rather than data.

Leading EPCs address this through integrated data ecosystems—a shift that requires both technological infrastructure and cultural change. These ecosystems are structured around platforms like digital thread or a project/asset digital twin. They spread information across traditionally separate domains (design, procurement, construction, operations).

For example, engineering models and tags can be linked to procurement statuses, which link to construction progress and then feed into an asset management system for operations. The result is greater speed and efficiency across the chain: for instance, when an engineering change occurs, an integrated system automatically notifies affected procurement orders, updates construction schedules and flags potential impacts on commissioning process that would take days or weeks within fragmented systems.

Contextualizing data like this means at any point in the lifecycle, the right people can access trusted, up-to-date information. This lifecycle approach also enables powerful analytics: AI can be applied to the unified dataset to find patterns (e.g. which contractors consistently perform better) or to forecast outcomes across the project portfolio.

Importantly, data connectivity needs to accompany the mere addition of tools. Without integration, adding more digital tools can ironically create extra work as teams jump between systems. It’s no surprise that 73% of EPC executives say lack of data integration has a “strong or severe” negative impact on their operations.

The high-performing EPCs avoid this trap by investing in platforms that speak to each other, often via standards like CFIHOS (Capital Facilities Information Handover Specification) for handover data and by enforcing data governance practices. The results are tangible: less time spent cobbling together reports and more time using information to make decisions.

#3 Avoiding Project Derailment at Commissioning and Handover

Another high-impact area where conventional practices fall short is completions, commissioning and handover to the owner/operator.

Traditionally, preparing turnover dossiers while ensuring every test, inspection and punch-list item is complete typically involves coordinating hundreds of documents across multiple contractors—a process prone to documentation gaps, version control issues and coordination failures between multiple stakeholders. These practices are also highly inefficient: as the Construction Industry Institute notes, “Commissioning failures are too common in frequency and extremely costly in impact. The business case for action is clear”.

So, what does this action look like? Modern completions management systems like Intergraph Smart® Completions turn this into a digital process. All asset information, checklists and test results are captured in a centralized database, with automated tracking Smart Completions of outstanding tasks. The payoff can be significant: on one Australian LNG megaproject, adoption cut the compilation and delivery time of commissioning dossiers by 98%.

Such tools also benefit the EPC in two important ways. First, commissioning is embedded in the design and construction processes rather than treated as an afterthought, which reduces rework, delays and other unforeseen issues during final testing. Second, they drive standardization, repeatability and continuous improvement rather than handling each project as one of a kind.

This emphasis on standardization is crucial: consistently delivering projects on time and on budget requires repeatable processes, not heroic efforts on each project. This consistency requires the effective use of data, from project selection to handover, to reduce risk and guesswork and increase margins.

The tools and methodologies exist and with digitalization adoption still lagging across much of the industry, early movers can establish a significant competitive advantage before digital maturity becomes a baseline expectation, rather than a differentiator.

Discover how Hexagon’s solutions, including project twins and EcoSys, our Enterprise Project Performance platform, can help you digitalize processes and achieve greater project performance here.

About the Author

Pedro Hidalgo Insua is a Senior Industry Consultant specializing in industry-leading solutions like S3D and SPI, SPEL, SP&ID, Smart Materials and construction tool. With a background in piping design, Pedro has over 20 years of experience in Information Management and Automation for the oil and gas and power industries, primarily in EPCs.

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Over 1.3 billion people live with disabilities yet their entrepreneurial potential remains overlooked. Entrepreneurs with disabilities innovate, seize opportunities, and reshape markets. With inclusive ecosystems supportive policies and strong networks they can drive innovation, resilience, and economic growth. Supporting them means unlocking a powerful source of creativity and transformation. 

The World Health Organization reports that over 1.3 billion people worldwide are living with a disability. It is the largest minority in the world, and a group that anyone can join at any time. Because disability is not necessarily permanent; it can also be temporary. Too often, they remain excluded from mainstream economic life. And with an unemployment rate that is twice the national average, it goes without saying that career prospects are sometimes compromised., But is starting a business necessarily the default choice for people with disabilities? But framing it this way misses the point.

Entrepreneurs with disabilities do more than create livelihoods; they generate innovation, competitiveness, and social impact. Their lived experience becomes a strategic resource, helping them navigate uncertainty, adapt to constraints, and solve problems in original ways. They identify unmet needs, spot gaps in existing systems, and anticipate opportunities, building ventures that are economically viable and socially meaningful. Blind since birth, Baptiste “realized the lack of interest, and the media treatment on the subject of parasport.” Driven by this observation, he launched an organization to publicize and promote parasports and their athletes. “It was about undertaking something. It was an idea. As I went along, I built something important.” Step by step, he shaped an editorial line and gathered a community around his desire to inform and encourage participation in sport. “It reaches a lot of people.” His presence on social media quickly gained influence, and he began using it not only to raise awareness of parasport but also to inspire change in the job market for PwD by spotlighting remarkable and motivating profiles. “I went further than just the sports sphere. Now I’m really in the disability sphere in the broadest sense, and also impacting the professional world, human resources and project managers.”

Research tends to view entrepreneurs with disabilities as a homogeneous group, at the risk of failing into clichés. Yet it is important not to fall into clichés. The most common one is that of the ‘everyday fighter,’ the entrepreneur who constantly overcomes challenges. Conversely, it would be misleading to pretend they are just like any other entrepreneur. A balance must be struck. They are not different from others; they are different like others. It is this very otherness that is a source of richness. Contrary to stereotypes, entrepreneurs with disabilities start businesses not only out of necessity, but also to seize real opportunities. Decisions are opportunity-driven, informed by strategic planning and experiential knowledge. Daba has built her company around two complementary areas. The first is a general-interest sector that serves the broader mission and purpose of her work. The second is a business arm that sustains and finances the activities of the non-profit side. Her goal “is to change perceptions on disability issues, and on the business side, it provides support for companies and clients through consulting, communication, and events.” Entrepreneurs with disabilities position themselves deliberately in the market, mobilize resources, and structure organizations to maximize impact and sustainability. Drawing on social, human, and network capital, they gain legitimacy, attract critical support, and remain adaptable to shifting market conditions. Societal prejudice may exist, but it does not necessarily determine entrepreneurial choices. Their scope can be broad, ambitions high, and objectives strategically aligned. At just 25 years old, Vincent, who has been blind since birth, has already launched three companies. His entrepreneurial journey began with a platform designed to connect restaurant owners and consumers. He then went on to create a business specializing in three-dimensional screens, giving blind individuals the ability to make the most of their mobile phones. “My latest company is my favorite.” Today, this third venture offers consulting, training, and support services to law firms. “We are growing very, very fast.”

This potential does not emerge in isolation. Organizations and institutions play a central role in providing enabling environments. The threat of budget cuts looming over social and solidarity economy organizations could jeopardize this essential support for entrepreneurs with disabilities. Targeted funding, tailored incentives, and structured mentorship programs strengthen opportunity recognition and decision-making. Incubators and training initiatives can go beyond foundational skills, offering sector-specific expertise, market insights, and tools to integrate inclusion and social responsibility into business models. Collaborative networks and entrepreneurial communities allow experiential knowledge to combine with broader industry perspectives, fueling innovation and scaling ventures. Public policy is equally decisive. Inclusive ecosystems that bring together policymakers, social sector actors, vocational organizations, and industry stakeholders create the structural framework that supports entrepreneurs with disabilities at every stage. Well-designed policies embed accessibility and inclusion into entrepreneurship, encourage adaptive business models, reward socially responsible innovation, and integrate disabled entrepreneurs into mainstream networks. If the State is the guarantor of the common good, it cannot, on its own, carry out all the actions in support of people with disabilities. Entrepreneurs with disabilities are increasingly numerous. Entrepreneurship offers them the possibility to flourish on their own terms, for who they are rather than for who others would want them to be.

The evidence is clear. Entrepreneurs with disabilities are already innovating, adapting, and leading change. Yet their potential remains underutilized because the ecosystems around them are not designed with inclusion at their core. This is a missed opportunity not just for individuals, but for economies and societies that need resilience, innovation, and fresh ideas more than ever. Business leaders can design funding, mentoring, and innovation programs that actively include disabled entrepreneurs. Institutions can integrate inclusion into training and incubation programs. Policymakers can embed accessibility and support into every stage of the entrepreneurial process, from education to finance to market access. Some entrepreneurs with disabilities require the support of caregivers, whose status deserves to be formally recognized. Supporting entrepreneurs with disabilities is not charity, it is a strategy for innovation, resilience, and growth. The choice is obvious: either continue to overlook this potential, or build economies that are inclusive, dynamic, and future-ready. Entrepreneurs with disabilities are ready.

About the Authors

Julien Billion holds a PhD in Sociology (EHESS), a PhD in Management Science (Polytechnic Institute of Paris), and a habilitation in Management Science (Polytechnic Institute of Paris). As a professor at ICN Business School and an affiliated researcher at the CEREFIGE laboratory of the University of Lorraine, he is an expert in social innovation and social entrepreneurship. He is the author of numerous articles, books, and documentaries in these fields.

Christel Tessier Dargent is an ESCP Business School alumni and Associate Professor of Entrepreneurship at Jean Monnet University and CoActis Research Lab, Saint-Etienne, France. Previously a manager at Accenture, Christel conducts research on inclusive entrepreneurship and responsible entrepreneurial education, with a particular focus on necessity entrepreneurship and entrepreneurship by persons with disabilities.

Jérémie Renouf leads the Entrepreneurship specialization and the incubator at ISC Paris Business School. His expertise lies in career mobility, hybrid and inclusive entrepreneurship. He holds a PhD in Entrepreneurship and has previously worked as a Startup Project Manager at EDF, as an Entrepreneurship Advisor at AFE (acquired by Bpifrance in 2019), at Boulogne-Billancourt City Hall, and as an Incubator Project Manager at Cnam.

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By João Filipe Pereira

The landscape of organic search is undergoing a profound transformation, shifting from authority-based rankings to intent-driven relevance. João Filipe Pereira explains how algorithms, AI assistants, and evolving discovery behaviours demand a new SEO strategy. He emphasises that brands must align content, product, and visibility with user intent to achieve sustainable growth.

“We can get away with this because we are Brand Y”. I heard this too many times in my career. The days when brands could rely on authority or legacy to secure top rankings are over. Visibility is no longer solely about who you are but about how relevant you are to a user’s intent in the moment. Algorithms, AI assistants, and shifting discovery behaviours have rewritten the rules: you don’t rank because you matter, you rank because you’re relevant… and also because you matter.

Organic search is no longer a channel, but a user behaviour we build products around. This was the key idea I wanted to share with my audience at the Digital Marketing World Forum this year, and it is the idea behind my book “SEO as a distribution game”. When we understand that search is a reflection of intent, it becomes natural that the days of optimising for just Google’s blue links are behind us. Today’s users discover content through AI assistants, TikTok feeds, voice searches, marketplace queries, and rarely with a simple typed keyword.

Moreover, the user funnel is becoming almost a perfect loop: users search on LLMs, which in turn rely on Google results, and then users often return to Google to validate or go deeper. This creates a circular dependency where both platforms feed each other, reinforcing Google’s role while shaping how LLMs surface answers.

This fragmented discovery journey, accelerated by generative AI and privacy-first policies, demands a new playbook. SEO is no longer just technical or keyword-focused; brand recognition and engagement become critical for the success of any business. Brands must be where their audiences are. Organic is now a strategic distribution engine for visibility and growth across digital surfaces. If you want to rank and be discoverable by your customers, your brand needs to matter across the web, and your services or products must be relevant.

I’ve been lucky to collaborate closely with Product teams, and when SEO aligns with Product, it stops seeking permission and starts delivering real impact. In recent years, leading SEO at Eventbrite and now Organic Marketing Growth at Busbud, I’ve witnessed the power of distribution. Eventbrite has been distributing its content to platforms where its audience is active, by working with Google, TikTok, Spotify… At Busbud, we are now attacking the Google space and the recent Google Bus space, but we know our users seek information across searchable platforms, not only on Google.

Be relevant

Today, users need to genuinely love you and your products or services. If the new organic search is about relevance, then the playbook to succeed must evolve as well.

Relevance today goes far beyond keywords. Stop thinking about content and blog posts. Consider your audience and brand, and how your brand, product, and content align with genuine user intent across various discovery channels. This is about your message and the format of the message.

Let me try to summarise this concept in 5 points:

1. Build authority where users already spend time

Your site is not the only touchpoint that matters. If your audience is searching on TikTok, Amazon, Reddit, or AI assistants, you need to show up there with the right content – in the right format – that answers their intent. Being relevant means being present where your users are.

2. Focus on solving real user problems

Stop chasing long lists of keywords and start mapping the problems your customers are trying to solve. When your content, product, or experience solves the underlying problem better than anyone else, relevance follows naturally, regardless of the channel. Keywords can be a good way to find out what problems users are trying to solve, but they shouldn’t define the copy or the message you will put out there.

3. Optimise for validation

Users rarely stop after the first answer. They cross-check, compare, and validate. Make sure your brand builds trust through consistent messaging, transparent proof points (reviews, case studies, testimonials), and credible partnerships. That trust is what converts validation into action.

4. Treat SEO like a business channel

SEO needs to be approached in terms of cost per acquisition, return on investment, and profit contribution. Just like paid media, SEO requires spend – whether on content, tech, or distribution. Track impact at the revenue level, not the ranking level or just traffic. That’s how you’ll defend your budgets in times of cuts.

5. Collaborate deeply with Product and Marketing

Relevance is achieved by integrating SEO within different parts of the business. You know what they say: Product shapes user experience, Marketing amplifies reach, and SEO ensures visibility. The brands that succeed are those where these teams align on a shared growth model. Without that, SEO remains tactical rather than transformational.

The pressure is rising

Everyone is panicking. Some more than others, but all of us, at some point, panicked with the most recent rise of AI and LLMs. Teams are feeling the pressure to find solutions to problems that are unclear or not identified.

Leaders across industries are facing the same pressure: shrinking budgets and increasing scrutiny on every line of investment. Teams can no longer ask for resources based on activity or historical precedent. Leadership needs a clear justification of why an investment matters, what outcomes it will deliver, and how it ties directly to business revenue. For SEOs, this demands a fundamental mindset shift.

The days of reporting on rankings and traffic as proof of success are behind us. Senior leadership isn’t interested in vanity metrics! They expect – because they need it – to see profitability, efficiency, and clear return on investment. SEO must be treated with the same rigour as a paid channel: there is a cost to running it, and that cost must be justified with measurable revenue impact.

In other words, SEO teams must start speaking the language of business. By connecting organic performance directly to revenue, margin, and long-term growth, we transform SEO from a “nice to have” into a core driver of profitability that deserves its seat at the table – even in times of budget cuts.

This August, I had the privilege of joining the State of Play panel at Aviva’s headquarters in London. The big question on everyone’s mind: to panic or not to panic?

What became clear is that even among dozens of experienced professionals and leading experts, no one had a definitive answer. If that group felt uncertain about which tactics to adopt, it’s safe to say the wider industry is facing the same reality. Right now, no one has a clear roadmap for where we’ll land or how best to prepare for the future. There is consensus on two points: the pressure is real, and a shift in mindset is urgent. But when it comes to navigating this new era of LLMs, the truth is: we’re all still figuring it out.

Don’t panic

Despite the noise, AI hasn’t killed Google – and it’s unlikely to. The real story in search isn’t LLMs stealing market share, it’s the rapid expansion and fragmentation of search surfaces. Datos’ Q2 report revealed YouTube searches have tripled year-on-year, Pinterest searches have doubled, and Reddit searches are up 30%. Meanwhile, LLM prompt growth remains modest, with early signs suggesting that the more people use LLMs, the more they still turn back to Google.

The lesson here is clear: don’t fall into AI panic. Instead, step back and think about how to build distributed influence across all these surfaces. That means SEO can’t sit in isolation.

The smarter play is to focus on adaptability: optimise owned content entities for inclusion in LLMs and new AI search features like Google’s Overviews, while applying proven SEO principles: technical foundations, schema, and information architecture. Have presence and be relevant across platforms like TikTok, YouTube, and Reddit.

This is a massive opportunity for SEO leaders: with all eyes on search, use the attention to reclaim your seat at the table, push for an integrated content strategy, and secure the investment needed to drive discoverability. By 2026, the winners will be the teams that break silos, work as one, and deliver the right information in the right places for their audiences.

About the Author

João Filipe Pereira is the author of SEO As A Distribution Game and a leading voice in the search industry. With over a decade of experience driving growth through SEO and product strategy, João has led initiatives at globally recognized companies including TripAdvisor, Eventbrite, EF Education First, and Hostelworld. He currently works as Director of Marketing at Busbud. A frequent speaker, consultant, and Global Search Awards judge, João is known for developing innovative strategies that blend product, content, and search to deliver real business impact.

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By Yousef Khalili

Agentic AI is slowly changing the very foundations of business by allowing systems to act autonomously, make their own decisions and pursue their own goals over time, without requiring constant human intervention. The actual narrative behind this change is not the mediums that drive it but the companies intelligent enough to adapt to it.

We are now in a new period of artificial intelligence development which is no longer just assistive but autonomous. Generative AI wowed the world with what it could create, but Agentic AI is slowly changing the very foundations of business by allowing systems to act autonomously, make their own decisions and pursue their own goals over time, without requiring constant human intervention. The actual narrative behind this change is not the mediums that drive it but the companies intelligent enough to adapt to it.

What is Agentic AI?

Agentic AI is the system that exhibits agency: it can perceive its environment, develop goals, make decisions, learn in real time and is able to perform complex tasks with minimal supervision. In contrast to either traditional automation or even generative AI models, Agentic AI agents are long-lasting, goal-seeking and able to coordinate across domains, tools and timescales.

In other words: if generative AI was a talented assistant, Agentic AI is a reliable operations manager. It never waits to be told what to do, it anticipates, plans and acts.

The technology providers (such as OpenAI, Google, or xAI) are the ones stealing the headlines, but the more interesting developments are brewing behind the scenes in the boardrooms of the business world. Smart businesses are adopting agentic systems to address real-world operational challenges.

There are five lessons we can learn from the early adopters of the Agentic race.

Lesson 1: Give Agents A Mission, Not A Script

Case Example: Siemens Energy

Previously, AI in energy management was equivalent to a calculator – capable of computing when you feed it what to compute. Siemens Energy did something way more interesting. They incorporated Agentic AI in their grid monitoring systems and turbine diagnostics. These agents are not enforcing a set of rules, they are picking up deviations, setting priorities on maintenance schedules and synchronizing with multiple plants, all in real time.

The lesson? Companies that view AI as a co-pilot rather than a tool, realize more returns. Siemens did not feed the system with tasks. They gave it a purpose: to maintain the grid, keeping it stable and efficient. The agent manages the rest autonomously.

Lesson 2: Prepare Agents to Navigate Complexity 

Case Example: Unilever

Unilever has quietly added agentic AI into some parts of its global supply chain. The AI agent is expected to maintain supply resilience across 190 countries. It not only reacts to demand shifts; it predicts shortages, changes logistics, negotiates contracts, and even tells procurement officers about sustainable alternatives. This is not a simple and linear optimization.  We are talking about multi-variable decision-making in action, mapping environmental, geo-political, and economic signals.

Lesson two is about scope: when you constrain your AI agent to low-level tasks, you are not ready to play on agentic scale. Let it handle real-world uncertainty.

Lesson 3: Let Agents Truly Act

Case Example: DBS Bank (Singapore)

DBS Bank has shifted towards autonomous financial agents that are taking action beyond predictive analytics. For example, one of their agents follows real-time financial behavior across accounts, identifies risk indicators, and, on its own, freezes transactions or changes portfolio exposure within pre-approved guardrails, without any human involvement.

It doesn’t simply warn a risk officer. It acts.

Most companies fail at this point. They introduce AI dashboards and forget the last-mile execution. Lesson: Companies don’t get exponential value from agentic AI when they merely embed it in thinking loops. They need to embed it in action loops.

Lesson 4:  Get Agents To Orchestrate Ecosystems

Case study: Lufthansa Group

Airlines are one of the most complicated operational organizations across the globe. Lufthansa is trying out agentic AI to organise crew rostering, aircraft maintenance, weather rerouting and passenger re-accommodation – all with the same objective: minimum disruption.

In this case, the agent is a conductor rather than an analyst. It extracts information in siloed systems that previously were not communicating with one another, models results and implements strategies.

The lesson: agentic systems perform best when you abandon thinking departmentally and orchestrate change at the mission level.

Lesson 5: Make It All Explainable

Case Example: Roche pharmaceuticals

Trust is fundamental in healthcare and life sciences. Roche is using agentic AI in drug discovery and clinical trials tracking. However, their agents are designed differently. Unlike black-box AI systems, they can produce reasoning and audit trails. So in the event of a clinical recommendation being flagged, the system can explain why.

Lesson: Agentic AI must not be synonymous to mysterious AI. Transparency should be given priority from the onset. Explainability is a must in highly regulated industries like healthcare.

What Do These Companies Have In Common? 

These companies did not wait for agentic AI to offer the perfect solution before they implemented it. They had a clear mission, they trusted their agents to evolve over time, and they restructured their business around real results.

The race has started. Those who move fast will end up not only with better AI, but with an entire new operating system for their business.

About the Author

Yousef Khalili is Global Chief Business Transformation Officer and CEO MEA region at Quant AI Inc., which develops cutting-edge digital employee technology. Yousef is on a mission to transform businesses, augment human productivity, and drive profitability through the deployment of Agentic AI technologies globally.

The post The Agentic Race: Smart Lessons From Companies Leading the Way appeared first on The European Business Review.

By Filippo Frangi

From identifying strategic opportunities to enabling faster experimentation, from co-designing with users to reshaping go-to-market strategies, GenAI is pushing the boundaries of how we define and deliver innovation. GenAI is indeed gaining traction as a key enabler across all stages of innovation processes. This shift demands structure, strategy, and measurable outcomes.

GenAI: a General-Purpose Technology with democratic access

The article draws from the latest research by the Startup Thinking Observatory at the Politecnico of Milan University to outline how companies can move beyond novelty and start integrating Generative AI as a structural component of their innovation systems.

GenAI can assist leadership teams in identifying emerging trends, reshaping innovation strategies, and monitoring entire portfolios of innovation initiatives.

GenAI shares the core traits of General-Purpose Technologies (GPTs, which is not the acronym of ChatGPT), such as electricity and the internet: it is versatile, scalable, and capable of enabling complementary innovations across industries. However, it introduces an additional, unique dimension: accessibility. Thanks to intuitive interfaces and relatively low barriers to entry, non-experts can now leverage GenAI for sophisticated tasks, a phenomenon rarely observed with other transformative technologies.

According to Microsoft’s 2024 Work Trend Index ¹, 75 per cent of employees already use AI at work, often informally and before any structured adoption plan. This bottom-up movement highlights the urgency for leadership to harness and regulate this creativity before it scales haphazardly, but often it is already too late!

How GenAI Supports the Innovation Lifecycle in Each Phase

Starting from the four traditional phases that every innovation project must go through, it is easy to understand how GenAI is already delivering tangible value across the innovation lifecycle:

1. Exploration: in this phase, GenAI tools analyze vast datasets to identify emerging trends, unmet needs, and strategic foresight scenarios. They can synthesize market signals and competitive landscapes far faster than traditional methods.
2. Idea Generation: GenAI systems support divergent thinking by proposing a wide array of creative and unconventional ideas. Controlled experiments have shown that LLMs, for instance, can outperform human brainstorming groups in feasibility and impact, though not necessarily in originality².
3. Experimentation and Prototyping: from UI mockups to working code or product sketches, GenAI enables the rapid development of MVPs. This accelerates the “fail fast, learn faster” approach and reduces the time-to-feedback cycle.
4. Execution and Go-to-Market: in this phase, GenAI can assist in personalizing campaigns, automating market segmentation, and generating content tailored to micro-audiences, making market launches more dynamic and responsive.

Beyond the operative stages, the role of GenAI is also becoming relevant at strategy level. GenAI can assist leadership teams in identifying emerging trends, reshaping innovation strategies, and monitoring entire portfolios of innovation initiatives. By turning unstructured data into strategic insights, these tools enable more informed, agile, and forward-looking decision-making processes.

Real-world Applications

Several companies are already demonstrating the practical benefits of GenAI in innovation:

• IKEA used GenAI to design furniture inspired by retro-futuristic aesthetics, challenging its design teams to reimagine product categories.³
• Oreo (Mondelez International) uses AI to accelerate the development of new snack recipes. Their AI tool uses machine learning to generate recipes based on desired characteristics such as flavor, aroma, and appearance.⁴
• Albert Invent, a chemistry company, is leveraging an AI trained on over 15 million molecular structures to identify effective and safe ingredient combinations quickly, predicting physical, toxicological, and aesthetic properties.⁵
• Beck’s created a product called “Beck’s Autonomous,” entirely conceptualized by AI, from the recipe to branding and packaging.⁶

These cases show that GenAI is not only improving internal innovation efficiency but also enabling new forms of user engagement and co-creation. In some instances, companies pursued these projects purely as experimental trials; in others, they addressed more concrete use cases. Either way, these experiences are meaningful examples — often executed with still-maturing tools — that can inspire further applications and strategic refinement.

The Other Side of The Coin: Limits and Risks

To fully leverage GenAI, companies must move from ad-hoc experimentation to structured integration.

Despite the excitement, organizations must remain critical. Several challenges can limit the strategic effectiveness of GenAI. One key concern is the risk of homogenization. GenAI tools trained on existing datasets tend to reinforce dominant patterns, which can inhibit breakthrough originality. This is not only a creative limitation but also a potential driver of bias. By amplifying dominant narratives and patterns found in training data, GenAI can unintentionally reinforce existing prejudices and stereotypes. Another issue relates to the quality of data; outputs are only as good as the inputs, and poor-quality or unrepresentative datasets can lead to misleading or inaccurate results.

Furthermore, there are still numerous ethical and legal ambiguities surrounding GenAI. Questions about the ownership of AI-generated content, the risk of unintentional plagiarism, and the lack of clear regulatory frameworks are pressing challenges that remain unresolved. Finally, even though GenAI can significantly augment creativity, it cannot replace human oversight. The effectiveness of these tools depends heavily on the expertise and critical thinking of users who can steer and validate AI-generated outputs.

Building an Augmented Innovation Model

To fully leverage GenAI, companies must move from ad-hoc experimentation to structured integration. This requires more than tools; it calls for a holistic approach rooted in culture, organization, and collaboration.

First, AI literacy and culture are foundational. Teams need more than access to advanced technologies; they require the right mindset, critical thinking skills, and ongoing learning opportunities. Fostering a culture that encourages experimentation and responsible use is crucial for scaling AI capabilities effectively and ethically.

Second, organizations should establish safe places for experimentations. These environments provide a sandbox for testing GenAI applications in controlled, low-risk settings. Here, teams can explore new ideas, experiment with workflows, and identify best practices that can later be scaled across departments or business units.

Finally, success requires embracing hybrid collaboration. The goal is not to replace human creativity and judgment, but to amplify it. GenAI should be seen as a co-pilot and an intelligent partner that augments human strengths while still requiring strategic direction, ethical oversight, and contextual interpretation from people. Designing systems that integrate human and machine capabilities seamlessly will be a key competitive differentiator in the years to come.

Beyond the Buzzword

Generative AI is not a passing trend. It is a foundational technology that can redefine how organizations innovate, but only if adopted with strategic intent. Companies that move past the hype, invest in capabilities, and embed GenAI into their innovation architecture will move not only faster, but smarter. In a world where change is exponential, the future belongs to those who can innovate with technologies, not just around them.

About the Author

Filippo Frangi, Senior Researcher, Digital Innovation Observatory, Politecnico of Milan

Master graduated in Management Engineering at the Politecnico of Milan, Filippo Frangi is Senior Researcher within the Digital Innovation Observatories. Since 2017, he has been studying how innovation is managed and developed in large enterprises and SMEs. In particular, the empirical and theoretical research activity is focused on the study of organizational and operational models for innovation, adoption of Corporate Entrepreneurship activities, Open Innovation theory and the role of startups. filippo.frangi@polimi.it | https://www.linkedin.com/in/filippo-frangi-005394109

References

1. https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part

2. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4526071

3. https://www.fastcompany.com/90871133/ikea-generative-ai-furniture-design?utm_source=chatgpt.com

4. https://com/2024/12/27/lifestyle/oreos-owner-is-using-ai-to-create-new-snacks-and-get-them-on-shelves-5-times-faster/?utm_source=chatgpt.com

5. https://www.businessinsider.com/how-beauty-product-chemists-are-using-ai-to-test-ideas-2025-5?utm_source=chatgpt.com

6. https://lbbonline.com/news/becks-new-beer-and-its-ad-campaign-were-created-by-artificial-intelligence?utm_source=chatgpt.com

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By Michael J. Provitera and Mostafa Sayyadi

We aim to expand Kotter’s change model to address both scholars and practitioners throughout the world to initiate a new conversation on organizational transformation. Our reasoning is based on the true transformation which has to be team-oriented. We blend our consulting practices with not only practicing leaders but also scholars from leading universities such as, but not limited to, Harvard, UC Berkeley, Rutgers, and Cornell. The C-suite will find our idea novel in approach and scholars will delve into our idea of high-performance transformation so that they can expand on it, criticize it, extrapolate it, and, in some cases, replicate it. Much of what we share in this article has been adapted from our book titled Management Consulting’s Black Box, which summarizes our 25 years of consulting work experience and will be published in the Business Expert Press in 2025.

Introduction

High-performance transformation is at the heart of teamwork. While working as senior corporate executives, we realized that self-managed teams may be self-managed but may not be high-performance teams. This led us to change the name from self-managed teams to high-performance teams. John Kotter, in 2007, coined the term “Leading Change: Why Transformational Efforts Fail” in the Harvard Business Review. Since then, many authors implemented different applications of this idea, which is easily transferred to organizations and companies in a practical and virtuous way.

With Michael as Andreas School of Business senior faculty professor and Mostafa in a senior management consulting role in Australia, we guide managers toward the goal of transformation using high-performance teamwork by expanding on Kotter’s model of change. In this article, gained from our consulting work experience and adapted from our book titled Management Consulting’s Black Box, our effort is to help leaders improve their team performance in organizations. Many organizations are restructuring, reengineering, reorganizing strategies, merging companies, downsizing, quality planning, and undertaking new, in-vogue cultural projects. Having a management mentality to create transformation, despite the presence of quality people in the process, self-managed team transformation will face inevitable failure. There are several categories of pressure for transformation. One is the difference between leadership and management, and the other is the culture of the organization.

The Problem Of Self-Managed Team Transformation And Its Solution

Why do organizations fail? Today, changes in organizations are inevitable. For success, it is necessary to make continuous changes, and an organization that cannot implement these changes correctly and in accordance with its goals will inevitably fail. In this context, organizations commit frequent and common mistakes that accelerate the failure of change. The most common mistakes organizations make are:

1st Mistake: seeking too much comfort

When comfort levels are high, changes always fail to achieve their goals.

This is a fatal mistake because, when comfort levels are high, changes always fail to achieve their goals. The occurrence of change that aims to reduce people’s convenience paralyzes managers; people become defensive; morale is weakened; or even worse, managers confuse necessity with concern, and by showing their concern to employees, they cause them to sink deeper into their known safe haven and even show more resistance to change. When you take away supervisor titles and replace them with team leader, you might as well put up tepees, because people are going to feel a tribe mentality.

2nd Mistake: failure to create powerful coalitions

In order to create successful change, it is necessary to create a coordinated team composed of senior managers, department managers, or heads of departments, in addition to a number of other people who are committed to improving team performance. Team activities that do not have a strong enough coalition will have only limited progress. Teams struggle with tradition and short-term interests, preventing structural change from bringing about the needed behavioral change that comes with high-performance teams.

3rd Mistake: underestimating the power of perspective

Vision plays an important role in bringing about beneficial changes by guiding, aligning, and inspiring people’s activities.^1,2 Some people, understanding the problems of creating change, try to manage their activities quietly behind the scenes and deliberately avoid any discussion in public. Without a blatant published vision to guide decisions, every choice employees face will lead to endless debate.

4th Mistake: insufficient transmission of the vision to the employees

The willingness of employees is necessary in high-performance teams.^3,4,5 People are not willing to sacrifice if they are not satisfied with the current conditions. They must see the benefits and believe that change is possible. Without establishing effective communication, it is not possible to conquer the hearts and minds of employees. Draw the vision clearly in the minds of the team without any doubt to help them fully.

5th Mistake: the presence of obstacles against the new perspective

When employees feel that they are facing obstacles on the way, new, poor job classifications such as team members can reduce effectiveness. New compensation systems or performance evaluation systems can force employees to choose between divesting from a new perspective and focusing on personal resources such as new employment options.^6,7 Things get worse when supervisors refuse to adapt to new conditions because they feel that they are being usurped. Whenever intelligent and benevolent people avoid facing obstacles, they weaken the employees and destroy the transformation.

6th Mistake: inability to create short-term victories

Real transformation takes about eighteen months. If the efforts to create transformation or reconstruction of business and work lack short-term goals that are easy to reach or admirable, the motivation of employees will be lost. Most people do not continue with long-term efforts unless they see signs of the expected results after a short period of time. Most employees give up without short-term victories or resist change because the target is too far into the future.

7th Mistake: premature declaration of victory

After several years of hard work, the employees want to announce the results of the transformation as a victory. Although celebrating a victory is a good thing, it should not be considered a complete victory, and this is a mistake. The changes must be deeply penetrated and institutionalized in the organizational culture, and this usually takes three to 10 years.

8th Mistake: neglecting to stabilize the changes in the culture of the organization

Change takes place and becomes stable when it is part of a new or enhanced culture.^8,9,10  Regression is real and easily accepted. Conscious efforts by leaders must show the importance of change and much work to improve the attitude to improve the attitude employees must be ongoing.

These eight mistakes may be summarized
as follows:

• New strategies are not implemented well.
• With the merger, the expected synergy does not occur.
• Reengineering takes a lot of time and money.
• Downsizing does not control costs.
• Quality improvement programs do not produce the expected results.

The Expansion of Kotter’s Change Model

The challenge of the global economy creates opportunities and threats for everyone and puts companies under pressure. Successful organizations in the change process have learned how to adopt new strategies of integration, reengineering, quality programs, and restructuring. In 2007, John Kotter proposed his model of change. In many cases, scaffolding is used as a success factor. Multi-stage processes with the appropriate authority level from senior leaders provide motivation. This process is effective when it is led by top management with a high-quality leadership steering committee.

Now, we expand Kotter’s change model and, as shown in table 1, present the eight success stages of organizational transformation that correspond with the eight main mistakes.

Stage 1: Recognizing necessity and urgency

Examining the market and the competitive realities by diagnosing current and potential crises. People outside the organization can be useful along with customer relationship management. Additional information can be gathered by suppliers and shareholders.

Stage 2: Creating a guiding coalition

A steering committee with enough authority to lead the transformation and guide the group in such a way that they work as a unified team. A powerful guiding coalition with the right structure, appropriate level of trust, and common goals will steer the organization in the correct direction.

To create an effective guiding coalition, four key features should be considered:

1. The organizational capital of the situation:Are there enough key people involved in this coalition so that other people cannot create a barrier against the transformation?
2. Broad expertise:Are there different departmental experts that are knowledgeable and some that are outsiders to offer an outside point of view so that the correct and intelligent decisions can be made?
3. Credibility:Does the steering committee have a good reputation in the company so that other employees of the company take their opinions seriously?
4. Leadership: Does the steering committee have leadership knowledge, authority, and autonomy so that they can guide the transformation process well?

The combination of trust and a common goal between people with the right and appropriate characteristics can lead to the creation of a strong steering committee.

Stage 3: Creating a vision, mission, and strategy

A vision that guides change efforts is usually five to 10 years out, while a mission could be a daily continuous day-to-day operation. The strategy is much more inclusive of both vision and mission but also guiding principles, goals, and objectives. Thus, vision refers to a clear picture of the future that shows why an organization thrives. In the transformation process, a good vision has three important goals:

• Clarify the development path
• Motivate people
• Keep people focused on the mission.

Most visions have the following characteristics:

1. Provide a picture of the future.
2. Show the long-term interests of employees, customers, shareholders, and stakeholders.
3. Include realistic and practical goals.
4. Clear to provide the necessary decision-making.
5. It is an iterative process that may change.
6. The vision is easy to remember, easy to manifest, and known and practiced by all employees.

The degree of desirability of a transformation vision can be determined by asking the following questions:

• What is the customer value proposition offered by our vision?
• What effect will the vision have on the shareholders and the communities in which the organization prospers and serves?
• What is the effect of the vision on attracting and retaining talented professionals?

Stage 4: Providing an engaging vision

Continuously convey the vision and strategy and create role models that portray the mission and vision. A great vision serves an important purpose. The real power of a vision is revealed when most of the people involved in the transformation activity have a common understanding of the organizational goals and direction. When the sense of urgency is high, employees will be able to create a vision and transfer that vision into the future appropriately. To effectively convey the vision, some important features should be considered:

1. Use simplicity: all technical terms and jargon should be left out.
2. Use metaphors: similes, examples, verbal images are worth a thousand times more than written writings.
3. Use multiple platforms: informal memos and company newsletters, all are effective in spreading the vision.
4. Use repetition: ideas penetrate deeply into people’s minds only when they are repeated and heard over and over again.
5. Use leadership: present models and host monthly praising sessions.

Stage 5: Empowering employees

Changing systems or structures that help people thrive strengthens the vision, encourages risk-taking, and welcomes ideas. Use a customer-centric vision so that the organization continually adds value.

Stage 6: Creating short-term wins

Planning for visible improvements in performance or small victories, whatever they may be, is important to provide an impetus of positive momentum in the company’s vision and mission. Appreciating and giving rewards to the people who make progress possible is very important. Major developments take time and in some cases require great care. Loyal believers want to see clear evidence that the transformation is working. Managing a transformation effort without a major focus on short-term wins is incredibly risky.

A short-term victory has at least the following three characteristics:

• It is visible. A large number of people can
  see if the result is real.
• It is not ambiguous. Clarification and advertising may be necessary.
• It connects the transformation efforts, and it is a victory.

Improving the functions that are learned in a short period of time helps the changes in six ways.

• Provides evidence of good decisions and valuable sacrifices.
• Short-term wins as positive feedback improves morale and motivation.
• They help provide clear vision and strategies; short-term victories provide objective information to the guiding coalition about the validity of their ideas.
• They reduce pessimism and conservative resistance; evidence that clearly indicates the improvement in performance makes it difficult for people to resist the required transformation.
• They keep the leaders in the scene; for the people who have a higher position in the chain of administrative ranks, they provide evidence that the transformation is on its way.
• They bring motivation to people; they turn indifferent people into supporters and reluctant supporters into active helpers.

Stage 7: Celebrating victories

Celebrating victories is not just throwing parties for no reason; it is built on employing, promoting, and developing people who can implement the organizational vision, and individual change agents that are advocates for the mission and change initiatives. As agents of change, each employee plays a critical role that needs to be celebrated.

Major changes, especially in large organizations, require spending a lot of time and money. This money spent must go to operative projects for improvement in the tangible assets of the organization, such as human capital, social capital, and organizational capital.

Emphasizing the development and production of sustainable technologies at home will allow European companies to compete with Chinese peers in the future.

The process of creating transformation needs to have everyone in the organization rowing in the same direction. Reward people for coming on board the change initiative, then halfway through, using short-term victories. The work on the strategic planning process must be coordinated and each step along the way must be communicated. Things to communicate via intranet or paper distribution would cover things such, as but not limited to, restructuring, reengineering, or change in strategic planning, monitored or new training programs, modifying information systems, increasing or decreasing the number of employees, and new enhanced performance evaluation systems. Finally, the stage of summarizing the victories must build upon each other incrementally from an off-site gathering to a full-blown concert or trip to an exotic island.

Stage 8: Opening lock-in cultural norms

Customer-oriented leadership, customer relationship management, and customer-value proposition are derived from intangible assets of organizations such as social capital, organizational capital, and human capital. Thus, productive behavior, more effective leadership, and better management establish a connection between new behaviors and organizational success. This creates tools to guarantee and develop leadership prowess throughout the organization. How this is manifested has to do with the seven stages mentioned above but, without a way of making this transformation stick, all efforts are bound to revert back to inertia.

Culture refers, in this case, to the norms of behavior and shared values among the stakeholders of the organization. Norms of instilling this behavior and sustaining it are common and penetrating methods of action that are found among successful organizations that prosper.

Shared values are important tasks and goals shared by most employees that shape group behavior and often persist over time, even if employees change. Thus, talent management and onboarding new people are very important to organizational success. Culture is important because it can have a great impact on human behavior, while changing it may be difficult.

When, in a transformation effort, new activities are not compatible with existing cultures, they are often subject to going back or regressing, causing inertia. Therefore, tying the knot on positive change is just as important as setting up the transformation process.

Locking in the culture is powerful for three reasons:

1. People are selected based on the culture of the organization with talent management.
2. Culture, like morale, can change easily and this must be monitored, and culture needs to be nurtured.
3. Culture can also be challenged by opposing egos that unconsciously undermine the transformation for self-interests.

These key eight stages have been presented in figure 2 below.

Conclusions

In many transformational efforts, the main axis of the previous culture is not in conflict with the new perspective, although there will be conflict with some of the tried-and-true previous cultural norms. In such cases, linking new activities to old roots while removing incompatible components is a fundamental challenge. This is why we suggest that leading strategic change must be the competency of senior leaders in the C-suite. Institutionalizing a set of activities in a culture that are even compatible with its core values is also a complex challenge. The biggest obstacle to transformation is a group’s culture. Thus, the first step in a big transformation is to change norms and values. Once accomplished, this has to be the organizational mantra instilled in the mission, vision, and guiding principles of the organization. Leaders need to understand the existing culture so that they can raise the level of urgency and necessity for change.

The key to the survival of successful organizations in today’s era of disruptions is effectively leading strategic change. Employees must be able to handle the competitive and constantly changing environment.

About the Authors

Michael J. Provitera is an associate professor of organizational behavior at Barry University, Miami, FL. He received a B.S. with a major in Marketing and a minor in Economics at the City University of New York in 1985. In 1989, while concurrently working on Wall Street as a junior executive, Dr. Provitera earned his MBA in Finance from St. John’s University in Jamaica, Queens, New York. He obtained his DBA from Nova Southeastern University. Michael J. Provitera is quoted frequently in the national media.

Mostafa Sayyadi works with senior business leaders to effectively develop innovation in companies, and helps companies—from start-ups to the Fortune 100—succeed by improving the effectiveness of their leaders. He is a business book author and a long-time contributor to top management journals and his work has been featured in the top-flight publications.
.

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By Gilles Paché

In today’s retail landscape, efficiency is not always the golden rule. Some of the largest retailers have mastered the art of controlled chaos, using supply chain failures to stimulate demand and boost profits. In short, what if chaotic logistics was the key to marketing success? Gilles Paché sets out to explore how unpredictability exacerbates consumer desire, influences pricing strategies, and gives companies a competitive edge.

Regularly reading the trade press and listening to Europe’s top executives makes it clear that logistics is a crucial factor in the success of the retail sector—whether offline, online, or both. A seamless supply chain, optimized inventory levels, and strict delivery management are generally considered essential for ensuring customer satisfaction, maximizing company profitability, and delivering strong returns to shareholders. In e-commerce, the quality of fulfillment operations is often highlighted as critical for building a sustainable competitive advantage¹. However, this dominant view overlooks a far more complex reality: powerful large retailers are thriving despite logistics that, by conventional performance standards, would be deemed “chaotic.” Yet, rather than being a weakness, these inefficiencies appear to drive sales. This raises an intriguing question: could what is typically seen as logistical underperformance serve as a powerful lever for marketing success?

Powerful large retailers are thriving despite logistics that, by conventional performance standards, would be deemed “chaotic.

There is no doubt that this perspective on supply chain management is iconoclastic—perhaps even provocative. But is it really? On the contrary, three key insights highlight the relevance of a heterodox approach to logistics—thinking outside the box, as I explored in a recent book². First, stockouts in-store or online, along with extended wait times, can unexpectedly enhance a product’s appeal and create a sense of desirable scarcity, increasing consumer demand. Second, chaotic logistics can foster an opportunistic and agile business model, prioritizing adaptability and responsiveness over rigid planning while reducing operational constraints. Third, what appears to be logistical inefficiency can serve as a strategic justification for pricing and assortment management policies that maximize a large retailer’s profitability and strengthen its market position. A closer and more nuanced analysis of these perspectives reveals their strategic significance.

Perceived Scarcity: Amplifying Demand

Traditionally, stockouts in-store or online are viewed as failures that harm a large retailer’s profitability. However, research suggests that, in certain contexts, product unavailability can have the opposite effect, as demonstrated by Barton et al.’s³ meta-analysis. When a product becomes difficult to obtain, its scarcity enhances its perceived value. Faced with the possibility of missing out, consumers feel a heightened urgency to purchase, increasing the likelihood of a sale. This phenomenon aligns with scarcity theory, which posits that goods perceived as rare or difficult to access are often seen as more valuable⁴. Large retailers can strategically leverage this mechanism, turning a disruption into a powerful driver of desirability. By applying this approach, a large retailer can encourage customers to return frequently—whether to physical stores or online—fostering loyalty while generating sustained demand for products that are not always in stock.

On the other hand, companies like Brico Dépôt (home improvement and DIY), Costco (warehouse club and wholesale), and Action (non-food consumer goods) deliberately employ strategies that make their products temporarily inaccessible. These large retailers cultivate a “treasure hunt” experience, where consumers understand that if they do not act quickly, the product may soon be gone⁵. While this is not a new approach, it has become increasingly prevalent in sectors such as food, electronics, and fashion, where promotional items and exclusive products are often available in limited quantities. The scarcity of products on shelves—or the speed at which certain items sell out—compels customers to return frequently, ensuring that they do not miss out on a deal. Rather than viewing stock discontinuity as a weakness, these businesses harness it as a strategic tool to attract shoppers, maintain steady foot traffic, and stimulate impulse purchases. Not only does this approach drive rapid inventory turnover, but it also fosters a sense of anticipation and excitement that strengthens brand loyalty.

Some companies take this approach even further, turning logistical constraints into strategic selling points. Announcing long wait times or limited quantities becomes an intentional marketing tool, leveraging consumer psychology. Shoppers, eager to acquire something rare or exclusive, often accept delays or less-than-ideal conditions if it means securing a coveted product. This phenomenon is particularly evident in luxury markets, where scarcity is not just a supply issue but a core branding strategy⁶. Hermès, with its highly sought-after Birkin bags, and Rolex, with long waiting lists for premium watches, deliberately cultivate exclusivity to heighten desirability. Even outside luxury, brands use similar tactics. Limited-edition sneakers from Nike or Adidas are released in small batches to generate hype, while electronics companies such as Sony and Nvidia leverage supply shortages to sustain demand for PlayStation consoles and graphics cards. The perception of rarity fuels anticipation, making products seem even more valuable and desirable.

A similar dynamic is at play with Aramisauto, a key player in the French car distribution market. Unlike traditional franchised dealerships, which maintain planned inventories and predictable delivery schedules, Aramisauto operates with an opportunistic sourcing model. The company buys vehicles in bulk whenever manufacturers like Renault or Stellantis need to offload unsold stock. As a result, its vehicle selection is constantly changing, with no guarantee that a specific model will be available at any given time. Delivery times also fluctuate significantly, ranging from a few days to several months, depending on the vehicle’s origin and logistical factors. However, this approach offers a significant advantage: by acquiring cars at deeply discounted prices, Aramisauto can sell new vehicles at prices up to 30 per cent lower than traditional franchised dealerships. While the unpredictability may frustrate buyers seeking a specific model, the ever-changing inventory creates a sense of urgency, prompting quicker purchasing decisions.

Logistical Chaos and Marketing Agility

Large retailers that excel at accurately forecasting demand, optimally managing stock, and minimizing costs are often seen as “masters of logistics.” In contrast, a more “chaotic” approach enables some companies to respond better to unexpected challenges. Hard-discount companies like Aldi and Action exemplify the urgent need for organized logistical chaos. Rather than relying on rigid forecasts and constantly renewed stocks, they frequently adjust their offerings in response to market opportunities. This strategy allows them to secure highly competitive prices by negotiating exceptional deals with suppliers⁷, without being constrained by long-term assortment planning. The fluctuating assortment also becomes a key asset in attracting consumers, as customers know they will not always find the same products with each visit, fostering a sense of excitement and anticipation. This dynamic keeps customers coming back, enhancing both engagement and sales potential.

The essence of these quotes encapsulates a future filled with promise and possibility. We must remember that automation is not an end, but a beginning—an opportunity to redefine human work and elevate one another.

This business model is based on a high level of responsiveness to buying opportunities, allowing these companies to offer a wide range of products while staying highly competitive. Logistical chaos, therefore, becomes a key advantage for hard-discount companies, which leverage it to quickly adapt to a constantly changing market. By replacing rigid planning with resilient flexibility, these companies optimize operating costs while minimizing waste. In addition, they benefit significantly by reducing fixed costs related to logistical facilities. Reactive inventory management minimizes the need for large warehouses or centralized platforms, instead favoring local supply systems like urban micro fulfillment centers⁸. This operating model not only enables them to stay agile in the face of market fluctuations but also allows them to rapidly adjust their offerings to shifting economic conditions, particularly during times of crisis or inflation. The adaptability of this approach supports long-term sustainability, even in uncertain times.

Moreover, this approach provides significant financial flexibility, which can be reinvested into other strategic areas, such as marketing or customer experience management. For instance, a large retailer adopting this logic can allocate additional resources to promotions, advertising campaigns, or enhancing store design. This strategy can be an effective means of retaining price-sensitive customers while simultaneously boosting foot traffic and increasing sales. Furthermore, the variability in product offerings creates a dynamic buying environment, where consumers are encouraged to return frequently, fearing they might miss out on valuable opportunities. Rather than focusing on occasional stockouts, these large retailers embrace controlled instability, a tactic that does not necessarily harm their overall performance. By leveraging more fluid and opportunistic logistics, they successfully combine competitiveness with adaptability to shifting consumer trends, ensuring sustainable profitability, and long-term growth in an unpredictable, rapidly evolving market.

This is particularly evident in the case of Action, founded in 1993 in the Netherlands, which has experienced significant growth across Europe in recent years, largely driven by its strategic pricing approach. The large retailer consistently offers nearly 1,500 items priced under €1, covering a wide range of products, from household goods to office supplies. This pricing strategy encourages frequent store visits, as customers aim to take advantage of the deals, even at the expense of leaving the shelves in disarray. The product assortment is regularly updated, creating a sense of urgency that drives impulse purchases, as customers are aware that stock levels are limited, and high-demand items may sell out quickly. At the core of Action’s approach is this “bargain-hunting” dynamic, which ensures a steady flow of shoppers without the need for active management of stockouts. Conversely, when products are unavailable, customers often attribute the shortage to their own delay in arriving at the store.

Inefficient Logistics: A Winning Strategy

Instead of fighting against stockout situations in-store or online, large retailers have increasingly recognized that it makes strategic sense to integrate these occurrences as a key competitive lever. Rather than viewing stockouts as failures, they deliberately cultivate them to maintain an aura of scarcity around their products. By controlling supply and artificially extending delivery times, these companies create a sense of urgency and heightened consumer desire. This phenomenon is particularly effective in sectors where exclusivity, originality, and prestige are key values, such as luxury or limited-edition products. More surprisingly, logistical inefficiencies are also used strategically as leverage to justify price hikes, because when supply difficulties are cited, companies find it easier to convince their customers that price increases are unavoidable⁹, as we witnessed during the COVID-19 pandemic and the ongoing war between Ukraine and Russia. This strategy successfully capitalizes on consumer behavior, leveraging scarcity to boost demand and sales.

Founded in France in 2011, Le Slip Français (“The French Brief”) exemplifies how intentionally creating logistical inefficiencies can become a powerful marketing strategy. Specializing in the production and physical distribution of high-quality, locally made underwear for men and women, the brand quickly set itself apart with its unique marketing approach. This includes releasing limited-edition collections, which generates a sense of urgency, encouraging customers to make purchases before items sell out. The company intentionally limits production and distribution, leveraging consumers’ desire for rare and exclusive products to build an emotional connection with its audience. Through its strategic scarcity, Le Slip Français creates an aspirational image of exclusivity and desirability. The brand has successfully turned the logistical challenges faced by its competitors into a strategic advantage. Far from diminishing the perceived value of its offer, these disruptions enhance it, creating anticipation and loyalty among its growing customer portfolio.

Large retailers adopting this innovative strategy are not only boosting their margins, but they are also shaping customers’ perceptions of the product assortment value. By maintaining a degree of opacity around the causes of stockouts, they transform a logistical constraint into a potent marketing argument. The temporary absence of an item heightens the desire to purchase it once it becomes available again, either in-store or online. Powerful large retailers take advantage of this dynamic to segment their customer base, offering programs that guarantee priority access to items in short supply. This enhances the feeling of exclusivity and strengthens the loyalty of regular buyers, especially when they are given timely updates after a stockout¹⁰. The phenomenon extends beyond luxury goods, as limited promotions and seasonal offers are based on similar principles. Therefore, far from being a mere logistical inconvenience, stockouts are increasingly becoming a powerful lever, influencing purchasing decisions and justifying higher prices.

This phenomenon was observed and studied in the context of panic buying after lockdowns were lifted during the COVID-19 pandemic¹¹. Some large retailers capitalize on this dynamic to segment their customer base, offering priority access to high-demand products. This reinforces the sense of exclusivity, strengthening the loyalty of regular buyers and encouraging anticipatory behavior among occasional shoppers. The phenomenon extends beyond luxury items, as limited promotions and seasonal offers operate on similar principles. By deliberately orchestrating logistical chaos, large retailers create the illusion of controlled scarcity, which paradoxically drives increased consumption.

A Deeper Understanding of Contexts

There is no denying it: achieving a high level of logistical performance is generally considered to be an inescapable imperative in the retail industry, and this managerial doxa is taught to MBA students around the world. Yet some companies in the retail industry are succeeding by adopting a more innovative approach that defies this logic. Far from being systematically perceived as harmful, stockouts in shops or online create a scarcity effect that benefits demand. Similarly, chaotic logistics enhance commercial agility, reduce fixed costs, and encourage a more opportunistic approach to conquering new markets. Finally, apparent logistical inefficiency is sometimes used as a strategic lever to justify higher prices, generate in-store traffic, or stand out from the competition. This non-traditional approach has proven successful, even in rapidly shifting market conditions. In short, has not the time come for a serious rethink of the classic performance criteria in the retail industry?

Rather than striving for ultra-optimized logistics at all costs, powerful large retailers are capitalizing on a certain degree of disorder and unpredictability to maximize marketing impact. This approach, grounded in flexibility and responsiveness, offers significant advantages in a competitive environment where consumer expectations are rapidly shifting. While unpredictability may seem risky at times, it allows companies to stand out by providing a more memorable and unique shopping experience. Of course, this is not to say that logistical chaos is always the best choice—this business model is not suitable for every sector or company. It is essential to carefully define the specific contexts in which this approach is beneficial versus harmful¹². Therefore, additional research is needed to better understand the conditions under which a successful balance between order and chaos can become a sustainable, long-term competitive strategy. Understanding these nuances will help businesses adapt to changing markets and continuously improve their approach.

About the Author

Gilles Paché is Professor of Marketing and Supply Chain Management at Aix-Marseille University, and Director of Research at the CERGAM Lab, in Aix-en-Provence, France. He has more than 650 publications in the forms of journal papers, books, edited books, edited proceedings, edited special issues, book chapters, conference papers and reports, including the recent two books: Variations sur la consommation et la distribution: Individus, expériences, systèmes (2022), and Heterodox logistics (2023).

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2. Paché, G. (2023). Heterodox logistics. Aix-en-Provence: Presses Universitaires d’Aix-Marseille.

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6. Fan, L. (2019). Effects of resource scarcity in consumer behavior. Unpublished doctoral dissertation, Hong Kong Polytechnic University.

7. Voigt, K.-I., Buliga, O., and Michl, K. (2017). Business model pioneers: Management for professionals. Cham: Springer.

8. Karaoulanis, A. (2024). “The role of micro fulfilment centers in alleviating, in a sustainable way, the urban last mile logistics problem: A systematic literature review”. Sustainability, Vol. 16, No. 20, Article 8774.

9. Khalil, M., and Lewis, V. (2024). “Price and output responses to supply disruptions in times of high uncertainty”. CEPR VoxEU [online], 22 April. Available on: https://cepr.org/voxeu/columns/price-and-output-responses-supply-disruptions-times-high-uncertainty

10. Kumar, P., Rossiter Hofer, A., and Peinkofer, S. (2023). “The role of scarcity-inducing post-stockout disclosures on consumer response to stockouts”. International Journal of Physical Distribution & Logistics Management, Vol. 53, No. 9, pp. 946-66.

11. Cham, T.-H., Cheng, B.-L., Lee, Y.-H., and Cheah, J.-H. (2023). “Should I buy or not? Revisiting the concept and measurement of panic buying”. Current Psychology, Vol. 42, No. 22, pp. 19116-36.

12. Breugelmans, E., Campo, K., and Gijsbrechts, E. (2006). “Opportunities for active stock-out management in online stores: The impact of the stock-out policy on online stock-out reactions”. Journal of Retailing, Vol. 82, No. 3, pp. 215-28.

The post The Art of Controlled Chaos: How Logistical Inefficiency Drives Retail Performance appeared first on The European Business Review.

By Filip Pesek

Startups thrive on founder hustle, but doing it all can become a growth bottleneck. This piece explores the hidden costs of over-functioning leadership and makes the case for strategic delegation. By letting go and building support systems, founders shift from reactive operators to visionary leaders—unlocking scale, clarity, and sustainable success.

In the early days of a startup, founders often wear every hat. It’s a rite of passage—one minute you’re negotiating contracts, the next you’re triaging emails or troubleshooting a marketing campaign. I know this routine intimately. For years, I prided myself on being the hardest-working person in the room. My calendar was packed, my inbox a warzone, and my to-do list—endless.

At the time, I thought I was modelling strong leadership. What I didn’t realize was that I had become the single biggest bottleneck in my own business.

The Dangerous Myth of the “Do-It-All” Leader

I’m not alone in this. Founders are often told: “If you want it done right, do it yourself.” In the early, scrappy stages of a company, it almost feels like truth. Resources are scarce, trust is still forming, and explaining a task can feel harder than completing it yourself.

But here’s what I learned: this survival mentality doesn’t scale. When leaders hold tightly to every decision and operational detail, growth slows—because execution waits for one person. The business becomes dependent on the founder’s availability, and that dependency comes at a high cost.

What It Really Costs to Do Everything Yourself

On the surface, doing it all can look like efficiency. But underneath, it erodes long-term effectiveness. Here’s what I learned the hard way:

• Lost Strategic Focus: Time spent on admin tasks displaces time needed for high-impact decisions—like product direction, talent strategy, or partnerships.
• Execution Bottlenecks: Your inbox becomes the delay point for projects that need momentum.
• Mental Fatigue: Constantly switching from big-picture thinking to small, reactive tasks fractures clarity and direction.
• Burnout: Over time, the chaos becomes your baseline. You end up reacting, not leading.

The result? A business that becomes harder to steer—and a founder who feels like they’re always running, but never moving forward.

The Real Superpower? Strategic Delegation

My turning point wasn’t a dramatic burnout or crisis. It was a quiet realization that my most valuable work—strategic direction, team culture, and growth—wasn’t getting the attention it deserved. That’s when I hired my first executive assistant. Not to just offload chores, but to build a system of strategic support.

Delegation is often misunderstood as simply handing off tasks. In reality, strategic delegation is about investing in people and systems that extend your decision-making, protect your focus, and amplify execution across the organization. A well-integrated assistant or operations partner doesn’t just “help”—they create leverage.

Breaking the Bottleneck Mindset

Most founders don’t choose to become bottlenecks. It happens gradually, through a series of rational-sounding excuses:

• “It’s faster if I do it myself.”

Maybe once. But over time, this belief creates a culture of dependency and missed opportunities for growth.

• “I can’t trust anyone with this yet.”

Trust isn’t something you wait for—it’s built through clear processes and iterative delegation.

• “Delegation is for bigger companies.”

The paradox is that without learning to delegate early, many companies never grow big enough to need it.

Leadership isn’t about the volume of work you handle alone—it’s about the clarity of direction you provide and the systems you build to support it.

A Scalable Solution—Without Full-Time Overhead

One barrier founders often face is assuming that building this kind of support system requires full-time hires and permanent overhead. But that’s not always the case.

When I founded virtual assistant agency DonnaPro, it was in response to this exact problem. We provide part-time executive assistants who specialize in working with founders—people trained not just to handle tasks, but to manage complex workflows, anticipate needs, and create the operational breathing room leaders need.

The result? Founders shift from “reactive operator” to “strategic orchestrator.” They reclaim the time and headspace to think, build, and lead at a higher level.

Closing Thought

As a founder, your job isn’t to hold everything together through sheer force of will. It’s to build a system that doesn’t collapse when you pause. That’s real leadership.

Letting go isn’t a sign of weakness—it’s a sign you’re ready to scale. And often, the smartest thing you can do for your business is not to push harder, but to get out of your own way.

About the Author

Filip Pesek is the founder of DonnaPro, a virtual assistant agency that empowers founders to scale through strategic delegation. With a background in marketing and entrepreneurship, Filip helps build systems that reduce founder burnout and boost operational efficiency, transforming busy operators into focused, visionary leaders ready to grow sustainably.

The post From Bottleneck to Builder: Why Letting Go is a Strategic Leadership Move appeared first on The European Business Review.

By Jiayi Huang and Xiangming Chen

From a battery maker to the world´s leading electric vehicle producer, BYD’s spectacular rise is an eventful journey fueled by dedication, tenacity, and consistent research and development. This analysis of the giant EV auto manufacturer´s success will help growth-oriented companies fine tune their strategy in the age of transition toward green mobility.

The Chinese EV company BYD, headquartered in the high-tech megacity of Shenzhen bordering Hong Kong, has ascended to the pole position in global green mobility. BYD not only overtook Tesla in selling more EVs in 2024 but also beat Tesla by having developed a more advanced charging system that can charge its latest cars in just five minutes to go 400 km (250 miles), relative to Tesla’s Superchargers, which take 15 minutes to add 320 km (200 miles). In addition, BYD offers its proprietary “God’s Eye” driver-assistance system on cars that cost just below $10,000. How did BYD rise so spectacularly to its current position from a budding battery maker in 1994? While much Western media reports on BYD’s rapid growth, we take an in-depth look into the company’s eventful journey and the real sources of its success over the past three decades.

After persistent investment in R&D for nearly 20 years, BYD achieved breakthroughs in key technologies of electric vehicles and took off in the global passenger vehicle market.

Since its founding in 1994, BYD has leveraged three transformative opportunities to develop its core technologies and expand its businesses around the world. The first opportunity was China’s integration into global supply chains after China intensified market reforms in the 1990s. Between 1994 and 2002, BYD developed a cost-effective system to manufacture batteries for top mobile phone companies such as Motorola. The second opportunity that BYD leveraged was the historic growth of China’s automotive market in the 21st century. BYD built a vertically integrated system to mass-produce internal combustion engine (ICE) and new energy vehicles. The third opportunity was the electrification of the global automotive industry in recent years. After persistent investment in R&D for nearly 20 years, BYD achieved breakthroughs in key technologies of electric vehicles and took off in the global passenger vehicle market. BYD’s founding and current president, Wang Chuanfu, acutely identified the three opportunities when they arose.

From 0 To 1: How BYD Established A Firm Footing In The Automotive Industry* 

BYD’s rise to a top battery supplier

Wang Chuanfu formally founded BYD by registering it in Shenzhen in February 1995 to leverage opportunities in the battery industry. Wang saw enormous potential in the battery market given the increasing demand for electronic products. Wang was a battery expert when he founded BYD. He moved from Beijing to Shenzhen in 1993 when he was assigned to manage a state-owned enterprise that produced nickel batteries. He discovered that the state-owned enterprise could not keep pace with market changes, so he created his own company. As China’s first special economic zone (SEZ), Shenzhen was a pioneer in China’s market reforms and opening to the world. Financial incentives like lower taxes provided by the Shenzhen government, coupled with bordering Hong Kong, created a favorable environment for entrepreneurially-minded people like Wang to pursue their economic opportunities. Wang obtained financial support from his old friends and several companies to found BYD. BYD started with a team of around 20 employees. BYD exemplified a wave of entrepreneurial start-ups around that time, a number of which later turned into highly successful global companies such as Huawei and Tencent (Chen and Ogan 2017).

BYD created cost-effective ways to produce high-quality nickel and lithium-ion batteries. Whereas its Japanese counterparts used automated processes to make nickel batteries, BYD leveraged abundant labor in China to develop a much cheaper method of production. Wang arranged labor and fixtures in an efficient way that achieved robotic functions. After making breakthroughs in nickel batteries, Wang began studying lithium-ion batteries which were more sophisticated and had a bigger market than nickel batteries. BYD soon became the first Chinese company to mass-produce lithium-ion batteries. Wang decided to target the biggest clients in the battery market so that BYD could learn about the highest standards for quality management. Many multinational companies began outsourcing to China around 2000 allowing BYD to become a supplier to Motorola and Nokia in 2001 and 2002 when BYD also underwent an initial public offering on the Hong Kong Stock Exchange, culminating its achievement as a company focused on producing batteries.

BYD’s great success as a battery maker, more than anything else, stems from Wang Chuanfu being a battery chemist at heart. BYD’s competitors quickly stopped trying to compete with Wang’s battery, which was far superior, and instead used BYD as their supplier. By driving BYD to improve its battery technology, Wang achieved great success in making BYD’s batteries better and cheaper than any competitor (Ogan and Chen 2016). Starting out as a battery manufacturer laid the most logical and sustainable foundation for BYD to enter and thrive in the automotive industry.

BYD’s entry into the automotive industry

After the early success in battery manufacturing, Wang Chuanfu made a bold decision to enter the automotive industry. Wang aimed to enter an industry that was bigger than the consumer battery industry and had connections with batteries. He saw the enormous potential of the Chinese automotive market. In the early 2000s, the Chinese government was reforming the automotive market and encouraging families to buy cars. Most people in China used motorcycles or bicycles for everyday transportation. Wang predicted that a historic number of Chinese people would buy cars over the next decade and that the automotive industry would be more energy-efficient and cleaner, creating opportunities for battery manufacturers. He was confident that BYD could produce high-quality cars at low costs after mastering the core technologies, just like its past experiences in battery manufacturing. BYD obtained the license to produce cars by purchasing the Qinchuan Automobile Company in 2003.

Qinchuan did not have full mastery of automobile technologies so Wang led his team to invent new cars. Although Wang was the most interested in electric vehicles, he understood that the technologies and market for electric vehicles were immature. Inventing ICE vehicles could be a transition and help BYD understand the automotive supply chain. BYD initially wanted to procure parts from external suppliers, but it was difficult to find suitable suppliers. Wang decided to pursue vertical integration. Vertical integration was time-consuming at first but enhanced the efficiency and reduced the costs of R&D in the long term. BYD’s current General Manager of the Branding and Public Relations Division, Li Yunfei, comments, “If you rely on external suppliers, they will not tell you their long-term plan for R&D. They usually provide you with the technologies that are the most profitable for them. Vertical integration helps BYD come up with comprehensive solutions to existing problems in automotive products.” BYD produced its first ICE vehicle model called F3 in 2005 and its first battery electric vehicle (BEV) model e6 in 2009. BYD launched F3DM (DM stands for dual modes) in 2008 and became the first company to sell plug-in hybrid electric vehicles (PHEV) in the world.

BYD started developing electric commercial vehicles in 2008. Wang realized then that it would still take a very long time to electrify passenger vehicles; roadblocks include the lack of the charging infrastructure, consumer distrust in relevant technologies, and the high prices of electric vehicles. But Wang saw at least two benefits of electrifying commercial vehicles. First, electrifying commercial vehicles could act as a buffer zone that educates consumers about electric vehicles. Second, electrifying taxis and buses could significantly reduce air pollution because they accounted for over one-third of air pollution from vehicles. The latter has stayed with Wang as a top consideration in BYD’s relentless pursuit of building more and better EVs as a worthy contribution to the climate cause.

Since 2013 BYD’s electric buses have entered major overseas markets such as the UK, the US, Japan, and India. By 2015, BYD K9 electric buses and e6 electric taxis have spread to over 190 cities in 43 countries and regions. BYD’s buses succeeded in different climates and regulatory contexts. For example, BYD delivered electric double-decker buses to London in the 2010s. In fact, Wang walked side by side with President Xi Jinping of China during the latter’s official visit to the UK in October 2015 when London bought more zero-emission electric buses from BYD (Chen and Ogan 2017). This purchase by a top global city with an iconic bus system went a long way to elevate BYD’s brand and global reputation. It also motivated BYD to solve the technological challenges in transforming the K9 model into a double-decker bus, such as a higher center of gravity and limited space for batteries.

Wang has the deepest understanding of the cutting-edge technologies at BYD. He knows how and when the current bottlenecks will be solved. Solving those bottlenecks will completely transform the customer experience.

BYD established a firm footing in the automotive market and managed to maintain its strategic focus on R&D for electric vehicles despite abrupt changes in market conditions. BYD sold around 400,000 to 500,000 vehicles every year in the 2010s. BYD’s revenue declined in 2012 and 2019, coinciding with fluctuations in the Chinese automotive market. The two troughs pushed BYD to increase the efficiency of its management system. In a system of vertical integration, some BYD factories lacked the motivation to reduce the costs and raise the quality of their products because they were guaranteed that their products could be sold to other factories in BYD. BYD thus made significant changes to its procurement system. It used external suppliers as benchmarks and closed some underperforming factories. Some factories started competing with external suppliers in bidding processes.

The year 2019 turned out to be a very difficult one in BYD’s history. Its net profit for shareholders was only 1.6 billion RMB that year, but Wang Chuanfu still invested 8.4 billion RMB in R&D. Li Yunfei comments, “Wang has the deepest understanding of the cutting-edge technologies at BYD. He knows how and when the current bottlenecks will be solved. Solving those bottlenecks will completely transform the customer experience. His technological expertise has helped BYD to develop a long-term vision and strategy. He is like a prophet and a time traveler. He can maintain his strategic focus and avoid being distracted by fluctuations in external conditions. We firmly believe that our future is bright. We will be lucky if market tailwinds arrive sooner. We are prepared to withstand the difficulties if market tailwinds arrive later.”

Back in 2008, Wang described his three green dreams. The first dream was to develop affordable technologies to use solar energy. The second dream was to help humans store energy. The third dream was to build electric vehicles to reduce air pollution. BYD has invested in R&D for solar cells and energy storage power plants since the 2000s. The three dreams have motivated Wang to expand BYD’s presence in other green industries besides electric vehicles at a global level.

BYD’s Take-Off In The Global Automotive Market

BYD released the revolutionary Blade Battery in March 2020, leading an unprecedented wave of breakthroughs. The Blade Battery is a lithium iron phosphate (LFP) battery for electric vehicles and looks like a blade (Figure 1). The Blade Battery has higher energy density than traditional battery packs and increases the range of electric vehicles, which paved the way for upgrading the Dual Mode (DM) technology platform of hybrid vehicles. The earlier versions of the DM platforms primarily relied on fuel. The DM 4.0 platform, released in June 2020, primarily relied on electricity. BYD released the e-Platform 3.0 for battery electric vehicles in 2021, which Wang Chuanfu called the most essential step from electrifying vehicles to increasing their intelligence. The e-Platform 3.0 was a brand-new platform specifically designed for electric vehicles and integrated the most critical technologies of electric vehicles.

Powered by technological breakthroughs, BYD quickly diversified its vehicle models to meet different demands from consumers. BYD currently has four brands and five sales networks in China. The four brands are BYD, DENZA, FANGCHENGBAO and YANGWANG. The bestselling brand is BYD, which has two sales networks (Dynasty and Ocean). BYD stands for “Build Your Dreams”, symbolizing BYD’s green dreams. In China, vehicle models of the Dynasty network are named after Chinese dynasties (Qin, Han, Tang, Song, Yuan, etc.).  The Ocean network looks more youthful than the Dynasty network. DENZA offers a new luxury travel experience. FANGCHENGBAO, meaning “formula leopard” in Chinese, is a professional personalized brand. YANGWANG is a high-end brand. This quartet of brands has provided BYD with a broader and more diversified portfolio of assets.

Wang drives BYD

As BYD’s founder but going beyond a conventional founder’s role, Wang Chuanfu has played a pivotal role in shaping and sustaining both the technological core and cultural meanings of the BYD brands. Li Yunfei recalls, “Not everyone in the marketing team is an engineer, but our marketing is driven by a thorough understanding of our technologies. We have launched some pioneer technologies. Many consumers found engineering concepts very boring, so it was challenging to quickly impress our consumers with the strengths of our technologies. Wang was willing to work with the marketing team in the planning stage of marketing campaigns. He was like a professor giving lectures to students. He translated sophisticated technological concepts into plain words. After his lectures, Wang would double check whether we fully understood. He also has great admiration for traditional Chinese culture, which is reflected in the names of our Dynasty models and the logo of our high-end YANGWANG brand. When we started to design YANGWANG’s logo, Wang told us to borrow from the oracle bone script used in ancient China. While some of us proposed using the oracle bone script of ‘electricity’, other proposals went beyond the oracle bone script. Wang ultimately chose our proposal.” Given its thorough understanding of technologies and consumer demands, it was no surprise that BYD’s sales and revenue took off in 2022. Its revenue jumped from 216.1 billion RMB in 2021 to 424.1 billion RMB in 2022, pushing BYD onto the Fortune Global 500 list. Its revenue further rose to 777.1 billion RMB in 2024 (Figure 2). BYD produced its one-millionth new energy vehicle in May 2021 and its ten-millionth new energy vehicle in November 2024. By February 2025, BYD’s passenger vehicles reached 90 countries and regions (Table 1).

Wang’s personal influence is key to BYD’s brisk overseas expansion through a growing and more internationally informed team of senior executives. BYD sold 4.25 million passenger vehicles in 2024, and over 417,000 of those were sold in overseas markets. Since its first overseas office opened in the Netherlands in 1998, BYD has established over 40 branch offices overseas. BYD opened a factory in Thailand last year and is currently completing factories in Brazil and Hungary. Its overseas branches have gained extensive knowledge of local markets by selling batteries and commercial vehicles. Li Yunfei comments, “Many senior executives of our overseas branches have been working in BYD for over 20 years. They are familiar with foreign culture and BYD’s internal organization. They have laid a solid foundation for BYD’s overseas expansion. In addition, we have incorporated overseas talents into our teams.” Regarding Europe, Li adds, “We want to give European consumers more choices, which will benefit them. We have a high respect for automotive brands in Europe and been learning from the European brands. Market competition can motivate everyone to make progress.”

Wang Chuanfu has continued to prioritize innovation through R&D. In 2024, BYD invested 54.2 billion RMB in R&D expenditure, which increased by 35.7% year on year. In March 2025, BYD’s global workforce reached one million, and over 120,000 of those work on R&D. Li Yunfei comments, “A wise leader is essential to a company’s development. A few years ago, my team was planning to build a powerful public image of Wang Chuanfu like other companies but he asked us to stop as soon as he learned about our plan. He said that we should focus on communicating our technologies and products to the public instead of building individual heroism. People that have interacted with Wang have been impressed by his low-key manner. Over 80% of Wang’s meetings focus on technologies and lead to plans for the medium and long terms.”

From a corporate innovator to a global leader

Continued innovation has become the core DNA of BYD, leading to a series of technological breakthroughs in recent years (Figure 3). While recent, these innovations reflect BYD’s persistent and cumulative investments in R&D over the three decades of its rapid growth. BYD’s passion for innovation has been fueled by the larger environment of Shenzhen as its home city that strongly favors corporate innovation and has nurtured several innovative companies like Huawei and DJI in a dense technological ecosystem. Beyond Shenzhen itself, BYD has benefited from competing against many domestic and international automakers in China’s highly competitive EV market irrespective of government subsidies. It is no surprise that these competitive and innovation-conducive local and national environments have fostered BYD’s cumulative success as a leading corporate innovator.

As BYD has innovated from its home base, it has leveraged its innovative capacity in elevating the BYD brand globally and extending its market footprint across nearly 100 countries. Having spanned all segments of the global EV market, BYD has moved up and forward into one of the world’s leading automotive companies, and more importantly, as a pace-setter in green mobility. At a time when geopolitical turmoil has disrupted the global agenda on climate change and energy transition, BYD has proven as a robust and innovative corporate and national leader in pursuing that agenda.

About the Authors

Jiayi Huang is a senior specialist at BYD’s headquarters in Shenzhen. She researches on international political economy and works on overseas public relations for BYD. She holds a Ph.D. in political science from the University of Pennsylvania, a master’s degree in economics from Duke University, and a bachelor’s degree in economics and mathematics from Trinity College in Connecticut.

Xiangming Chen is Paul E. Raether Distinguished Professor of Global Urban Studies and Sociology at Trinity College in Connecticut and an Associate Fellow at the Center for Advanced Security, Strategic and Integration Studies (CASSIS) at the University of Bonn, Germany. He has published extensively on urbanization and globalization with a focus on China and Asia as well as a frequent contributor on “China in the World” to The European Financial Review and The World Financial Review. He has also conducted policy research for the World Bank, the Asian Development Bank, UNCTAD, and OECD.

Footnote

• The first two sections draw heavily from the Chinese book The Soul of Engineers, which BYD recognizes as its official history. This article including its illustrations also draws from other material and information compiled by BYD unless otherwise noted. The interview with Li Yunfei was conducted in March 2025 specifically for this article.

References

• Xiangming Chen and Taylor Lynch Ogan (2017). China’s Emerging Silicon Valley: How and Why Has Shenzhen Become a Global Innovation Center. The European Financial Review, December/January p. 55-62.

• Taylor Lynch Ogan and Xiangming Chen (2016) The Rise of Shenzhen and BYD—How a Chinese Corporate Pioneer is Leading Greener and More Sustainable Transportation and Urban Development. The European Financial Review, Feb/March p. 32-39.

• Shuo Qin and Yuejia Xiong (2024) The Soul of Engineers: BYD’s Rise During 1994-2024 (in Chinese). (Beijing: The CITIC Publisher).

The post BYD’s Rapid Ascent to the Global EV Leader appeared first on The European Business Review.

The rapid integration of AI into workplaces has transformed how employees engage with their tasks. By automating repetitive work, AI offers a promising solution to boost efficiency and free up time for strategic and creative thinking. Yet, despite AI’s ability to simplify workflows, many businesses are still struggling with an overload of disconnected productivity tools that create constant distractions. While AI can eliminate tedious tasks and create space for meaningful work, the proliferation of such non-integrated platforms risks creating a “ping-fatigue” crisis that leaves teams overwhelmed and exhausted.

I’ve worked extensively with organisations navigating the AI landscape, and I understand the promise of AI to unify workflows and create a more efficient digital experience. The challenge isn’t AI itself, but how businesses integrate it with their wider tools and platforms. The key lies in striking the right balance, leveraging AI as an opportunity to consolidate and simplify workflows, rather than adding to the noise and complexity. When implemented strategically, AI helps create a seamless and stress-free digital experience, while keeping employee well-being front and centre.

The rising tide of digital overload

With various platforms managing different tasks – collaboration software, communication apps, automated workflows – employees must constantly switch between interfaces.

While productivity tools are designed to enable efficiency, their sheer volume has led to an unintended consequence – overwhelmed employees grappling with an influx of digital distractions. From real-time project updates to instant chat messages, employees often find themselves constantly responding to a tidal-wave of notifications, rather than engaging in meaningful work. Research by Gloria Mark, a professor of informatics at the University of California, Irvine, found that people typically take about 23 minutes and 15 seconds to fully regain their concentration. With constant notifications disrupting their workflow, it’s understandable why many employees feel they can never get through tasks effectively if every notification can potentially impair their cognitive focus and productivity.

One of the biggest obstacles is the fragmentation of collaboration tools across different departments. With various platforms managing different tasks – collaboration software, communication apps, automated workflows – employees must constantly switch between interfaces. This “app overload” not only disrupts focus but also creates inefficiencies that AI can help us eliminate. Add to that the stress of the always ‘on’ culture with employees feeling the need to deliver on managerial demands regardless of what they’re doing or the time of day (especially when it comes to global teams). It’s no surprise that teams report feeling more stressed and less productive despite having more “productivity tools” at their disposal than ever before.

Leveraging AI to cut through the noise

To combat ping fatigue, business leaders must take a strategic approach to AI adoption by first uncovering what their organisation truly needs and then incorporating the right AI tools to support those goals. Rather than deploying multiple standalone tools, organisations should focus on integrating AI within a single, intuitive system that consolidates tasks and minimises unnecessary distractions. AI should be seen as the unifying force that streamlines workflows and eliminates redundant processes, rather than an additional layer of complexity. By carefully selecting and integrating the AI tools that align with their specific business objectives, companies can create a cohesive stack that directly addresses operational challenges and enhances workflow efficiency. The right AI solutions can help reduce unnecessary notifications, surface only the most relevant information, and improve overall productivity – all without overwhelming employees.

Companies can also consider adopting AI solutions that incorporate smart prioritisation, where notifications and tasks are surfaced based on urgency and relevance. For example, with Smartsheet, users can configure their notifications to ensure they only receive a specific type of notification on their desired device and can also opt out of notifications like ‘changes to a document’ to reduce the notification noise.

By aligning communication methods with employee needs, organisations foster a more effective and less overwhelming digital work environment, ensuring that technology enhances collaboration rather than becoming a source of frustration.

Beyond technological solutions, implementing a culture that prioritises digital well-being is crucial. Encouraging teams to set clear boundaries, limit non-essential notifications, and embrace productivity techniques – such as the famous Pomodoro technique (25 minutes of focused work followed by a 5-minute break) – can help mitigate mental exhaustion. It’s also helpful to encourage employees to have their ‘focused ping-free’ hour where they can concentrate on tasks exclusively.

Another key element of reducing digital overload is recognising that communication preferences vary among employees. While some may prefer instant messaging on platforms like Teams and Slack, others might find email more manageable, and some may opt for more direct phone or video calls for clarity. Leaders should engage in open discussions with their teams to understand these preferences and, where possible, establish guidelines that respect individual working styles. By aligning communication methods with employee needs, organisations foster a more effective and less overwhelming digital work environment, ensuring that technology enhances collaboration rather than becoming a source of frustration.

Prioritising employee well-being in the AI era

The AI revolution in the workplace is still unfolding, and businesses must remain agile in addressing its challenges. Leaders have an opportunity to reshape how AI is implemented, not as just another tool, but as a way to simplify and streamline work processes and move towards a cohesive, employee-first approach. By thoughtfully consolidating AI tools, respecting individual work styles, and prioritising mental well-being, businesses can create digital environments that truly serve their teams.

As organisations seek to optimise their digital strategies, discussions around AI adoption and workplace well-being will take centre stage. I’ll be speaking at Smartsheet’s upcoming London Summit on June 3, where we will explore these themes in depth – offering insights into how businesses can harness AI effectively while keeping employee experience at the forefront. With registration now open, it’s an opportunity for leaders to engage in meaningful conversations about the future of work in an AI-powered world.

The goal isn’t to implement technology for its own sake, but to build systems that empower employees to do their best work without unnecessary friction. This human-centred approach to AI adoption will distinguish tomorrow’s workplace leaders from those who simply chase the latest innovations without consideration for their impact. As we continue to refine our relationship with AI, let’s remember that the most valuable workplace asset remains human creativity and collaboration – qualities that technology should enhance, not hinder.

About the Author

Caz Brett is a Sr. Director of Product Management responsible for Smartsheet’s Enterprise Administration teams. Caz joined Smartsheet in 2022, prior to which she led product, engineering and design teams at the BBC and a global software development agency.

The post Productivity Versus Ping Fatigue – is AI the Answer to Simplifying our Workflows? appeared first on The European Business Review.

By Suhaib Zaheer 

All Small and Medium-Sized Businesses (SMB) owners know the importance of gaining customer loyalty and trust, in order to grow and scale their business and unfortunately, ambitions and resources are not always aligned. Growing and scaling requires a robust website to reach customers, but the technical expertise of SMB founders is often cited as being a large part of the challenge; especially if they have no prior technological experience and tight budgets. Artificial Intelligence (AI) offers a way to level the playing field, by protecting the brand’s reputation, boosting customer trust and saving time and resources.  

This article reveals how AI is revolutionising website management by offering SMBs access to the innovative tools that were once reserved for big corporations. AI-powered solutions can transform online operations, from proactive issue resolution to enhanced customer experiences, leading to a better customer experience that fosters trust and loyalty.  

Reducing downtime and optimising performance

SMB owners are losing sleep over website crashes, slow loading times, and cybersecurity threats, threatening the reliable online presence that is crucial for business success. Rather than hiring a large web development team, growing businesses can themselves harness the power of AI-powered diagnostics and automation.   

Tools can offer proactive monitoring and rapid issue resolution, significantly reducing website downtime and enhancing overall performance. Continuously analysing server logs, traffic patterns, and user behaviour, AI systems can predict potential problems before they occur.   

Automated diagnostics swiftly identify and often resolve issues without human intervention, minimising disruptions to service—not only saving time and resources, but ensuring a consistently smooth user experience, crucial for customer retention and satisfaction.   

Moreover, AI-driven performance optimisation tools can automatically adjust server configurations, compress images, and optimise code in real-time, leading to faster load times and improved SEO rankings. For SMBs with limited IT resources, these AI solutions provide enterprise-level website management capabilities, allowing them to compete effectively, while maintaining a seamless and responsive online presence for customers.  

Web experiences that create returning customers

Recent Cloudways data reveals that 10% of consumers avoid SMBs due to reliability concerns. Leveraging AI can help proactively identify and resolve website issues before they can negatively impact visitors. This approach significantly reduces the risk of downtime, slow loading speeds, or broken features, all of which can frustrate users and harm an SMB’s reputation.   

While customers don’t notice a website’s efficiency when everything is working well, they will quickly notice an unreliable website. Using AI to take pre-emptive action before issues arise gives customers consistently smooth and dependable experience, fostering trust and loyalty. As customers increasingly expect flawless digital interactions, AI’s ability to maintain high-performance standards is crucial in building and preserving trust in the online environment, ultimately contributing to improved customer satisfaction and retention rates.  

Credibility matters

Credibility is more important than ever. In today’s competitive business landscape, customers can be fickle and easily swayed by enticing offers from competitors. This is  especially true for SMBs, who not only compete against more recognisable, established brands but also work to build their own reputation and customer base to gain brand equity and credibility.    

Consumers and clients can quickly shift their loyalty after even a minor disruption, turning to competitors who may be larger and have more resources. To counteract this, AI-driven solutions are accessible to businesses of all sizes and are able to help SMBs compete by being scalable and cost-effective.     

The future of the use of AI  

The democratisation of technology empowers SMBs to compete on a level playing field with larger enterprises today. The future of AI in SMB operations promises to be even more transformative, extending far beyond current capabilities applications. I predict that in the future:   

• Automated issue resolution will evolve to become even more sophisticated.   
• AI will predict and prevent issues before they occur.  
• AI-enhanced customer support will provide personalised, round-the-clock assistance. Moving on from the stock-answer chatbots we are familiar with today, new tools will leverage natural language processing to understand and respond to customer queries with human-level empathy and accuracy.  
• Workflow optimisation will see AI analysing business processes in real-time, identifying bottlenecks, and suggesting improvements. Machine learning algorithms will continuously refine these suggestions based on outcomes.   
• AI will also play a crucial role in decision-making, providing data-driven insights and predictive analytics to inform strategy on how best to gain customer trust and loyalty.  

AI as an essential business function  

As we look towards the future, it’s clear that AI is not just a passing trend but a transformative force for SMBs. By embracing AI-powered solutions, SMBs can level the playing field with larger enterprises. From enhancing website reliability and performance to providing personalised customer experiences, AI is revolutionising how SMBs operate online.  

The benefits are tangible and far-reaching: increased efficiency, reduced downtime, improved customer trust, and the ability to make data-driven decisions. As AI technology continues to evolve and become more accessible, SMBs that adopt these solutions early will be well-positioned to thrive in an increasingly competitive market.  

The message is clear: the future belongs to those who embrace innovation. For SMB owners, the time to act is now.

About the Author

Suhaib Zaheer is the Senior Vice President, DigitalOcean and General Manager at Cloudways, a cloud hosting provider that offers businesses, agencies, freelancers and more a fully managed, expert hosting management platform. Suhaib joined Cloudways in 2021 as its COO and helped Cloudways dedicate its services to SMBs.  

The post How AI can Help SMBs Build Credibility and Earn Consumer Trust in an Increasingly Competitive Digital Landscape   appeared first on The European Business Review.

By Chengyi Lin and Lluvia Shen

How should incumbent electric-vehicle manufacturers respond to the growing competition posed by Chinese EV makers? Chengyi Lin and Lluvia Shen argue that, rather than following the playbook of their Chinese competitors, incumbents should adopt a more strategic approach tailored to their unique strengths.

China’s electric vehicle (EV) scene has experienced marked growth in recent years. Brands including BYD and Geely have grabbed significant global market share and put pressure on EV pioneer Tesla, as well as traditional automakers. This is largely due to their price advantage, knowledge of local conditions, and willingness to invest in on-the-ground infrastructure.

A dangerous knee-jerk response to the entry of lower-priced Chinese EVs would be to adopt a similar low-cost strategy.

In response to these strong challengers, most incumbents have focused on shoring up their existing internal combustion engine (ICE) vehicle market share and preserving residual value. But although this could be effective in the short term, it hardly spells long-term success amid the shift to more environmentally friendly EVs. The unravelling of the traditional auto incumbents has already begun, with Volkswagen closing multiple plants and the Stellantis Chief Carlos Tavares’s early resignation.

What can traditional automakers in the United States, European Union, Asia and beyond do to catch up? Here are four lessons they can apply to their EV journeys.

1. Differentiate through premium offerings

A dangerous knee-jerk response to the entry of lower-priced Chinese EVs would be to adopt a similar low-cost strategy. If not done well, this approach could lead to eroding margins, fewer innovations, and potentially deteriorating quality. Indeed, the airline industry offers a cautionary tale of the long-term consequences of a race to the bottom; the dramatic fall of Boeing is partly due to the company chasing cost savings and higher margins.

Still, challenges for incumbent automakers abound. Their battery technologies are far behind those of Chinese EV firms. Additionally, their EV products are generally less appealing in terms of the design and digital cockpit. Prices would therefore have to be set below Chinese offerings to lure consumers, which could mean selling at a loss. EV production costs are also much higher compared to both Chinese EVs and ICE vehicles, which makes EVs a much harder sell internally than traditional products.

A potential solution would be to go premium and advocate for consumer value, especially in terms of mid-price to high-end products. Many traditional automakers – think Mercedes-Benz and BMW – have built strong brands over their long histories. By maintaining the high quality, rich customer experience, and stable life-cycle value they are known for, they can continue to differentiate themselves by defending their premium segments. The brand experience goes far beyond the product, from pre-sales to post-sales services. Incumbents can leverage their existing networks and communities – which will take time for Chinese EV firms to build – in order to achieve this.

This strategy has worked in other industries. To counteract competition from fast-fashion labels and contract manufacturers, long-standing haute couture and luxury brands like Louis Vuitton and Hermès have focused on quality, design, and the total customer experience to add value beyond the functionality of their products. This has helped differentiate their offerings from mass-market items. In the tech world, Apple has managed to retain its premium positioning amid the rise of Samsung and Xiaomi by making the brand synonymous with constant innovation.

At this critical time, traditional automakers need to focus on strengthening and evolving their brands to avoid a direct price war with Chinese EV companies. This strategy calls for courage from leadership, as it may cause a short-term loss in market share but could pave the way for long-term success.

Some incumbents have already begun developing advanced technologies for their luxury product lines. For example, Mercedes-Benz has further enriched the in-car experience by introducing an immersive audio system from Dolby Atomos. It has also embarked on a partnership with battery maker CATL to create the EQS luxury sedan and teamed up with battery start-up Factorial to develop solid-state batteries that they hope will revolutionise EVs. BMW has added battery company Solid Power to their list of partners, while Volkswagen has worked with software company Cerence to integrate ChatGPT into their vehicles to enhance the user experience.

2. Forge the right partnerships

Speed is key in an era of rapid technological evolution. Although developing core technologies in-house provides full control and can yield long-term competitive advantage, progress can be slow. Collaborating with makers of EV batteries or even Chinese EV automakers themselves could be a viable alternative.

The right partnerships leverage the strengths of both parties. Incumbent automakers have the brand recognition, access to markets, distribution channels, and connections with local institutions and communities, while battery makers and Chinese EV manufacturers bring advance technologies and low production costs. This combination could accelerate incumbents’ time to market and potentially result in a superior product.

Both sides stand to gain from teaming up. Incumbents could stem the loss of market share, accelerate their product evolution, and uphold their brand image. Battery manufacturers and Chinese EV companies could benefit from the incremental revenues, which could help shore up their bottom line in the face of headwinds such as protective tariffs.

Such a strategy has worked well in other industries. A recent example comes from the world of generative AI, where the partnership between Microsoft and OpenAI combines the market power and corporate access of Microsoft with the rapid development of new technologies of Open AI. This approach is not without its challenges, though. The partnership agreement needs to be negotiated carefully to create a win-win situation. Mistrust or suspicion could eliminate potential benefits.

Encouragingly, many such collaborations have sprouted in recent years. For example, Stellantis has partnered with Chinese automaker Leapmotor to produce EVs in Poland for the European market. Volkswagen has also entered into an agreement with Chinese EV maker XPENG on platform and software collaborations to “drive its e-offensive in China”. The partnership between BMW and Zapata AI has boosted the former’s operational efficiency by reducing idle time and streamlining the achievement of production targets.

3. Orchestrate the mobility ecosystem

One subtle yet profound shift in the automotive industry has been the shake-up of the industry value chain. When it comes to the adoption of new technologies, channels, services, and infrastructure all become critical to attract early adopters and convert consumers.

As younger generations and urban dwellers reconsider the automotive ownership model, automakers old and new are experimenting with mobility solutions such as digital platforms, mobile interfaces, and real-time asset management to ensure availability of cars and lure consumers.

As an example, direct-to-consumer (D2C) stores by EV brands including Tesla and Xiaomi have disrupted traditional dealership networks. The D2C model allows for a direct feedback loop from the consumer back to the manufacturer. Take Tesla CEO Elon Musk, who famously hosts periodic meetings with early Tesla owners to get their input. This shortens the consumer feedback cycle.

As younger generations and urban dwellers reconsider the automotive ownership model, automakers old and new are experimenting with mobility solutions such as digital platforms, mobile interfaces, and real-time asset management to ensure availability of cars and lure consumers. These require broad collaborations across industries to build a new mobility ecosystem. Historically, post-sales services and petrol station networks have not been the centre of automakers’ attention. But creating efficient and accessible charging infrastructure will be essential to get customers on board with EVs.

Incumbents must therefore pay attention to shaping the entire EV ecosystem around their core product. This includes everything from garnering customer feedback and constructing charging stations to influencing policy. The good news is that they have several advantages over newcomers.

First, their deep understanding of the local context could help them build viable solutions without stepping into obvious traps. For example, strategically placing charging stations in and around Paris’s city centre requires tacit knowledge of the local context, which Chinese EV makers may not possess.

Second, incumbents are likely already embedded within their local communities. They often represent national, regional, or local pride, provide employment opportunities, directly or indirectly support local economies, and sponsor local activities and events. For instance, automakers have long been the backbone of the German economy and attract international conferences such as the International Motor Show Germany and incubators like Startup Autobahn.

Third, incumbents could be better positioned to shape regulations and policy. For example, reconfiguring electricity grids in a country to support EV charging goes beyond laying new pipes. The decision is likely to affect various political and economic parties and must be tied back to the national energy security plan. A domestic brand could be much more mindful and influential on this front than foreign newcomers.

Successful examples can be found in retail. In the US, Walmart managed to leverage their scale, technology, and supply chain power to reconfigure their systems around e-commerce and fend off Amazon’s aggressive challenge. They converted many of their Supercenters into warehouses, which won support from their employees and the communities they were operating in. A similar story can be found in China, where JD.com extended their original brick-and-mortar network and built new ecosystems around e-commerce logistics – from last-mile deliveries to local convenience stores. Today, the company stands strong against digital natives like Alibaba and PinDuoDuo.

4. Explore alternative technologies

The Chinese EV industry got a head start on battery technologies in the domestic market. Building on its dominance in current lithium-based batteries, China has already moved on to developing solid-state batteries for EVs. It will be challenging for incumbent automakers to level the playing field in a short period of time. They should therefore explore other pathways for technological advancement. For instance, in addition to establishing themselves as a pioneer in solid-state battery research and production, Toyota has gone against the grain by exploring an alternative battery technology – the hydrogen cell.

Similar lessons can be drawn from the tech industry. Since Microsoft, Google, and Alibaba successfully moved into cloud, fencing off cloud natives such as Salesforce, they invest heavily in GenAI to continue their domination. Today, as they battle it out in the GenAI race, they continue to invest forward in quantum computing, which will become the next battleground in the coming decades.

As incumbents try to catch up with Chinese EV brands on battery technologies, it is equally important to look into the future. It is often challenging for a large incumbent to break with the past, overcome operational and cultural barriers, and speedily roll out new inventions. Beginning work on what they anticipate will be the next wave of disruptive technologies could be a good way for incumbents to leapfrog the competition.

Making the leap

The EV war has only just begun. When facing the new challengers from China, the pressure to put up good quarterly performance figures may influence incumbents to focus on direct competition in the immediate term, which could lead to panic, fear, and chaos.

In fact, incumbents have much more to offer from their brand power, knowledge of and relationships with local communities, and market influence. To regain their footing and take a step forward, established automakers should explore strategic options such as premiumisation, alliances and partnerships, end-to-end ecosystem orchestration, and alternative technologies. This could help them re-establish themselves as pioneers in the long run.

About the Authors

Chengyi Lin is Affiliate Professor of Strategy at INSEAD and a leading expert on digital transformation and sustainability transition. His research focuses on strategic impacts of technologies (e.g. GenAI, renewable energies) and effective organisational changes under uncertainty. Professor Lin serves as board member, CEO advisor, and consultant for multi-nationals and start-ups.

Lluvia (Xin) SHEN has been in the automotive industry since 2012, holding roles in strategy consulting and product management. She specializes in market analysis and strategic planning for the global automotive sector, with a focus on industry transformation and product strategy in Europe and China.

References

1. Chinese Automakers’ Secret to Scaling Up Electric Vehicles. 20 February 2024. Knowledge INSEAD. https://knowledge.insead.edu/strategy/chinese-automakers-secret-scaling-electric-vehicles

2. 3 Drivers of China’s Booming Electric Vehicle Market. 3 January 2024. Harvard Business Review. https://hbr.org/2024/01/3-drivers-of-chinas-booming-electric-vehicle-market

3. Tesla’s Profit Fell 45% in the Second Quarter on Weak E.V. Sales. 23 July 2024. The New York Times. https://www.nytimes.com/2024/07/23/business/tesla-q2-earnings-elon-musk.html

4. VW labour chief sounds alarm on mass layoffs and three German plant closures. 29 October 2024. Reuters. https://www.reutercom/business/autos-transportation/volkswagen-plans-major-layoffs-shut-least-three-german-plants-works-council-head-2024-10-28/

5. Board Accepts Carlos Tavares’ Resignation as Chief Executive Officer. 1 December 2024. Stellantis. https://www.stellantis.com/en/news/press-releases/2024/december/board-accepts-carlos-tavares-resignation-as-chief-executive-officer?adobe_mc_ref=

6. Boeing’s Tragedy: The Fall of an American Icon. 31 January 2024. Knowledge INSEAD. https://knowledge.insead.edu/strategy/boeings-tragedy-fall-american-icon

7. How One Chinese EV Company Made Battery Swapping Work. 28 May 2024. Harvard Business Review. https://hbr.org/2024/05/how-one-chinese-ev-company-made-battery-swapping-work

8. Unheard Of. n.d. Mercedez Benz. https://www.mercedes-benz.com/de/innovation/meilensteine/dolby-atmos/

9. Partnerships for Electric First. n.d. https://supplier.mercedes-benz.com/docs/DOC-2051

10. Mercedes teams up with Factorial to develop solid-state batteries. 10 September 2024. Reuters. https://www.reuters.com/business/autos-transportation/mercedes-teams-up-with-factorial-develop-solid-state-batteries-2024-09-10/

11. Solid Power and BMW Deepen Joint Development Partnership. 21 December 2022. Solid Power. https://www.solidpowerbattery.com/investor-relations/investor-news/news-details/2022/Solid-Power-and-BMW-Deepen-Joint-Development-Partnership/default.aspx

12. ChatGPT01 is now available in many Volkswagen models. 21 June 2024. Volkswagen Group. https://www.volkswagen-group.com/en/articles/chatgpt-is-now-available-in-many-volkswagen-models-18464

13. EU slaps tariffs on Chinese EVs, risking Beijing backlash. 30 October 2024. Reuters. https://www.reuters.com/business/autos-transportation/eu-slaps-tariffs-chinese-evs-risking-beijing-payback-2024-10-29/

14. Stellantis and LeapMotor to produce EVs in 17 June 2024. Fleet Europe. https://www.fleeteurope.com/en/financial-models/europe/features/stellantis-and-leapmotor-produce-evs-poland?t%5B0%5D=Stellantis&t%5B1%5D=Chinese%20OEMs&curl=1

15. Ready for next EV push: Volkswagen enters into agreement with XPENG for fast joint development of two smart e-cars. 29 February 2024. Volkswagen Group. https://www.volkswagen-group.com/en/articles/ready-for-next-ev-push-volkswagen-enters-into-agreement-with-xpeng-for-fast-joint-development-of-two-smart-e-cars-18246

16. https://zapata.ai/news/bmw-optimizes-vehicle-production-planning-using-quantum-inspired-generative-ai-techniques/

17. China to invest more than $830 mln in solid-state battery research -source. 29 May 2024. Reuters. https://www.reuters.com/world/china/china-invest-more-than-830-mln-solid-state-battery-research-source-2024-05-29/

18. Solid state batteries. n.d. Toyota. https://www.toyota.ie/company/news/2021/solid-state-batteries

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By Alessandro Lanteri and Mark Esposito

The rapid development of AI technology has brought in agentic AI systems with the ability to be autonomous and make independent decisions. This will redefine how organizations work and create a solid global economy.

In an era where artificial intelligence is rapidly transitioning from simple automation to sophisticated autonomy, the advent of agentic AI marks a pivotal shift in the technological landscape. Agentic AI systems, characterized by their ability to make independent decisions and act autonomously without continuous human oversight, are poised to revolutionize industries and reshape the workforce. For example, Nvidia CEO, Jensen Huang wants the company to grow to 100 million employees, the majority of which will be digital agents.

This is not merely a speculative vision of the future. Nvidia is already using some of these digital employees to design chips and develop software. Elsewhere, AI agents are also employed by AT&T to detect fraud and optimize network usage and by The Ottawa Hospital to improve patient experience and reduce administrative burden.

As these autonomous agents become increasingly capable of performing tasks that once required human supervision, next-generation enterprises will emerge that are autonomous, scalable, and networked and will surpass conventional models.

Next-Generation AI

This new generation of virtual employees is fundamentally different from the first-generation AI expert systems of the 1950s, the second-generation machine learning models of the 1990s, and even the latest generative AI developments like ChatGPT or DALL-E⁴. These advanced systems represent a new kind of artificial intelligence known as agentic AI because they possess agency (sometimes referred to as ‘agenticness’)⁵ — the capacity to perceive their environment, reason about complex situations, make decisions, and execute actions to achieve specific goals without continuous human supervision. Designed to act independently, these AI agents learn and adapt through their interactions and experiences.

Agentic AI operates through a four-step process for problem-solving:

• Perception: AI agents begin by gathering and processing data from various sources, including sensors, databases, and digital interfaces. This step involves extracting meaningful features, recognizing objects, and identifying relevant entities within their environment.
• Reasoning: A foundation model functions as the reasoning engine. It understands tasks, generates solutions, and coordinates specialized models tailored to specific functions such as content creation, image processing, or recommendation systems.
• Action: Agentic AI integrates external tools and software in order to execute tasks based on the plans it has devised. To ensure tasks are performed correctly, guardrails can be established. For example, a customer service AI agent might be authorized to process claims up to a certain amount, while claims exceeding that threshold would require human approval.
• Learning: Agentic AI continuously enhances its performance through a feedback loop. The data generated from the AI’s interactions is fed back into the system to refine and improve its models. This ability to adapt and become more effective over time empowers businesses to drive better decision-making and operational efficiency.

For example, in the financial sector, an agentic AI could analyze market trends, adjust investment portfolios in real-time, and execute trades independently to maximize returns while managing risk. These same tasks are still performed by people in some financial boutiques and by people supported by AI in larger financial institutions. The key distinction between agentic AI and other forms of artificial intelligence lies in autonomy and capacity for independent action (table 1).

Strategic Advantages of Agentic AI

The long-term promise of any technology depends on its ability to confer some unique competitive edge. Agentic AI indeed offers strategic advantages that go beyond traditional AI systems, by expanding some of the known benefits of AI — operational efficiency and cost reduction — and empowering new benefits — improved decision-making and scalability and flexibility.

• Operational efficiency. Agentic AI can autonomously handle intricate, multi-step processes that still require significant human intervention with current AI systems. This reduces the operational burden on employees and ensures that critical services are maintained around the clock — because AI agents operate continuously without fatigue — and so improves overall productivity.
• Cost reduction. Automating tasks with agentic AI reduces labor costs and minimizes errors, leading to savings. Agentic AI optimizes the use of resources such as materials, energy, and time, contributing to cost-efficiency and sustainability goals.
• Improved decision-making. Agentic AI can process vast amounts of data in real-time, providing immediate insights and enabling quicker, more informed decision-making. This leads to better strategic alignment and responsiveness to market dynamics.
• Scalability and flexibility. Agentic AI systems can adjust in real time to changes in the environment, market conditions, or organizational strategies, ensuring optimal scale, continuity, and resilience. They can be scaled up or down on demand, in a similar fashion to scaling cloud computational power, without the delays associated with recruiting and training new staff.

The strategic benefits of agentic AI are compelling. Moreover, though developing agentic AI is expensive, deploying it is “effortless”⁸. Therefore, as soon as agentic AI services become available, businesses will rush to adopt them.

Trajectories of Agentic AI

With widespread adoption, agentic AI will gather data that accelerate its performance (table 2) and therefore magnify its impact on organizations and workers.

Short-term evolution

In the immediate future, agentic AI applications will look like refinements of the current AI trends toward operational efficiency, achieved by automating routine and repetitive tasks. AI agents will handle administrative duties such as data entry, scheduling, and basic customer service inquiries. Early adopters in sectors like manufacturing, logistics, and healthcare will leverage agentic AI for tasks such as predictive maintenance, supply chain optimization, and patient monitoring.

Medium-term transformation

As agentic AI matures, its integration into organizations will become more profound. In the medium term, job roles and organizational structures will be transformed. AI agents will take over tasks that feel complex to humans. Decision-making processes will evolve. For example, agentic AI will contribute to strategic planning by simulating scenarios and forecasting trends with a level of speed and accuracy unattainable by humans alone. Organizations will restructure to maximize the benefits of agentic AI, adopting flatter hierarchies and more agile team configurations. Finally, the workforce will undergo significant changes. While some traditional jobs may diminish, new roles centered around AI — such as AI ethicists, strategists, and maintenance specialists — will emerge. Continuous learning will become imperative as employees must adapt to rapidly evolving technologies.

Long-term disruption

In the long term, agentic AI is anticipated to fundamentally disrupt entire industries and redefine the nature of work and organizational structures. Visionaries like OpenAI CEO Sam Altman have envisioned scenarios where companies could grow to unicorn status under the management of a single individual⁹. With agentic AI, one-person unicorns will become the norm in certain sectors. Autonomous operations will empower disruptive business models, with AI agents managing core functions with minimal or even no human oversight. For example, in industries such as transportation, the widespread adoption of fully autonomous vehicles and logistics networks could revolutionize mobility and supply chains. As market conditions evolve, agentic AI systems will dynamically scale to meet demand. Nvidia CEO Jensen Huang has predicted that “AI’s will recruit other AI’s to solve problems” , highlighting a future where autonomous AI agents work together to address complex challenges without human supervision.

Next-Generation Enterprises: Autonomous, Scalable, and Networked

Historically, humans with human intelligence have designed jobs for humans, leveraging human skills and coordinating tasks that humans can perform. As technology evolves, it has been incorporated into these tasks and their organization, gradually refining jobs over time. Presently, humans still play a critical role in hybrid work systems built on collaborative intelligence, where tasks at which humans excel are intelligently integrated with those at which machines excel, achieving performance levels that would otherwise be impossible.

As agentic AI masters new skills, future tasks may be redesigned by AI agents within agentic meshes in a way that could potentially eliminate human involvement altogether or relegate humans to serving as inputs within machine-first systems of value creation.

Over time, however, AI agents will eventually “find each other, collaborate, interact, and transact” in an interconnected ecosystem, which can be called an “agentic mesh”. Interconnected AI agents can exchange data, insights, and resources in real-time, creating a dynamic network that functions as a cohesive whole. This interconnectedness allows for seamless coordination and optimization of complex systems without human supervision. As agentic AI masters new skills, future tasks may be redesigned by AI agents within agentic meshes in a way that could potentially eliminate human involvement altogether or relegate humans to serving as inputs within machine-first systems of value creation.

The original logic of a one-person unicorn may have been that one human can supervise and control AI performing the tasks humans would perform. That too might evolve into a system where AI agents supervise tasks that other AI agents would perform.

The emergence of agentic AI is set to revolutionize the business landscape by empowering next-generation enterprises that are autonomous, scalable, and deeply networked.

Autonomous. Agentic AI autonomy allows enterprises to operate with greater agility and responsiveness. For example, in the manufacturing sector, autonomous AI agents can oversee production processes, adjust parameters in real-time to optimize efficiency, and predict maintenance needs to prevent downtime — all without direct human intervention. This leads to higher productivity and the ability to adapt swiftly to changing market demands or unforeseen disruptions.

Scalable. The scalability of next-generation enterprises is greatly enhanced by the capacity of agentic AI to handle vast amounts of data and manage complex operations efficiently. AI agents can be replicated and deployed across multiple functions and regions without the limitations inherent to human labor. As business requirements grow, enterprises can scale their operations seamlessly by deploying additional AI agents, ensuring consistent performance and quality. This scalability is not only vertical but also horizontal, allowing enterprises to expand into new markets or add new services rapidly. For instance, in customer service, AI agents can handle increasing volumes of customer interactions simultaneously, providing personalized support to a global customer base without the need for proportional increases in human staff.

Networked. Agentic AI also fosters the development of networked enterprises, where businesses are interconnected through AI agents that collaborate and communicate across organizational boundaries. These networked enterprises leverage agentic AI to form dynamic ecosystems that facilitate real-time data exchange, shared insights, and coordinated actions. In such an ecosystem, AI agents from different companies can interact to optimize supply chains, align production schedules, and respond collectively to market trends or disruptions. For example, in the logistics industry, AI agents representing manufacturers, distributors, and retailers can synchronize their operations to ensure timely deliveries, reduce inventory costs, and enhance overall efficiency.

Conclusion

The autonomous, scalable and networked nature of the next generation of enterprises enables the creation of a complex web of AI agents that continuously communicate, learn from each other, and adapt their behaviors accordingly. This interconnectedness enhances the ability of enterprises to innovate and respond to changes collectively. Innovations and best practices discovered by one AI agent can be quickly disseminated across the network, benefiting all connected entities. This results in a highly adaptive business environment where enterprises are not isolated entities but integral parts of a larger, intelligent network.

Moreover, the combination of autonomy, scalability, and networked operations allows next-generation enterprises to implement radically innovative business models. Organizations can operate with leaner structures, reducing overhead costs associated with large human workforces while maintaining — or even improving — service quality and operational efficiency. Resources previously dedicated to routine tasks can be reallocated to strategic initiatives, research and development, and enhancing customer experiences. Additionally, the networked approach opens up opportunities for collaborative value creation, where enterprises co-develop products or services, share resources, and enter new markets collectively.

By embracing agentic AI, next-generation enterprises can operate more efficiently, innovate rapidly, and collaborate effectively within interconnected ecosystems. This new paradigm redefines how businesses function, fostering a dynamic and cooperative global economy where the collective capabilities of networked enterprises unlock unprecedented opportunities for growth and value creation.

About the Authors

Dr. Alessandro Lanteri is a Full Professor of Strategy at ESCP Business School where he teaches and directs executive education programs globally. He helps executives and students navigate turbulent environments and seize the opportunities of hyper-transformation. His recent books are CLEVER. The Six Strategic Drivers for the Fourth Industrial Revolution (Lioncrest, 2019), Innovating with Impact (The Economist, 2023) and Financial Social Innovations. A New Framework to Understand the Social Innovations Disrupting the World of Finance, from Crowdfunding to Bitcoin (Routledge, 2024).

Dr. Mark Esposito is a professor of economics and public policy with appointments at Hult Int’l Business School and Harvard University. He equally serves as an Adjunct Professor of Public Policy at Georgetown University’s McDonough School of Business. He co-founded the Machine Learning research firm, Nexus FrontierTech and the EdTech venture, The Circular Economy Alliance. He has equally co-founded The Chart ThinkTank and The AI Native Foundation. He was ranked by Thinkers50 in 2016 as one of the 30 rising business thinkers in the world and was shortlisted for the Breakthrough Award in 2019 and the Strategy Award in 2023.

References

1. Goel, S. (2024). Jensen Huang Says He Wants Nvidia to Be a Company with 100 Million AI Assistants. Business Insider, Oct 14.

2. Robuck, M. (2024). AT&T Arms Agents for Next Phase of GenAI Revolution. Mobile World Live, Jul 18.

3. The Ottawa Hospital (2024). The Ottawa Hospital Introduces AI-powered Digital Teammate to Share Information with Staff, Patients, and Visitors. The Ottawa Hospital, Jun 13.

4. Gill, SS. et al. (2022). AI for Next Generation Computing: Emerging Trends and Future Directions. Internet of Things 19: 100514.

5. Shavit, Y. et al. (2023). Practices for Governing Agentic AI Systems. OpenAI Research Paper,

6. Pounds, E. (2024). What Is Agentic AI? Nvidia, Oct 22.

7. Lanteri, A. (2021). Strategic Drivers for the Post-Pandemic Era. The European Business Review, March 24.

8. Puutio, A. (2024). The Agentic AI race Is on, and the Blue Chips Are All in. Forbes, Nov 15.

9. Confino, P. (2024). Could AI Create a One-Person Unicorn? Sam Altman Thinks So — and Silicon Valley Sees the Technology ‘waiting for us’. Fortune, Feb 4.

10. Broad, E. (2024). Agentic Mesh. Principles for an Autonomous Agent Ecosystem. Towards Data Science, Nov 19.

11. Lanteri, A. (2017). Tesla Is Fixing Its Automation Problems with Collaborative Intelligence. Hult blog, Thought Leadership.

12. Moravec, H. (1990). Mind Children. The Future of Robot and Human Intelligence. Harvard University Press.

According to what is known as Moravec’s paradox, tasks that are effortless for humans — such as motor skills and social interactions — are challenging for machines to replicate whereas, tasks that are difficult for humans, like complex mathematical calculations or analyzing large volumes of data, are relatively straightforward for machines. For example, an algorithm can predict a patient’s risk of a particular condition based on their medical history and lab results, but it struggles to grasp the nuances of the patient’s individual cases or consider their social and environmental factors.

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Small businesses often face unique challenges in scaling their impact while juggling limited resources such as funding, sales, customer care, talent, and time. In our previous article, Small Employers 2025: Scaling Impact on Customers, Community & Capital, we explored how small businesses can achieve sustainable growth by adopting scalable talent strategies and utilizing the PTP (Process, Tools, People) Method to optimize business operations. Now, we focus on an equally crucial factor: the strategic management of time and delegation. Time is one of the most valuable yet finite resources for business leaders, and its allocation directly influences scalability, efficiency, and long-term growth.

Recognizing the value of your time, core vs. non-core functions, and whether you’re investing vs. spending time on activities are critical principles small business leaders can leverage to scale their impact and business. However, the challenge lies in recognizing that time must be managed with the same discipline as financial resources to yield optimal results.

The Value of Time

Time is more than a conceptual limitation—it is an operational asset that dictates business success. Many entrepreneurs fall into the trap of believing they must handle every aspect of their business, but this misallocation of time often results in stagnation and exhaustion. When we work IN the business, we can lose sight of key leadership functions that enable us to work ON growing the business. The opportunity cost of engaging in non-strategic tasks is substantial, detracting from core business development initiatives.

Time is more than a conceptual limitation—it is an operational asset that dictates business success.

Numerous articles in Entrepreneur Magazine say it’s paramount to know the value of your time and systematically evaluate each activity against a time-based calculation. If a task takes an hour, and an hour of your time is worth $100, evaluate the ROI of spending that hour on that activity versus outsourcing the task to someone you pay $25 per hour, and use your hour to focus on core business strategies such as customer retention, business development or brand repositioning. The key to scalability is leveraging your time to maximize impact.

Distinguishing Core vs. Non-Core Work for Strategic Time Allocation

For solopreneurs and small business owners, time is an even scarcer resource and must invested wisely to support sustainable growth. Without the luxury of large teams, every hour spent on non-essential tasks is time taken away from revenue-generating activities and business development. To optimize time allocation, start by distinguishing core vs. non-core activities.

Core functions are activities that directly drive customer value, enhance competitive advantage, and generate revenue, such as strategic planning, business development, client engagement, and product innovation. Core roles can change and evolve as a company grows and develops. So, a periodic evaluation is advisable.

Non-core roles are the positions that support core work. These are typically essential yet non-strategic tasks that are not needed 40 hours per week and can be outsourced or automated. Some possibilities include administrative support, data processing, bookkeeping, and marketing. Don’t fall into the trap of thinking of non-core roles as unimportant. They are often valuable to quality operations but do not directly impact a customer’s perception of your business.

Core and non-core roles vary from industry to industry. Properly defining these roles before hiring ensures efficient resource allocation and maximized productivity. Moreover, businesses that proactively evaluate their operations and reassess these classifications are better equipped to pivot and scale in a competitive environment.

Effective Delegation as a Growth Lever

Once you define what your core vs. non-core activities are, it’s time to consider what and how to delegate to process, tools and (lastly) people. Finding the right mix helps you get the most value out of each of those resources.

To delegate with impact, we revisit the PTP Method: 

Processes: Create repeatable, well-documented systems

• Develop processes around objectives and measurable goals that align with your long-term vision to ensure consistent value delivery.
• Review and optimize your existing processes to eliminate bottlenecks, streamline operations, and enhance productivity and consistency. 

Tools: Leverage technology that complement your processes

• Automate where possible by tapping into software tools to handle repetitive administrative tasks like invoicing, scheduling, and email management.
• Embrace Artificial Intelligence (AI) to automate routine process workflows and responses, such as using bots for customer service.
• Ensure tools integrate seamlessly with your existing processes and platforms to enhance productivity.

Once these two steps are complete, it’s time to outsource to people.

People: Maximize the unique thinking capabilities of people

• Leverage freelancers and virtual assistants to take on specialized or time-consuming tasks non-core work, allowing more time for core business activities.
• Utilize human support for critical thinking, creativity, and product/service innovation.

Successful leaders transition from individual contributors to strategic orchestrators, ensuring that the right people execute the right functions to drive efficiency and scale.

Successful leaders transition from individual contributors to strategic orchestrators, ensuring that the right people execute the right functions to drive efficiency and scale. Additionally, leveraging fractional support offers access to specialized expertise without the commitment of full-time roles, providing further flexibility and scalability.

Scaling You with Intention

Business scalability is not merely a function of increased revenue or team expansion; it hinges on effective time utilization. Recognizing time as a finite strategic asset, prioritizing high-impact initiatives, delegating non-core tasks, and leveraging technology enables business leaders to create sustainable growth pathways.

Ultimately, scaling a business requires a conscious and strategic effort to maximize the most limited resource: time. By mastering time management and delegation, entrepreneurs can enhance their operational effectiveness, drive meaningful impact, and establish a scalable, resilient business model.

For further insights on strategic hiring and scaling your impact, visit ResultsResourcing.

About the Author

Elizabeth Eiss is a well-known speaker on entrepreneurial growth and a sought-after expert on the future of work, business performance, and culture, on-demand talent/virtual staffing trends, as well as leadership transformation from intrapreneur to entrepreneur. After decades of running Fortune 500 business operations, she launched ResultsResourcing, a virtual fractional talent platform, and service to help solopreneurs and small business owners find the resources they need to grow and scale.

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By Ralph Geertsema, OP Lumijärvi, and John Wass

Introduction

Over the recent years, AI has conquered the world by storm and has been widely used so far for GenAI with LLMs and chatbots in companies. Results are great and it seems that employees are enthusiastic to adapt new tools to increase their productivity. However, most of these tools are based upon public data and intelligence gathered from it. Ritter and Lu have asserted that the next way in AI will concentrate on enterprises’ own data. We foresee that this next wave of AI will also open up opportunity to utilize the immense power of AI to improve companies’ performance and profitability in particular.

We see that there is a huge potential for AI across multiple business functions. Especially, we have already seen how the new wave of AI enables integrated financial forecasting and product profitability analysis across finance, marketing, and sales.

Enhancing product profitability

One of the basic questions any company needs to answer is what product-services mix to offer to which customer segments. To answer that question accurately and in a data-driven manner, management needs to understand better the profitability of their services, products, and customers in a timely fashion.

Most companies analyze their product and customer data by gross margin. The main reason is simply that this data is somewhat easily available from ERPs. When it comes to fixed costs, many companies do not allocate those to the products or the customer. The primary cause is that it is difficult, and you need to apply, for example, an activity-based costing principle. This is not easy, mainly because the data you need is not only in the ERP but in various production and logistic systems and Excel sheets. In addition, master data about products and customers is always a challenge in any company, especially due to acquisitions and system changes.

The capability of AI to perform complex and large-scale data harmonization and integration at speed is phenomenal and has never been seen before.

The unique value that AI can bring to the product profitability domain is three-fold and these are real boosters to some major drawbacks of the past. First, the capability of AI to perform complex and large-scale data harmonization and integration at speed is phenomenal and has never been seen before. This is especially relevant in setting up allocation engines and maintaining and keeping product profitability systems up to date. Once the algorithm has “learned” how an allocation or assignment of cost should happen, this will automatically be applied to similar transactions.

Second, the ability to drive multiple views over the data by customer and market segment or by product and / or services is unprecedented at this speed and multi-dimensionality. Third, once the time dimension is added to this data set, we can start to understand causality, which means that we can understand what actions lead to which outcomes. Altering pricing, special promotions, and campaigns are always assumed to drive sales and revenues, but what happens to profitability has been impossible to track at scale and in detail up to now.

This is where AI can act as an enabler to bring the different domains and data sources (sales, marketing, finance) together and show its real strength. In fact, there are companies that can analyze their product, service, and customer profitability at net profit level using AI and create a competitive advantage by choosing the right customers and producing the right products and services at the right cost (see figure 2).

Case example

Many retailers still look at their business through the traditional lenses of revenue and gross margin. This lens creates blind spots that can cost retailers 10–20 per cent of their profits. One $10bn US retailer had a large and promotionally active loyalty program focused on increasing their revenue. When looked at through the lens of profitability utilizing an AI-based solution, it turned out that 35 per cent of their highest loyalty tier customers were unprofitable. These over-promoted loyalty customers had one common characteristic that was easily identified. The company quickly took action to: 1) slightly reduce promotional spending to unprofitable customers, 2) focus promotions away from a particular set of low-profit services (made unprofitable by promotions), and 3) restructure the loyalty program incentives to reward more profitable products and purchasing behavior. The result was a 5 per cent increase in company profitability with continued revenue growth.

As the case example shows, with AI, imperfect data is not a limitation and the company created a visibility to net profit for every transaction. This creates a great platform for various use cases in companies such as:

• Cost optimization: break down your general ledger and dynamically assign costs down to every transaction from your business and analyze costs across production, marketing, and sales to optimize profitability.
• Customer segmentation and product mix: cluster your customers, products, and operations data into clear segments of high profit, low profit, and losses for customer segment and product strategic decision-making.

In addition, you can do revenue forecasting by predicting product demand and revenue by integrating market trends and sales data.

Conclusions

What we can see with the start of using AI for product profitability is that it will start to bring insights into the company that can lead to further, deeper insights in the following domains:

• Revenue and sales forecasting
• Demand and capacity planning and forecasting
• Integrated Sales and Operations planning

The use of AI in the product profitability space is proving to be a big step forward in this domain, bringing product profitability fully back into the spotlight. This will lead to much better accessible, faster and more accurate insights for companies in their evaluation of profitable and loss-making products, segments, and markets.

About the Authors

Ralph Geertsema, Global program director, successful in driving high energy teams, with a passionate focus on delivering successful programs and achieving results. Has spent extensive time as a big-4 consulting director for EY, Finance Consulting Leader for Europe at TCS and office of the CFO EMEA leader at FTI.

Olli-Pekka Lumijärvi, Ph.D. (Econ.), Managing Director, Profit Isle, a former Managing Director at Accenture. Author of numerous articles and books.

John Wass, Co-Founder and CEO of Profit Isle, an MIT STEX25 startup based in Cambridge, MA, USA. A serial entrepreneur with a track record of building and scaling companies. Holds a master’s degree from MIT in Logistics and a B.S.E. from Princeton. Co-authored the book Choose Your Customer: How to Compete Against the Digital Giants and Thrive.

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By Mostafa Sayyadi and Michael Provitera

Now, a critical and unanswered question is: How can CEOs develop an effective innovation culture so that their companies can achieve greater business success? If you are looking for an answer to this critical question, then this article analyzes the Tesla innovation culture to solve this problem. We identified the important characteristics of a highly impactful innovation culture at Tesla. This secret weapon of Tesla in our new world is no longer secret.

Introduction

In an empirical study in Australia in 2024, we asked 689 Australian senior executives to list the characteristics of an innovation culture. We found that about 91 per cent of them listed characteristics such as intellectual courage, risk-taking, and a flexible and non-hierarchical structure. We felt that this was a great start to an innovative culture, but we also added the following tenets to move the company toward more innovation and creativity: more commitment by all employees to think outside the box; providing more support from lower levels; empowering people on the front lines; flatter structures; and using steering committees to lead change. These are tenets that we have learned from Tesla. A lack of proper understanding of the leader’s responsibilities is one of the reasons why the development and maintenance of a set culture of innovation fails. The development and maintenance of a culture of innovation is one of the main responsibilities of leaders. A simplistic view of culture and innovation as only a list of pleasant and attractive practices demonstrates negligence on the part of leaders. Thus, too much bureaucracy and mechanistic cultures are not warranted today and will ultimately mean the death of innovation. In this article, we will look at Tesla as one example of a powerful innovative culture. We focus on Tesla as an example not only because it is the best at an innovative culture but because it is truly dynamic in this area of business and cultural cohesiveness. Finally, an applicable model will be presented for executives to better spur an innovation culture in their companies.

Tesla’s golden key is to stay current and innovative in a world in which dinosaurs are dying every day.

In the new era of digital and AI disruption, innovation is the only way to succeed and survive in business today, and the right mix of strategy and market share is the way to be profitable.^1,2,3,4,5 Tesla’s golden key is to stay current and innovative in a world in which dinosaurs are dying every day. If Tesla does not constantly improve and innovate, lower prices, or increase battery distance, it will not be able to stay on top of the electric vehicle market. Tesla shows us that innovation is a slow, gradual, and permanent movement into the future.^6,7,8 Fortunately, getting caught in the trap of spending big money to implement innovation models is not the best way to develop innovation.^9,10 Another way that is much more reliable and involves less cost is to create and maintain a culture of innovation the way Tesla does. This way focuses strongly on empowering employees on the front lines to provide more support from lower levels of the organization, favors flatter corporate structures, and uses steering committees to lead change.

A culture of innovation involves the human and intellectual capital of the organization. Leaders at Tesla are aware of this and consider human and intellectual capital as key capital to remain competitive, and accordingly invest in people to spur an innovation culture. One key point for the innovation culture at Tesla is more commitment by all people as organizational intellectual capital to think outside the box. At Tesla, employees are encouraged to challenge the status quo and they are allowed to test, trial, and even fail at times. Thus, members of the organization are challenged to think beyond their roles, create innovative ideas, and ask exploratory questions without fear of retribution. Gregersen, a leading scholar in asking questions to gain control of any situation, contends that “as disruptive innovators, from Albert Einstein to Jack Dorsey, put it, ‘Question everything!’” We now add to this expert knowledge, “Strategize Everything, Leave Nothing to Chance!”¹¹ Psychological safety is developed throughout the organization through the continuous collective participation of members of the organization in exploring innovative ideas and asking questions. We found that the best human resource capacity involves a set of people with exceptional interpersonal skills, coupled with expertise as engineers. Shipley, a Harvard Business Review author, put it plainly and simply in an article titled “How Tesla Sets Itself Apart.”¹²

Tesla’s speed in innovation in the market for high-end vehicles is more like a Google or an Amazon than an automaker. And its soaring market valuation is a clear sign to all automakers that they’ll need to develop more innovative, Tesla-like business models in order to survive.

The other key principle that Tesla uses is that they have mastered all aspects of culture. Their culture of innovation shows itself in qualitative ambitions in products and services, where the synergy of the sum of the ideas of individuals is captured as a team of salespeople. Everyone at Tesla is in sales, and everyone at Tesla is in innovation.

The Tesla formula for success is not innovation by itself, it is innovation plus a dynamic culture based on teamwork. Tesla continues to find new opportunities and novel solutions to real-time customer concerns. They remain creative and experimentative. They continuously offer innovativeness aimed at developing new automobile updates, extensive customer service, and a failsafe process for buying a car.

The Key Principles of Tesla’s Innovation Culture

The initial idea of Tesla originated from the adventurousness and natural exploration of man and was a symbol of individualism and perfectionism. Tesla products depicted a new form of human life, which showed itself in change and transformation. People only knew of cartoons featuring the future. Tesla felt that there was a need to separate man from fossil fuels and move toward clean and renewable energy. This is not only the symbol of the American culture but also encouraged in other parts of the world. The dynamic and consistent image of the electric vehicle strengthened the idea of cleaner air coupled with better efficiency. What turned these unknown ideals into Tesla’s driving force for the electric car industry were five key principles of Tesla’s innovation culture.

1. Developing flatter corporate structures coupled with intellectual courage

Empowered employees are allowed to think outside the box, provide innovative ideas, and enthusiastically challenge the status quo.

In Tesla’s approach to innovation culture, flatter corporate structures are effectively developed, intellectual courage is increasingly espoused, and empowered employees are allowed to think outside the box, provide innovative ideas, and enthusiastically challenge the status quo with the goal of achieving higher ideals. These key techniques have helped Tesla to be ranked by Boston Consulting Group as one of the most innovative companies in the 50 World’s Most Innovative Companies of 2023.¹³ For example, on a recent visit to a Tesla dealership in North America, a Tesla owner came in with a dangling part dragging on the street, a scary feeling for a battery-operated car with a battery exposed. The service manager told the customer, “Where is the car?” He then proceeded to walk over to the car, bent over, ripped the part off the bottom, and stated, “You can fix this if you feel the need to, but it is a part that will not harm the vehicle or the battery. The battery is wrapped and sealed,” he said. We have reviewed many innovative organizations around the world and we have never experienced a dedicated customer service representative like this one person at Tesla. Thus, failure to develop a culture of innovation coupled with decentralized decision-making will lead to an impediment to success. The marginalization of intellectual courage coupled with a lack of challenging the status quo will lead to the development of bureaucracies that will bury the culture of innovation.

2. Taking risk under strict supervision

The culture of innovation at Tesla is very similar to the personal characteristics of Elon Musk, such as Musk’s intolerance of paying additional costs for inefficiency and incompetence. Building on Frederic Winslow Taylor’s effort to find the One-Best-Way to run a shop floor, Musk encouraged intellectual courage, high risk-taking, and idea generation. This company has one of the most accurate forms of hiring and managing human resources. Lack of work is not tolerated in any way, and all members of the organization are under strict supervision, while enjoying work in a work environment imbued with a culture of innovation and a flexible structure. Tardiness and lack of respect for the customer are not acceptable. Tesla managed to create an innovative culture through an effective performance management system.

3. Distinguishing between successful failures and unsuccessful failures

At Tesla, innovative ideas are collectively and collaboratively reviewed by a steering committee to identify what is best for the customer. According to IMD’s Center for Future Readiness Report in 2024, this technique has secured Tesla’s innovation rank in the top spot in the automotive industry.¹⁴ The ideas enter the review and improvement stage after being selected and then enter the implementation phase. At this stage, failure or success are two options. Tesla distinguishes between the successful failures and the unsuccessful failures that they can learn from to improve. Unsuccessful failures are tolerated but not praised, while successful failures are endured and are part of the knowledge management database of the Tesla learning environment.

4. Learning continuously

Another key principle is that Tesla’s innovation culture overcomes innovation barriers by paying close attention to testing ideas. Many things in use today by customers driving a Tesla are in beta mode. Through regular testing of ideas with rigid discipline, Tesla is the ultimate learning organization. According to specified standards (the cost of successful failures and unsuccessful failures), steering committees at Tesla review ideas in consultation with operational-level experts to determine which ideas are worth testing and which are not. In light of this discipline and consensus, Tesla optimally utilizes the insights and innovations of experts who are closer to the market and anticipates future success better than competitors. At Tesla, choosing an idea for testing does not mean it will be tried, and the costs incurred to test ideas under the umbrella of standards are spent in the most effective way possible.

5. Thinking and innovating beyond formal roles

To get a movie accepted for production at Disney, you have to work there. Unlike Disney, Tesla provides a culture of innovation which is the flagship of the intellectual development of the members of the organization and encourages them to think and create ideas beyond their roles. Tesla also recruits people who have the potential to generate ideas and can provide feedback (both positive and negative). This psychological contract draws people to Tesla to work there. There is ample opportunity for strategic views and technical approaches to issues at Tesla.

We suggest that executives use these five key principles of Tesla’s innovation culture and implement the following applicable model to develop an effective innovation culture in their companies.

In Conclusion

Tesla is a good example that has proven qualities of an innovative culture. According to Baumgartner, “candidates are seeking workplaces where they can intertwine their beliefs with those of the company and work together on a common vision of purpose and success. Great culture should provide continuous alignment to the vision, purpose, and goals of the organization.”¹⁵ At Tesla, employees are empowered and engaged, they feel valued, and would like to be heard more. Tesla maintains a strong innovation culture, which provides the context for idea generation and the intellectual courage of employees, which ultimately improves the level of innovation. By doing what Tesla is doing, more companies can improve their innovation level, better predict their future success, and thrive in a world of digital and AI disruption.

About the Authors

Mostafa Sayyadi works with senior business leaders to effectively develop innovation in companies, and helps companies—from start-ups to the Fortune 100—succeed by improving the effectiveness of their leaders. He is a business book author and a long-time contributor to top management journals and his work has been featured in top-flight publications.

Michael J. Provitera is an associate professor of organizational behavior at Barry University, Miami, Florida. He received a B.S. with a major in Marketing and a minor in Economics at the City University of New York in 1985. In 1989, while concurrently working on Wall Street as a junior executive, Dr. Provitera earned his MBA in Finance from St. John’s University in Jamaica, Queens, New York. He obtained his DBA from Nova Southeastern University. Michael J. Provitera is quoted frequently in the national media.

References

1. Knight, G. & Cavusgil, S. (2004). “Innovation, organizational capabilities, and the born-global firm”. Journal of International Business Studies, 35 (2), 124–41. https://doi.org/10.1057/palgrave.jibs.8400071

2. Kabir, M.N. (2019). “Innovation”. In: Knowledge-Based Social Entrepreneurship. Palgrave Studies in Democracy, Innovation, and Entrepreneurship for Growth (pp. 163–204). Palgrave Macmillan, New York. https://doi.org/10.1057/978-1-137-34809-8_6

3. Asemokha, A., Musona, J., Torkkeli, L. & Saarenketo, S. (2019). “Business model innovation and entrepreneurial orientation relationships in SMEs: Implications for international performance”. Journal of International Entrepreneurship, 17(3), 425–53. https://doi.org/10.1007/s10843-019-00254-3

4. Anand, J., McDermott, G., Mudambi, R. & Narula, R. (2021). “Innovation in and from emerging economies: New insights and lessons for international business research”. Journal of International Business Studies, 52(4), 545–59. https://doi.org/10.1057/s41267-021-00426-1

5. Andreini, D., Bettinelli, C., Foss, N.J. & Mismetti, M. (2022). “Business model innovation: a review of the process-based literature”. Journal of Management and Governance, 26(4), 1089–121. https://doi.org/10.1007/s10997-021-09590-w

6. Schuijt, L. (2016). “A New World Is Already Here: Lessons from Radically Different Organizations”. In: Neal, J. (eds) Handbook of Personal and Organizational Transformation (pp. 1–36). Springer, Cham. https://doi.org/10.1007/978-3-319-29587-9_16-1

7. Fink, T.M.A., Reeves, M., Palma, R. & Farr, S. (2017). “Serendipity and strategy in rapid innovation”. Nature Communications, 8(1), 1–9. https://doi.org/10.1038/s41467-017-02042-w

8. Recanati, A.M. (2023). “Tech”. In: AI Battle Royale (pp. 67–141). Springer, Cham. https://doi.org/10.1007/978-3-031-19278-4_4

9. Sánchez, F. & Hartlieb, P. (2020). “Innovation in the Mining Industry: Technological Trends and a Case Study of the Challenges of Disruptive Innovation”. Mining, Metallurgy & Exploration, 37(4), 1385–99. https://doi.org/10.1007/s42461-020-00262-1

10. Lammers, T., Guertler, M., Sick, N. & Deuse, J. (2023). “It’s Coming Home Down Under – The Potential of Digital Work to Overcome Australia’s Challenges in Reshoring Manufacturing”. In: Shajek, A., Hartmann, E.A. (eds) New Digital Work (pp. 161–70). Springer, Cham. https://doi.org/10.1007/978-3-031-26490-0_10

11. Gregersen, H. (2013). “Use Catalytic Questioning to Solve Significant Problems”. INSEAD KNOWLEDGE. https://knowledge.insead.edu/leadership-organisations/use-catalytic-questioning-solve-significant-problems

12. Shipley, L. (2020). “How Tesla Sets Itself Apart”. . https://store.hbr.org/product/how-tesla-sets-itself-apart/H05EXJ

13. Manly, J., Ringel, M., MacDougall, A., Cornock, W., Harnoss, J., Apostolatos, K., Baeza, R., Kimura, R., Ward, M., Viner, B., Izaret, J., Backler, W., Lukic, V., Duranton, S. & de Laubier, R. (2023). “Most Innovative Companies 2023”, Boston Consulting Group. https://www.bcg.com/publications/2023/advantages-through-innovation-in-uncertain-times

14. IMD’s Center for Future Readiness (2024). “Tesla fends off hot competition from China to lead auto sector in Future Readiness Indicator”. https://www.imd.org/news/competitiveness/tesla-fends-off-hot-competition-from-china-to-lead-auto-sector-in-future-readiness-indicator/

15. Baumgartner, N. (2020). “Build a Culture That Aligns with People’s Values”. Harvard Business Review. https://hbr.org/2020/04/build-a-culture-that-aligns-with-peoples-values

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UK businesses are at a critical crossroads in an era of unprecedented economic complexity. The recently announced UK government’s Autumn Budget with its £40bn in tax increases and heightened employer National Insurance contributions has created a challenging landscape in which teams are expected to do more with less.

Slower growth, increased taxation, and tightening budgets are putting significant pressure on businesses across sectors, meaning traditional approaches like across-the-board cuts or simple workforce reductions are no longer sustainable or practical. In the face of these challenges, companies must empower teams of all sizes to continue delivering on their objectives through fostering a culture of innovation, strategic resource allocation, and adaptive management. This will require leaders to reimagine organisational structures, invest in targeted efficiency improvements, and create agile frameworks that allow teams to maximise their potential while remaining within financial margins and continuing to prioritise long-term strategic goals.

The collaborative advantage

Economic uncertainty is like sailing through unpredictable waters. Smaller boats are often more agile than ships. They can change direction quickly, navigate through narrow passages, and adapt to sudden weather changes. The crew’s communication, preparedness, and ability to work together become their greatest asset – not the size of their vessel. Similarly, modern teams aren’t defined by their size but by their ability to collaborate, adapt, and innovate. Often, it is the smaller teams that operate with precision, purpose, and efficiency, with each member understanding their role and working towards a shared vision that cuts through complexity.

The key to unlocking efficiency is not working harder but smarter. As the pressure to become more efficient continues to mount, businesses must recognise the role of technology. Technology is more than a supportive tool; it is a crucial strategic asset. Platforms that offer real-time collaboration, automated workflow management, and intelligent resource allocation should no longer be considered luxuries but essential infrastructure for competitive businesses.

Connecting dots across the organisation

Organisations that are impacted by tightening budgets may see historically robust and collaborative teams face pressure to adopt a more concentrated approach, often resulting in siloes. This shift can cause teams to become more insular, prioritising self-sufficiency at the expense of shared problem-solving. The drive to assume complete responsibility – often to avoid ‘troubling’ others – can lead to missed opportunities to tap into existing expertise and resources from other teams. It can also significantly impede innovation and create systemic inefficiencies, effectively wasting valuable resources.

It is the smaller teams that operate with precision, purpose, and efficiency, with each member understanding their role and working towards a shared vision that cuts through complexity.

To avoid this, leaders need to help connect the dots for teams across the business. This can include encouraging them to ask for help, asking on their behalf sometimes, and making introductions across the organisation. Leaders must also be aware of the work happening in other departments and, importantly, any overlaps that can benefit their initiatives or could be more efficient in terms of unnoticed repetition. By doing so, they can identify opportunities for teams to support each other, leveraging collective knowledge and resources.

Here, technology, specifically collaborative work management platforms, can be the key to unlocking intelligent frameworks to optimise processes, reduce redundancies, and liberate latent potential within existing resources. For instance, project management tools can offer visibility into ongoing work across teams, making it easier to identify where collaboration can occur. By integrating these technologies, organisations can create an environment where asking for help is normalised, and collaboration is streamlined, leading to more efficient and effective operations.

Turning limitations into launchpads

Every great transformation begins with a moment of necessity – when traditional methods fall short, and teams are forced to reimagine what’s possible. In times of economic pressure, businesses often find themselves at a crossroads where they must innovate or risk falling behind. This necessity drives creativity and encourages teams to think outside the box, exploring new ways to achieve their goals with limited resources.

By leveraging Smartsheet, the event management team within HP’s North America Commercial Marketing group significantly increased efficiency and productivity. By automating project tracking and planning, the team boosted the number of HP-led sales and marketing events from six to 26 per quarter, reduced email communications by 90 percent, and cut event turnaround time from 84 days to 54 days. This transformation not only streamlined their processes but also enhanced collaboration and communication, substantially improving their overall operations and allowing them to handle a higher volume of events without additional headcount.

Organisations can transform economic pressure into a competitive advantage by embracing technology that enables smarter working. This isn’t about replacing human talent but amplifying it—creating systems that allow teams to focus on high-value, creative problem-solving instead of getting bogged down in manual, repetitive tasks. Strategic technology adoption is a force multiplier, allowing smaller teams to achieve outsized results, break through traditional productivity barriers, and demonstrate that resource constraints can catalyse innovation.

As UK businesses navigate this increasingly complex economic terrain, those who invest strategically in collaborative work management technology will prevail. The following 12 months will demonstrate that adaptability, powered by intelligent technological solutions, is the true marker of organisational resilience. The businesses that will thrive view current economic constraints not as limitations, but as impetus for reimagining their operations.

Technology is more than a tool in this transformative landscape– it is a strategic lever for reinvention, agility, and flexibility. By embracing a forward-thinking approach that prioritises intelligent innovation and strategic technological integration, UK businesses survive economic uncertainties and potentially redefine their competitive advantage in an increasingly competitive market.

About the Author

Sarfraz Ali, VP, EMEA: As Smartsheet’s VP and General Manager of EMEA, Sarfraz is responsible for its business operations across the region. He is leading Smartsheet’s growth and development, driving Smartsheet’s strategy to increase brand awareness.

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By Aurélie Jean, Mark Esposito, Terence Tse and Danny Goh

Artificial intelligence and its rapid emergence have proven to be a double-edged sword. While its benefits are numerous, it also has the potential to bring grave consequences. In this essay, four experts from the fields of technology, AI, and digital transformation provide a framework for making the most of AI with low risks.

Today’s rapid emergence of AI for research and development (R&D) has opened up a myriad of use cases across different industries. We stand to gain the benefits of AI in general, and with the right level of project planning, we can deliver high business performance improvement. These are exciting times for AI. These are also times of contradiction: every story covering unprecedented successes is matched by other articles of concern over threats of unintended consequences. We want to develop AI to improve our lives. But we also want to protect ourselves from the bad things.

So, how can we build better tools to live better lives and use our tools to prevent life’s catastrophes? In the modern world, the very best time to do that is in research and development planning. We need ways to guide our innovative thinking and planning. Here, we are offering one such possibility.

The Recursive “More 3P” AI Transformation Framework

The definition of a recursive algorithm continuously seeks to break down the problem that the software is being asked to solve into smaller instances of the same problem. Instead of a solution to the problem, our proposed “More 3P” AI Transformation Framework intends to be a comprehensive disciplined approach to solution development.

The “3P” refers to the three-dimensional realms considered in the R&D guidance: Prediction, Personalization, and Precision.

Prediction:

Predictive data analytics help ensure that organizations can, and in near-real-time, forecast conditions, trends, outcomes and behaviors more accurately, leading to informed proactive planning and decision-making. When considering how to apply AI in any given field, predictive simulations come first to mind. Indeed, by capturing the signals and patterns within the underlying mechanisms and logic of past events or a given phenomenon, algorithms can anticipate (or predict) a similar event in the near or long-term future.

In past decades, ever-better processing and collection of data have enabled real-time gathering and automated curation of datasets that can be used to train AI.

Of note is that one could pay attention to the model’s capability to predict unique, singular, or new events resulting from the simulations, either autonomously or with human subject matter experts (SMEs) oversight in the given field or industry sector.

Such “predictives” can also help identify threat risk potential hidden – for example technology discrimination and environmental impact – within the opacity of the algorithms driving the simulations, again with SME human oversight.

Personalization:

Personalization, on the other hand, indicates a potential for customizing services, products, and experiences that are tailored to individual users (consumers, customers, clients, and/or value-chain partners) based on demographics, preferences, and behavioral data to enhance product or service provision, satisfaction, and loyalty.

In past decades, ever-better processing and collection of data have enabled real-time gathering and automated curation of datasets that can be used to train AI. Additionally, up-leveling advances made on AI models make possible highly personalized recommendations or actual modifications of the delivery of products and services in general. Such increased capacity for personalization brings new business opportunities in improved design, production and delivery of more personalized products and services to customers.

How to Embrace the Recursive 3P AI Transformation Framework Approach

We expect More Predictive, More Personalized and More Precise business, work or production processes by employing formal design and systems thinking approaches that fully anticipate and consider AI transformation opportunities.

A use-case-driven approach should be used when adopting the 3P Frame by asking the following questions: What are the business transformation opportunities envisioned? What are the problems that can be anticipated? What are the threat risks?

We offer the More 3P AI Transformation Matrix, as depicted in Figure 1, which presents a list of all tasks for each of the three Ps. Here are the steps to building and using an AI Transformation planning matrix:

1. 1. List all the tasks in which AI is already being, will be or can be applied;

   2. For each task, list how this task can become more precise and/or more predictive, and/or more personalized;

   3. Identify tasks that have substantially similar or common ways to more of each P dimension;

   4. Identify tasks that have the most influence on precision, prediction and personalization to identify the tasks that will bring the most to the business;

   5. Reiterate this matrix over time while moving forward to the AI transformation of the target process;

   6. Tell the stories of what went right, what went wrong, and what came next.

During the matrix planning process, it is useful to remember that this is simply an R&D guidance mechanism for model development. The simpler, the better. This enables development teams to actively and iteratively apply The More 3P Matrix to make ever-increasingly smarter, and more effective planning decisions.

The Promise of Business-Transforming Performance and Return on Investment

A simple framework and matrix means it can be more rigorously applied. In its simplicity, thoughtful detail, and rigor lies its power as an important planning tool. “More” performance improvement within the context of the 3P Framework Matrix may also mean improvement in planning for abeyance and mitigation of downside risk instances such as technology discrimination, for example, techno-racism, and algorithmic biases.

This is made possible by measuring the “more” quotient levels in each of the 3P realms and their evolutionary stages over time. Indeed, being more precise, more personalized and more predictive over baseline measures enforces project concepts as a matter of science and engineering.

The More 3P AI Transformation Framework is a proactive approach to continuous process improvement that voluntarily compels the full and willing participation of designers, developers (both data scientists and process engineers), and business-side leaders.

Technology development teams and business leaders must collaborate. They need to collaborate at every stage to design, develop, test, and operationalize. The underlying machine learning operations and/or generative artificial intelligence operations, as applied to the algorithmic models being developed, require business leadership to help ensure that the model’s aims, in terms of “More 3P AI,” meet all design criteria represented in the matrix.

If not, the systems may not run correctly with a resultant drag on business performance and return on investment for the company as a consequence. Poor governance may well result in the unintended consequences of imprecise (loose) AI model development. The More 3P AI Matrix, at its best application, prevents that.

Forward-Leaning

The More 3P AI Transformation Framework is a proactive approach to continuous process improvement that voluntarily compels the full and willing participation of designers, developers (both data scientists and process engineers), and business-side leaders.

This matrix must be planned and implemented with no-option fidelity as a “mission critical” matter to ensure these software systems meet stringent performance guidelines, specifications, and necessary policy and governance guardrails, all geared toward achieving true AI-led business transformation.

The More 3P AI Framework Matrix should likely lead the development of a business case for the proposed AI project models. This may apply particularly in mature corporate software development organizations. What makes it to the matrix and is fully listed and described will inform the business case criteria. For the AI start-up or early-stage venture, the 3P Framework Matrix may represent a clear, easy-to-understand way to introduce to all stakeholders what the business of the business is.   

When pursuing AI Transformation within an organization, it’s useful to envision it through this Framework lens as it demonstrates how the organization can empower itself to take the best advantage of AI. The faster this can be fully articulated and demonstrated to leadership, the faster competitive advantage can be attained.

Furthermore, delineating how the business can evolve to become a More 3P organization within the business case cum an applied 3P AI Transformation Framework during the AI transformation provides a straightforward narrative of AI’s impact. This storyline goes beyond just the expected growth, profitability and efficiency performance gains. This narrative powerfully conveys AI’s business value, resonating with all stakeholders—employees, customers, value chain partners, and investors—by showcasing tangible business operations and enhancements to outcomes.

Embedding Effective Governance

Demonstrating near bullet-proof effective algorithmic governance in the 3P AI Transformation Framework is crucial as it addresses various challenges, such as data privacy, sovereignty, ethical considerations and guardrails, and regulatory compliance. By integrating algorithmic governance, the organization can mitigate risks associated with AI while optimizing its benefits. This governance should be dynamic, evolving with changing AI capabilities and societal norms to ensure that the transformation is innovative, continuously responsible, and sustainable.

Conclusion

A well-considered AI transformation course, viewed through the “3P” lens can confer substantial advantages for organizations. By rigorously applying 3P AI Transformation Framework strategies, organizations can realize significantly enhanced operational effectiveness and efficiencies, business performance improvement, ROI and competitive advantages – all governed by robust recursive algorithmic development and management practices that safeguard against potential risks.

About the Authors

Aurélie Jean, PhD, computational scientist, entrepreneur and author. Aurélie Jean has close to 20 years of experience in computational science applied to a broad range of disciplines. After 11 years of academic research, Aurélie is now running two companies, including a deep tech AI startup in the early detection of breast cancer. She is the author of several bestseller non-fiction titles on algorithmic science, as well as a columnist on science and technology. Aurélie is teaching algorithmic science in executive education and is a research fellow at the Hult Business School and The Digital Economist. She is also an investor and a board member of several companies in the United States and in France.

Dr. Mark Esposito is a professor of economics and public policy with appointments at Hult Int’l Business School and Harvard University. He equally serves as an Adjunct Professor of Public Policy at Georgetown University’s McDonough School of Business. 

At Harvard, he serves as a social scientist with affiliations at Harvard Kennedy School’s Center for International Development; Harvard University’s Institute for Quantitative Social Science (IQSS); the Davis Center for Eurasian Studies and he is an incoming faculty affiliate of the Berkman Klein Center for Internet and Society at Harvard.

He co-founded the Machine Learning research firm, Nexus FrontierTech and the EdTech venture, The Circular Economy Alliance. He has equally co-founded The Chart ThinkTank and The AI Native Foundation. He was ranked by Thinkers50 in 2016 as one of the 30 rising business thinkers in the world and got shortlisted for the Breakthrough Award in 2019 and for the Strategy Award in 2023. He holds a doctoral degree from Ecole des Ponts Paris Tech and lives and works across Boston, Geneva, and Dubai.

Terence Tse is a globally recognized educator, author, and speaker. He is a Professor of Finance at Hult International Business School and co-founder of Nexus FrontierTech, an AI company. He is also a visiting professor at ESCP Business School and Cotrugli Business School. His latest co-authored book, The Great Remobilization: Strategies and Designs for a Smarter Global Future, was nominated for the 2023 Thinkers50 Strategy Award. Terence co-authored two Amazon bestsellers, The AI Republic and Understanding How the Future Unfolds. The DRIVE framework from the latter earned a nomination for the Thinkers50’s CK Prahalad Breakthrough Idea Award. Terence also authored Corporate Finance: The Basics, now in its second edition. He has appeared on numerous media platforms as well as ran workshops and consulted for global brands. He holds a doctoral degree from the Cambridge Judge Business School and has a background in investment banking and consulting.

Danny Goh is a serial entrepreneur and educator with a significant impact in the fields of innovation, sustainability, and digital transformation. He currently holds the position of Entrepreneurship Expert at the Saïd Business School, University of Oxford, and serves as a Senior Fellow at the Centre for Policy and Competitiveness at the École des Ponts Business School. Additionally, Danny lectures on entrepreneurship and digital transformation at various universities, including ESCP and Ecole des Ponts Business School, and provides his expertise as an advisor and judge for various technology start-ups and accelerators, including Microsoft Accelerator, Startupbootcamp IoT, and LBS Launchpad.

Danny is also a sought-after speaker, having presented at prominent conferences such as TEDx, UK High Commission events and BCGx. He co-authored the international best-seller on Amazon, The AI Republic: Building the Nexus Between Humans and Intelligent Automation, alongside Dr. Mark Esposito and Dr. Terence Tse. He is also a co-founder of the AI Native Foundation and The Chart Thinktank, a bipartisan non-profit organisation based in London. These organisations collaborate with global entities, including the United Nations and various governments, to advance the use of technology in the fourth industrial revolution.

As the founder and CEO of Nexus FrontierTech, Danny leads an AI research lab that leverages computer vision and NLP technologies to create digital transformation solutions for businesses across all sectors. The lab has successfully assisted Fortune’s top 100 enterprises like HSBC, UBS, MUFG and Toyota, as well as government bodies in the UK and Singapore, in integrating AI into their operations, thereby driving business growth and maintaining a competitive edge in an ever-evolving digital landscape.

The post Winning Strategies for the High-Stakes AI Arena: Unveiling an Innovative AI Research and Development Planning Framework and Matrix appeared first on The European Business Review.

Measuring your carbon emissions now

Beginning today will benefit you today

It’s never too early to start measuring your carbon emissions, and measuring these will benefit you from the get-go.

“We’ll start measuring and reducing our carbon emissions when we get bigger,” is a very common notion among companies with limited budget and resources. But the increased efficiency, awareness, risk mitigation, and future-proofing that results from measuring your carbon emissions as soon as possible are invaluable.

Budgets can be tight. Operational efficiency is therefore imperative. A key way to measure that is through your carbon emissions. Take a paper manufacturer, Papyrus Co. as an example. By measuring carbon emitted, the company was able to identify which areas of the factory were producing the most emissions, and introduce measures to reduce them. Heating Papyrus Co.’s facilities was contributing disproportionately to their carbon output. They therefore re-adjusted the default settings on boilers, which decreased the carbon emitted from heating by 8%.

Additionally, measuring carbon emissions builds awareness around the impact your company is having on our planet. There is a growing importance placed on reducing our carbon footprint, and a business’ climate responsibility and awareness is key. Having robust numbers to describe exactly what carbon you’re emitting can help make carbon emissions more tangible for your staff and customers by showing how your company is contributing to the overall health of the planet.

As the climate crisis becomes more severe, more regulatory compliance around carbon emissions is being enacted. By proactively measuring and managing your carbon footprint, you can stay ahead of evolving compliance requirements. This not only safeguards against potential legal repercussions but also positions the company as a responsible and compliant entity in an ever-changing regulatory landscape.

Request a demo of our decarbonization software today

Future-proof your business

Above all, measuring your carbon emissions now, will make it much easier to measure in the long run and hit decarbonization targets as you evolve. Decarbonization not only contributes to your sustainability goals and boosts your reputation, but also benefits your business’ bottom line.

By measuring your carbon emissions from the get-go, you’re able to instill best measuring practices, observe the evolution of your carbon emissions as you grow, and begin to roadmap your decarbonization goals immediately.

Instilling the best measuring practices

By starting carbon emission measurement early, you’ll be able to trial measurement practices and find what suits your business best. Of course, specialized decarbonization software solutions can help you and your team with some quick wins.

Carbon emissions evolution data

Your organization’s carbon emissions will naturally grow as your business grows. Measuring this evolution enables your business to accurately predict how further growth will impact your carbon emissions.

For example, Papyrus Co. increased their manufacturing capabilities in 2012 by doubling their facilities. They haven’t expanded since but are planning to in 2025. Thankfully, they kept a thorough record of what impact the expansion had in 2012, so they can predict carbon emissions and adopt measures accordingly and better plan for 2025.

Begin decarbonization from the start

Growing your business while decarbonizing is difficult, but simply measuring carbon emissions from the get-go is already taking steps towards decarbonization. By collecting the data and analyzing it, you will naturally spot areas for improvement that can easily be addressed.

How to measure your carbon emissions from the get-go

Determine your carbon emission metrics

For different businesses, different carbon emission metrics will be relevant. While Papyrus Co. focuses on energy use, a transport company might focus on fuel consumption, and a commercial real estate company on heating. Different metrics might also be relevant for different parts of your business too.

Make sure you’re collecting the right data.

Get your carbon emission data in one place

Once you’re collecting the right data, make sure it’s useful! It’s important to make measuring carbon emissions as simple as possible, so collecting all the data in one place methodically is essential. Additionally, this makes it easy to share with stakeholders if and when that’s necessary.

On the Zeigo Activate platform, users are able to log their Scope 1 and 2 emissions data, and view all the data on a dashboard which displays their company’s historical and ongoing data all in one place.

Create a system to collect Scope 3 emissions

Scope 3 emissions include those indirect greenhouse gas emissions that occur in your value chain but are outside of your company’s direct control. These emissions can result from the activities of entities that you interact with, such as suppliers, customers, and other stakeholders.

Given that these emissions are indirect, collecting data for these sources can be more difficult. To collect them effectively, creating systems which involve your partners is important. As these systems often take time to set up and fine-tune, getting started immediately can avoid bumps later down the line, when Scope 3 emissions are perhaps more significant in your business.

Set a carbon emissions baseline

Setting a baseline for your carbon emissions is key to providing a point you can measure against. This makes it easier to identify changes or trends in your emissions data, and is an essential step in decarbonization. Starting to measure emissions as soon as possible enables you to have a baseline sooner, so that you can measure against it.

Set a target

If you’re beginning your decarbonization journey at the very start of your business, you might want to set a not-so-ambitious target at the start. Nevertheless, getting into the habit of setting a target to go along with the measured baseline, and involving employees in carbon reduction, is very beneficial for later decarbonization too.

Having a target is key to drive decarbonization. A solid number provides a tangible metric that your company is working towards and gives you a goal for which to track progress.

Create a decarbonization roadmap

A target must be accompanied with a strategy to achieve it. That’s where creating a roadmap specific to your business comes in. The more data you have, the easier it will be to assess which actions will be most effective in reducing your carbon emissions. That’s why measuring your carbon emissions from the get-go is absolutely essential!

You don’t have to do this alone: Zeigo Activate helps you build your customized decarbonization roadmap. Based on your company’s baseline and selected target, the software helps you track and reduce your carbon emissions while providing manageable projects that you can begin right away.

There’s no better time than today! Click here to create your account and start tracking your emissions or click here to request a demo of Zeigo Activate!

The post Why & How to Measure Your Carbon Emissions Early appeared first on The European Business Review.

By Alan Thorogood and Stephanie L. Woerner

When undertaking a sizable project, a large organization might consider partnering with a small company in order to leverage their greater agility. However, such partnerships bring risks as well as benefits. How to get your head around the issues? What about a case study?

In a digital world, no organization can thrive alone, and partnerships with xTechs – nimble small companies – present large companies with powerful opportunities to innovate quickly. An xTech offers speed, agility, and lower cost for developing and implementing innovations, because xTechs don’t face large organizations’ processes, scale, and governance. In exchange, the large organization provides significant capital, revenue, and cash flow to the xTechs. This article will discuss what motivates large organizations to work with xTechs and three practices that help the partnerships succeed while managing the risks. We will use the Bendigo and Adelaide Bank case to illustrate our findings.

Motivations and challenges of partnerships with xTech

We started this research by asking senior executives from large organizations what they hoped to achieve by engaging with xTechs as part of the innovation process.¹ They identified faster speed to market and the internal adoption of an agile mindset as the desired outcomes.

At the same time, the executives were primarily concerned with regulatory, compliance, and brand risks that could arise from working with xTechs. Over half of the interviewees reported that the due diligence necessary to ensure compliance and protect the brand was extensive and expensive.

We then surveyed to understand what kinds of mechanisms large firms can use to increase their rate of innovation in their partnerships with xTechs. Our analysis identified three mechanisms associated with an increased rate of innovation:

• Create collaborative innovation teams with members from the large organization and the xTech who have decision rights. Building such teams requires a clear vision of the innovation process and desired outcome, solid and straightforward guardrails, and direct access to executives.
• Bake risk management into the innovation process when setting up the project and leverage existing processes to maintain alignment between the organization and the xTech.
• Partner with xTechs where there are existing relationships and trust. Typically, the project scope can increase when there is a stronger relationship.

Innovating with xTechs at Bendigo and Adelaide Bank

In a digital world, no organization can thrive alone, and partnerships with xTechs present large companies with powerful opportunities to innovate quickly.

Bendigo and Adelaide Bank (Bendigo Bank) is a midsize retail bank in Australia with a reputation for excellent customer service. For over 165 years, the bank has been providing customers with services and products to meet their financial goals. It has also been named Australia’s most trusted bank by Roy Morgan, an Australian market research company. Bendigo Bank’s total 2023 revenues were AU$1.9 billion, a 14 per cent increase over 2022 while investing in substantial digital transformation.

Up, a New Digital Banking App

In 2016, Bendigo Bank recognized it could serve more customers in the 18–35 age bracket, but it would need new technology. To develop a new banking app for these customers, the bank joined forces with Ferocia, an xTech that had previously designed and built the bank’s mobile banking app. Ferocia, a software engineering company with a staff of 27 people at the time, had skills in customer-centricity, product design, continuous delivery, and agility. Ferocia defined its mission as improving people’s financial well-being.

In 2018, Bendigo Bank began offering its new smartphone-only banking service, Up. Up was designed to encourage ongoing customer engagement and improved customer financial outcomes. The colorful and quirky interface stimulated interest and supported fast referrals and setup, enabling rapid customer acquisition by word of mouth. Ferocia and Bendigo Bank, using design principles, built gamification features into Up. ‘Savers’, for example, encouraged saving. Up customers could instantly create Saver accounts from their smartphones, each associated with a financial desire. Customers gave each Saver a name, an emoji, and a goal. Most of Up’s customers are under 35 and engage a lot. More than one-quarter of Up customers log in over 100 times per month, and the customer churn rate steadily sits in the single digits.

While the Up launch was successful, Bendigo Bank needed to address its legacy systems and, at the same time, continue innovating with Up and increase its customer share. In 2019, Bendigo Bank’s Managing Director, Marnie Baker, appointed Ryan Brosnahan as the bank’s chief transformation officer to lead Up and Bendigo’s digital transformation. Growth by merger and acquisition had left Bendigo Bank with eight core banking platforms, complex technology silos, and IT spaghetti. The goal of the digital transformation was to reduce costs and increase flexibility. Brosnahan noted, “We are in the midst of unwinding the labyrinth of technology we have and rebuilding it in a way that is digital-first, run in the cloud, API-enabled, and driven by microservices.“”

Innovation Teams with Allocated Decision Rights

Fast delivery was in Ferocia’s genes. However, the cadence and velocity of the Up innovation team – composed of both Bendigo Bank and Ferocia staff – differed from that of the core bank. Enabling the team to maintain this speed when working with the core bank required substantial delegations to the collaborative team. Partitioning the Up team from the bank development teams also helped the bank to focus its core teams on the transformation.

Bendigo Bank set the innovation team up for success by articulating a clear vision, setting up guardrails for project decision-making, and giving access to senior executives. Baker and Brosnahan made sure the vision for Up – helping 18–35-year-olds achieve financial well-being – was clear to its team by reinforcing the message. The Up team had the authority to make decisions about product features, launch dates, and requirements but within specific guardrails, such as using only a prebuilt set of APIs to link to the core banking engine and complying with cybersecurity. Finally, the Up team reported directly to Brosnahan, rather than indirectly through the bank’s product, distribution, technology, and operations teams. An advisory group was also established for Up that included CXOs to enable rapid feedback loops and fast decision-making.

Risk Management Baked into the Process

Brosnahan knew that managing a large-scale digital transformation at the same time as innovating a project like Up would increase the risks for both the transformation and Up. The Up team had to move fast and the bank had to deliver on the transformation. Further, the Up product had to conform to regulatory requirements for financial services and customer privacy regulations and protect Bendigo Bank’s reputation.

In Up’s initial setup and design stages, the bank managed credit and technology risks upfront. During the design stages for the Up home loan product and before product feature elaboration, management made credit risk management a central requirement for the new home loan to increase confidence in the assessment of Up loan applications.

Similarly, technology risk requirements were part of the initial setup for Up. The bank wanted to avoid creating another technology silo, so it required that Up operate on the core technology architecture under development as part of the bank’s digital transformation project. Limiting access to existing APIs and requiring requests for technological changes to operations to go through the Jira ticketing system were among the mechanisms the bank used to achieve this. Although the Up team initially found these constraints frustrating, it adapted quickly.

Temporary staffing assignments were another point of risk management for the bank. Baker approved assigning one product and risk person to the Up collaborative team, making those communities more comfortable with the Up team’s working methods. Cybersecurity and marketing people also took part in Up team sprints.

Project Scope Reflected in the Relationship’s Strength

Partnering with other organizations is an established practice at Bendigo Bank and it has produced decades-long relationships with numerous small businesses. The bank’s relationship with Ferocia began in 2012, when Ferocia developed the bank’s mobile banking app. Marnie Baker was Bendigo Bank’s chief customer officer at the time and championed Ferocia as a partner to the bank. Following that first successful engagement, the scope of the partnership grew.

When the bank set out to grow its under-35 market share, interpersonal trust, a belief that their strategies aligned, and substantial goodwill strengthened the partnership between Bendigo Bank and Ferocia. Shared confidence in the alignment between the companies allowed the scope to expand, leading first to a joint venture to develop Up and then to the bank’s eventual acquisition of Ferocia.

More than one-quarter of Up customers log in over 100 times per month, and the churn rate steadily sits in the single digits.

To build on the Up product offering, the bank engaged two other xTechs – Tiimely for home loan origination and Wise for international transactions, which were well known to Bendigo Bank. Tiimely, an xTech with a product that reduces the time to approve a mortgage, linked its online approval service to Up. After some tweaks, the results were so successful that Bendigo Bank’s core bank adopted Tiimely’s new services with its digital mortgage process for its BENexpress product. Approving mortgages quickly is a significant competitive benefit, because people buying a home compete with other buyers who may also be arranging a mortgage. The first to make a committed offering to the seller is at an advantage. In this way, Bendigo’s core mortgage offering became more attractive to home buyers. Wise, a UK xTech, helps Up offer market-leading experience and foreign exchange rates.

As of 2024, the bank continued partitioning its core business from the Up team. Even though Up shares its governance and management processes with Bendigo Bank, the Up team maintains its own culture and ways of working.

The relationship between Bendigo and Ferocia began a decade before Up launched a mortgage offering. The scope grew as trust grew and the partners got to know each other – again a robust mechanism that the survey results show works for others.

Leapfrogging Competitors

Bendigo Bank reports that it has a fraction of the investment budgets of the large banks in Australia. But spurred by high customer advocacy (i.e., customer brand promotion), with a market leading NPS, and following on its ranking as Australia’s Most Trusted Bank, its customers expect a superior experience and proposition. The most recent results³ show that digital mortgages have grown from 8.9 per cent of settlements a year earlier to 16.3 per cent. The digital deposits in Up ($1.7bn) surpassed the main bank’s digital deposits ($0.9bn). The bank does things differently from its competitors by realizing and sustaining high customer satisfaction and advocacy levels.

The bank will continue to partner with xTechs to accelerate customer and employee experience improvements and increase execution speed and adaptability while improving its risk posture. The next stage for Bendigo Bank is to leverage the success of its innovations further with xTechs. Bendigo is using the shared capabilities it has developed with xTech partners such as Ferocia and Tiimely to innovate quickly, safely, and at scale to help accelerate the digital transformation of the broader Bendigo Bank proposition.

Partnering to Accelerate Transformation

Executives want xTech partnerships to deliver innovation quickly. So, be fast by giving the xTech collaboration team authority to make decisions, access to executives, and clear guard rails. And manage the downside by identifying and baking key mitigation into the innovation process and relationship and include the xTechs and your risk professionals in the management framework. Finally, trust takes time, so don’t rush to engage in projects with a large scope; instead, focus first on smaller-scale projects that can be delivered quickly. Trust will grow with success.

About the Authors

Alan Thorogood, PhD, is a researcher at MIT CISR.  Based in Sydney, Australia, he works with sponsor organizations in Asia-Pacific. His research draws on his background in financial services, the public sector, and multinational consulting companies. He is also a Senior Visiting Fellow at UNSW, where he teaches and supervises research.

Stephanie L. Woerner, PhD, is a Principal Research Scientist at the MIT Sloan School of Management and Director of MIT CISR. She is a renowned researcher and speaker, and coauthor of Future Ready: The Four Pathways to Capturing Digital Value and What’s Your Digital Business Model? Six Questions to Help You Build the Next-Generation Enterprise, both published by Harvard Business Review Press. Stephanie studies how companies use technology and data to create more effective business models as well as how they manage the associated organisational change and governance and strategy implications. Stephanie’s research has appeared in MIT Sloan Management Review, Harvard Business Review, CNBC, Forbes, Chief Executive, and CIO.

References

1. This research is based on interviews and surveys from 2021–3. The Bendigo Bank case study was written in 2023 (also reported in Kwong, C., Van Toorn, C., & Thorogood, A. (2022, July). Banks responding to FinTechs in the Digital Era. In Pacific Asia Conference on Information Systems (PACIS)). The mechanisms identified in the survey analysis were significant in regression with innovation as the dependent variable. Innovation was measured as the percentage of revenues from products and services introduced in the last three years.

2. The longer the arrow, the more influential the motivation as drawn from qualitative analysis of interviews with senior executives in financial services who work extensively with fintechs. The analysis used a five-point Likert scale and a structured Delphi technique to verify the findings.

3. See Results Presentation, February 19, 2024.

The post Unlocking innovation with xTech partners appeared first on The European Business Review.

By Javier Cabetas, Iván Fernández-Muñoz, Pedro Cesar Martinez-Moran, and Fernando Diez

In an increasingly complex and globalised business world, corporate governance can guide companies to sustainable success if well implemented. This article will explore how startups can build and maintain a governance model that balances sustainable growth and business agility, attaining success in today’s market.

Introduction

Corporate governance defined in the growth phase of a startup can drastically influence its future, acting as a catalyst for its success or failure. This article explores governance practices and perspectives of investors and CEOs to build models that foster sustainable growth and business agility in startups. Furthermore, it analyses the balance between the expectations of investors and CEOs, who, although united by the desire to succeed, have divergent visions and goals, and thus maintain an agency relationship (Fama, 1980; Fama & Jensen, 1983).

Corporate governance plays a key role in strengthening the ability of companies to access global finance, providing credibility and ensuring fair and responsible management of capital.

While united by their desire for business success, these groups often have divergent visions and objectives. Investors seek security in their investments, aspiring to clarity and predictability in company strategies and direction, and prefer transparent and accountable corporate governance models that foster sustainable growth. On the other hand, CEOs face the challenge of navigating a complex operating environment, balancing the demands of investors with the need to maintain flexibility, foster innovation and, at times, make decisions in an agile manner.

In an increasingly complex and globalised business world, corporate governance emerges as the beacon that can guide companies to sustainable success if implemented in the right way. Good governance practices are essential in a world where transparency, accountability and sustainability play a critical role.

This article, through a discussion of different governance techniques and perspectives of investors and CEOs, will seek to shed light on how Startups can build and maintain a governance model that promotes synergy between sustainable growth and business agility, which is essential for the success of any Startup in today’s market.

What is Corporate Governance?

Definitions vary widely across regions, but corporate governance can be summarised as the relationship between organisations, their management teams, their board of directors, their shareholders and their stakeholders. Or, more specifically, it is the process by which organisations assure their investors of the presence of a proper and supervised management team and thus the appropriate, responsible and cost-effective allocation of their resources (Gregory, H. J., & Simms, M. E., 1999). Ultimately, it is crucial because it sets the framework for all business activities from strategy to risk management and cybersecurity (Diligent Corporation, n.d.).

Although there are different models of corporate governance, they all follow the same principles: ensuring fair and considerate dealings with stakeholders surrounding the organisation, adding transparency on financial performance, potential conflicts of interest and external risk management, overseeing the management team acting in the interest of the company and its investors, and communicating issues of importance to the organisation’s shareholders (OECD, 2023).

Effective governance reduces conflicts of interest between actors with divergent objectives, improving cohesion, efficiency in decision-making and return on investment.

In startups, effective corporate governance is crucial to increase trust between investors and financial institutions, improve decision-making and provide the organisation with a solid structure, mitigating risks and conflicts of interest. Good corporate governance clarifies the rights and obligations of founders, shareholders and the board of directors, promoting structured and consistent management practices, essential for sustained growth and success (ASOMIF Ecuador, 2021).

Importance of Corporate Governance

Corporate governance plays a key role in strengthening the ability of companies to access global finance, providing credibility and ensuring fair and responsible management of capital. It also fosters transparency and accountability in strategic decisions by providing an external check and balance that monitors the performance and actions of management. At the same time, it contributes to improving organisational resilience by establishing a second line of control for social, economic and environmental risks, enabling the company to maintain a responsible relationship with institutions and comply with local regulations (OECD, 2023).

In the startup context, corporate governance offers a series of benefits specific to its growth context (ASOMIF Ecuador, 2021):

• Attracting capital and investor confidence

Good corporate governance practices are a key differentiator for startups to access external funding. A robust governance system reflects effective and accountable management, which increases investor confidence by showing that capital will be managed efficiently and transparently. This makes it easier to raise the resources needed to drive the company’s growth.

• Agile strategic decision-making

Strong corporate governance in startups not only adds value through diverse and expert perspectives but also drives agile and well-informed decisions, which are essential in a fast-growing environment. A balanced board facilitates continuous adaptation to market changes, ensuring that the startup maintains flexibility and strategic focus, which is crucial to its long-term success.

• Alignment between founders, managers and investors

In startups, where founders play a central role, good corporate governance is essential to establish policies that align the interests of management, investors and other stakeholders. Based on agency theory (Jensen and Meckling, 1976), effective governance reduces conflicts of interest between actors with divergent objectives, improving cohesion, efficiency in decision-making and return on investment.

• Risk mitigation in an uncertain environment

Startups, especially in their early stages of growth, are exposed to a range of financial, operational and strategic risks. A sound corporate governance framework allows them to better anticipate and manage these risks, helping to protect reputation and ensure regulatory compliance. This not only reinforces stability and transparency but is also crucial to sustaining success as the startup scales.

Implementing sound governance practices offers long-term benefits, such as preparing the company for a possible IPO, improving sustainability and increasing expectations for future growth (Harvard CorpGov, 2021). It also minimises agency costs by reducing conflicts among stakeholders. Effective board oversight ensures that critical decisions are always made in the best interests of the company.

Challenges in Implementing Corporate Governance

Implementing good corporate governance in a startup entails significant challenges, mainly due to its resource constraints, size and urgent growth needs. Here are the key challenges:

• We don’t have time for those things

Time is a tremendously limited resource for startups (Al-Alawi et al., 2023), which, unsurprisingly, tend to prioritise investment in product design and lead generation over the implementation of more formal governance structures. However, the most common stressors associated with business failure in these firms are directly linked to areas where control mechanisms can provide crucial support, such as operational management, working capital control, understanding the competitive environment and preventing over-optimism in growth expectations.

While it is true that the focus of time varies greatly depending on the stage of evolution of the Startup, both in the pure ideation and development phase and in the scalability phases, a correct governance model can fulfil critical organisational functions for the sustainability of the business, whether in the search for investors, identification of possible collaborations or definition of the pool of talent needed to run the project.

• We need to focus on innovating! This structure will make us slow

Once the need to implement corporate governance mechanisms is understood, there is a logical fear that they will slow down those behaviours that are understood to be a priority for business success, such as innovation, commercialisation of ideas, continuous product improvement, etc. (Chokheli, 2023).

While larger boards can slow down decision-making, good governance practices, such as innovation-specific committees, can expand the pool of knowledge and perspectives, thus improving the innovation capacity of the startup (Matoug et al., 2024; Baum et al., 2022).

Several studies have shown that the diversity of governance teams, both at the functional (knowledge), occupational (professional) and relational (presence in governance mechanisms of other organisations) levels, positively fosters the innovative capacity of the organisation (Kim & Kim, 2015).

• Who can be part of these structures

When small and medium-sized companies create governance structures, they tend to move towards less formal structures than a management committee, tending towards advisory boards (Ding et al., 2013; Schiehll et al., 2018) and family boards (Arzubiaga et al., 2018; Gnan et al., 2015).

However, the inclusion of professional directors can compensate for the lack of experience of the founders, bringing crucial human and social value (Barroso-Castro et al., 2022). This balanced approach can help the startup make more informed and responsible decisions. The inclusion of both internal and external advisors is vital. External advisors can mitigate self-interested behaviour and improve control over the management team.

• How should I compensate them

The remuneration of board members is critical to fostering the attraction of the best possible talent as indicated by managerial talent theory (Meyers, M. C. et al. 2014), as well as to minimise divergences between shareholders and the management team (Elnahass et al. 2022). Some authors have shown that share-based payment can affect risk aversion (Martinez-Moran et al., 2020) and thus the innovative capacity of the startup in its initial phase (Hoskisson et al., 2002).

Implementing effective corporate governance in a startup involves balancing innovation with structures that support growth and mitigate risks. Good governance practices offer advantages by incorporating diverse perspectives and improving operational and financial management, strengthening the internal structure and preparing the startup to face business challenges in a sustainable manner.

Corporate Governance Models for Startups: Choosing the Right Path to Growth

Corporate governance is critical to ensure the sustainability and growth of any organisation, especially for startups, which face unique challenges as they evolve. Governance models can be grouped into two broad approaches according to their orientation: the shareholder-centric model and the stakeholder-centric model. Each of these approaches offers advantages and disadvantages that startups should consider when designing their governance structure.

On the one hand, the shareholder-oriented model focuses on maximising returns for investors, who are considered the true owners of the company. This approach seeks to increase wealth and financial performance by putting investors at the centre of strategic decisions. On the other hand, the stakeholder-oriented model expands the horizon of governance by including all stakeholders related to the organisation, such as employees, customers, suppliers and society at large. This broader approach recognises that financial success is not the only objective, but that the social and ethical impacts of decisions must also be considered (Neagoe, A. L., 2022).

However, in choosing an appropriate governance model, startups need to take into account their particular context. There are four main models that stand out in this type of start-up, each with its own advantages and disadvantages:

1. Founder at the centre

This model places the founder as the central figure in strategic decision-making. The main advantage is agility and clarity of vision, as decisions directly reflect the founder’s personal objectives. However, the risk lies in the lack of oversight, which can lead to biased decisions or conflicts of interest if the founder prioritises his or her own interests over those of the company (Fan, 2020; Board Foundation, 2023).

2. Professional CEO

In this case, day-to-day management rests with an external CEO, with extensive experience and sector-specific knowledge. This can provide an objective and less biased view, which is crucial for sustainable growth. Still, it can create tensions between the CEO and the founder, as well as representing a significant investment for the company (Board Foundation, 2023; Harvard Business Review, 2021).

3. Balanced board

This model combines the founder’s vision with the input of independent directors. Diversity of opinion improves the quality of decisions by integrating broader and more informed views. However, it can slow down processes due to the need to reach consensus, as well as increase the risk of conflict among stakeholders (Harvard Business Review, 2021; Pitchbook, 2021).

4. Active investors

Here, investors play a key role in governance, providing not only capital but also expertise and valuable contacts. However, this entails a loss of control on the part of the founder, who must align with the interests of investors and may be limited in his or her decision-making capacity (Pitchbook, 2021; Board Foundation, 2023).

The selection of the most appropriate model depends on the specific momentum of the start-up. Founders should carefully evaluate the advantages and disadvantages of each option and adapt their governance structure to ensure solid and sustainable long-term growth. In addition, when including third parties, it is crucial to select the right partners, both in terms of experience and cultural affinity. Thus, governance becomes a key tool for startups not only to survive but to thrive in highly competitive markets.

Conclusions and Recommendations

The implementation of governance mechanisms in Startups is shown to be a crucial process for the correct development and evolution of the organisation, however, its design and implementation must be strategically opportune from several perspectives:

• From a temporal point of view, it is essential to integrate governance mechanisms as soon as feasible. Even if the initial focus is on product development and commercialisation, governance should be on the radar from the beginning. Considering governance as a long-term investment will help to avoid management problems as the company scales up.
• To maintain the organisation’s momentum, the Founder/CEO must be alert to those processes where more formal governance models may slow down decision-making or stifle innovation. To avoid this, it is key to encourage diversity on the board and in governance mechanisms, making sure to include people with different functional, occupational and relational perspectives.
• The Founder/CEO should implement a governance structure with an independent advisory capacity. In addition, it is advisable to establish internal and external audits to mitigate risks and improve transparency, as well as specialised committees to oversee critical areas of the business through clear reporting systems. These actions should be implemented in an orderly and structured manner as the company grows.
• Board compensation should be aligned with organisational strategy. In the early stages, share-based payment may stifle innovation by increasing risk aversion, but in mature stages, it will encourage risk management and strategic sustainability. It is crucial to consider which method will best incentivise the long-term growth and stability of the organisation.
• The Founder/CEO should carefully consider the use of equity compensation, as it may not be the most appropriate model at all stages of development. If the company is in an ideation or aggressive growth phase, this method may increase the risk aversion of the management team and limit the ability to innovate. In these cases, it would be more appropriate to opt for compensation methods that maintain the focus on innovation and growth, without reducing risk tolerance.

The Founder/CEO should seek an appropriate balance between internal and external advisors get the best from both perspectives. The inclusion of external advisors can bring fresh and challenging visions that introduce best practices from the market, however, it is equally important to have internal advisors who understand the day-to-day reality of the organisation, which will allow for a proper balance in decision making and better alignment with business objectives.

The correct integration of corporate governance practices in the initial stages of start-ups will allow their founders to balance the dynamism and enthusiasm of this type of organisation with the responsible action required to ensure sustainable growth and competitiveness with their environment.

About the Authors

Javier Cabetas is a strategic consultant. He specialises in optimising the performance of organisations by focusing on their people and operating models. Over the last few years, Javier has helped several international clients transform their people and talent management processes, redefining their structures, processes and capabilities. Javier holds a degree in Organisational Psychology and a Masters in Human Resources Management and Business Analytics.

Iván Fernández Muñoz is a consultant based in Madrid, specialising in Board advisory and Corporate Governance projects for leading national and international companies across sectors. In addition to his experience, he holds a degree in Organizational Psychology and a Master’s Degree in Human Resources and Business Analytics from Universidad Pontificia Comillas (ICADE).

Dr. Pedro Cesar Martínez Moran is the Director of the Master’s in Talent Management at Advantere School of Management. He teaches at Universidad Pontificia Comillas and is also a member of academic research groups. In addition to his academic work, he has held various roles as a senior executive and consultant. Currently, he serves on the executive board of the Global Future of Work Foundation (www.globalfutureofwork.com).

Fernando Díez has built his career at the University of Deusto, holding a PhD in Education, an MBA-Executive (DBS), and degrees in Psychology and Pedagogy. A certified professor and lead researcher, he has directed collaborative projects and published high-impact articles. He also specializes in Human Resources Management and innovation leadership.

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This also has a profound impact on how we ideate and innovate. The rise of AI, especially Generative AI (GenAI) has added to this complexity. With GenAI being the first technology that is now capable of creating and approximating more human-like ideas and combining concepts in novel ways, it is becoming more difficult to discern where human creativity begins and the influence of AI ends.

GenAI, however, is not here to replace human ingenuity or our unique problem-solving abilities. Instead, it prompts a bigger question: How is AI reshaping corporate innovation? What are the opportunities and drawbacks of this technology, and how can organizations position themselves to embrace an AI-driven future?

Seismic Shifts in Corporate Innovation

Innovation has always been a key discipline for organizations to stay relevant in a fast-changing world. While AI has been around for some time, the emergence of large language models (LLMs) like ChatGPT, have sparked concern amongst many businesses, with fears of industry disruption and job losses. While these concerns are partly justified, in the context of corporate innovation, GenAI simply represents another shift in a long history of change.

In the early 20^th century, up until the 1980s, corporate innovation was primarily seen as a form of diversification, rather than as a separate strategic priority. Many executives relied on their personal experiences and intuition to drive company-wide innovation efforts. Towards the late 20^th century, innovation became more integrated into the overarching business strategy, by companies establishing dedicated teams and departments leading corporate innovation efforts, formalizing the approach.

The 21^st century saw a shift from closed innovation to open innovation models, welcoming the input of external parties and assistance through external ideas and technologies. Now, with GenAI, another shift is underway, which if harnessed effectively, can drive businesses to new heights.

AI as a Catalyst for Innovation

The possibilities of AI and GenAI to revolutionize traditional R&D processes as well as corporate innovation, are endless. If used in conjunction with an existing innovation management program, AI and GenAI can transform the innovation journey by accelerating and improving workflows, automating routine tasks, improving decision-making and act as co-pilot for coming up and validating new ideas. At rready, we’ve integrated AI into our innovation management software to help teams move more efficiently from ideation to implementation.

1. Identifying Problems

The first step in innovation is problem identification. Here, GenAI helps innovators as part of the brainstorming process by scanning through data sets and identifying certain trends in these data sets or recognizing possible market opportunities and gaps by analysing competitor activity. Unlike traditional machine learnings models, LLMs can understand and predict human behaviour in a way that is far more advanced than any other previous learning models, leading to more sophisticated outcomes, even as early as the problem identification process.

At rready, the combination of GenAI, our API-first innovation platform and proprietary company data unlocks new possibilities to uncover relevant problems and opportunities. We believe this will set a new standard for corporate innovation and fuel the disruption of innovation discipline as we know it.

Another useful way in which to incorporate GenAI in the innovation process, is by enabling innovators to discover ideas or solutions other innovators in their organization have come up with. Our rready platform features an advanced search function, which allows innovators to discover ideas from others, based on the similarities between ideas. This streamlines the innovation process, helping users avoid duplicating efforts on problems where solutions might already be in the works. We are also currently investigating how AI agents can help to do research and add up-to-date information on an idea level.

2. Creating and Enriching Ideas

Once an idea has been established, it is the task of the innovator to flesh it out. AI agents can analyse large data sets from the web or from internal proprietary company data sources much faster than humans and provide insights that enrich ideas with evidence-based reasoning. From customer preferences or user behaviour to market trends, or scientific research, GenAI helps innovators to synthesize complex information to support or refine their ideas further.

The ability of certain AI integrations to work cross-functionally also offers an opportunity, specifically when using innovation management platforms. The rready platform has AI-powered Dynamic Fields that react with AI integrations to help innovators not only create ideas or descriptions for these ideas, but also enrich these further through co-pilot support.

3. Rapid Prototyping and Simulation

Once an idea is validated, prototyping is essential. By creating a preliminary model, innovators can test, identify potential flaws and gather valuable feedback to iterate their solution. AI can speed up this traditionally time-intensive process, reducing costs and resources.

In product design for example, Generative Design (GD) uses AI-driven software to generate multiple solutions based on a given set of constraints, leading to faster and more efficient problem-solving. To create prototypes and simulations, the rready platform offers the use of AI connectors that facilitate an integration of AI into various tools and systems for challenges extending beyond the platform’s capabilities.

4. Implementation and Commercialisation

After developing a solution, GenAI can assist with market analysis and targeting strategies. By utilizing predictive analytics for example, companies can analyse historical and current trends to predict how a product or service would perform in the market. This allows organizations to adjust their marketing strategies in real-time, to allocate and use resources more efficiently.

5. Providing Oversight and Ensuring Continuous Improvement

AI plays a significant role in tracking and evaluating performance post-launch. For program- and innovation leads, AI helps maintain oversight and optimize programs by tracking key metrics such as KPIs or project ROI. For this, the rready platform offers AI-powered graph architecture to ensure a comprehensive understanding of relationships among ideas, people, and data.

The future of corporate innovation lies in the hands of top-level decision-makers in organizations and how they choose to integrate it. While incorporating AI into the innovation process can be daunting, the benefits are manyfold. Combining GenAI with innovation management tools, offers a comprehensive solution for streamlining and levelling up innovation across a company. This approach augments human creativity, while addressing the shortcomings of traditional human-driven processes, leading to improved product and service offerings.

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The AI of the beholder: Managers need to examine where AI can improve workflow processes.

Generative AI’s impact on productivity could add trillions of dollars in value to the global economy, according to consultants McKinsey.

Generative AI can learn, reason, make decisions, and automate many creative and intellectual tasks – providing the potential to supercharge productivity in the workplace.

As a starting point, companies need to identify where AI can help. This involves tasks within specific company functions, so the process needs to begin from the bottom up, rather than top down.

Every manager and decision-maker should analyse their team’s workflow to identify tasks that AI can help with. Tasks that AI can do alone should be automated, although this is a nascent area due to errors, so supervision is still often required – but is likely to expand rapidly over the coming years.

A step up from this, there are tasks where managers can learn to work seamlessly with AI, integrating it into their workflow and passing work back and forth (termed ‘centaur tasks’).

Then there are the tasks that can be delegated under tight oversight, including checking for errors and giving feedback. Both centaur and delegated tasks are likely to expand as AI becomes more flexible and can tackle more parts of the workflow.

Beyond this remain the ‘just me’ tasks that employees either don’t want to give up, where the AI is not capable, or it is too hard to get the AI to do a good job.

From the company’s perspective, managers then need to be empowered, resourced, and enabled in their use of generative AI. Firms need to be more proactive in this, rather than defensive – those that wait and see will lose out to competitors that jump in.

This includes establishing guardrails, best practices, and a sandbox for experimentation. Companies should plan for bespoke Large Language Models (LLMs) – machine-learning AI that uses neural networks trained through the input of data. For the best results the LLM should be tailored to the firm’s field, as has been done with LegalBERT, BioGPT and others, and this may require significant investment in IT and data acquisition.

LLMs can respond to questions, summarise, edit, translate, program, assign labels, extract facts, infer relationships, and reason about texts using learned knowledge. The larger and deeper LLMs enable the emergence of greater understanding and a higher level of response – in a similar way to humans as they accumulate knowledge growing up.

In addition to saving managers’ time and enhancing the way they do their job, AI can identify savings and streamline processes and procedures, as well as monitor performance and personnel.

More specifically, managers are likely to find that the help available from generative AI falls into one of the following six categories:

1. Helping with research 

AI can be used in most areas of research and analysis. For example, it can be used to look up and summarise patents, and search for potential customers or investors.

This can be extended to the provision of cost estimates to develop and produce new products, as well as the risks involved in their commercialisation. AI can also carry out research and analysis on competitors or potential acquisitions, including market positioning, customer satisfaction, service offerings and risk.

Based on this, it can go on to analyse and compare the positioning of companies in relation to current market trends and demands, and how they may be able to enhance customer satisfaction and optimise service offerings.

Managers partnering with the AI need to watch out for accuracy and originality of responses, or potential bias that may have been written into its system or through the information it digests.

2. Brainstorming ideas 

AI is very good at idea generation, including in the areas of planning and strategy, which can be hugely beneficial.

It can be creative, coming up with ideas for product logos, names and design. It can be employed in artistic design as well as text generation, helping with the donkey work in the process.

Concerns over low quality in this area are fast receding, with analysis now unable to distinguish human and AI created content – indeed, there is growing evidence to suggest AI creativity is of a high quality. The worry about losing the human touch appears to be fast receding, but this is a concern that users should always be aware of.

3. Supporting content creation 

Once ideas have been settled on, AI can adapt them to fit with brand identity or other requirements and can help develop marketing content.

Human feedback can be provided to the AI to help re-work particular aspects of this process. Managers must be wary of the possibility that AI may share sensitive or confidential information and adjust for this.

They are excellent in creating customer content, including writing about specific customer needs, and this applies to every industry.

4. Writing and understanding computer code 

AI can program in whichever language is required given the right LLM, which can enhance operational flexibility and cuts time and resources from programming tasks.

Online it can interact seamlessly with other computers and AI, as well as being able to conduct full analysis of websites and their performance, along with the quality and extent of their SEO, security and visitor interaction.

5. Automating interactions with customers 

Among the more immediate applications of generative AI automation is an improvement in the quality of automated interactions with customers – which should provide enhanced customer service, replacing clunky old chatbots.

With AI’s ability to ingest all the information relevant to that company and customer, the field should see rapid improvement.

However, proprietary AI may be required here, with considerable security to ensure customer safety. But it should provide more meaningful, friendly and more useful interactions with consumers, across a wide range of sectors.

6. Translating languages 

AI is now able to translate and interpret in whichever language is required to a high degree of accuracy and fluency.

Machine translation is a rapidly developing field, with many apps and websites available, such as Google Translate. There is also Neural Machine Translation (NMT), which sees a machine translation service pairing with an artificial neural network to provide better outcomes than standard translations.

For companies exporting or looking into new international markets this could be a valuable service and any translation can be cross-referenced with another translation app.

Looking to the future, possible developments include open source LLMs, as well as highly personalised AI put together for the needs of individual managers.

Moreover, AI enables everyone to be a manager and hugely increases productivity, which could have huge implications for organisational structure and strategy in the longer term.

Higher productivity could lead to lay-offs or re-direction of work to new areas. Organisational structure could change to one where individuals predominantly use AI independently – a leveller that may alter the dichotomy of management and workers, changing the traditional hierarchical nature of companies. Or the structure may involve a central AI monitoring every move being made, making control more centralised than ever.

AI itself will no doubt eventually have a suggestion of its own.

Learn more about WBS Digital Innovation & Entrepreneurship Executive Education courses here: https://www.wbs.ac.uk/courses/executive-education/?studytheme=Digital+Innovation+and+Entrepreneurship

About the Author

Ram Gopal is the Information Systems Society’s Distinguished Fellow and a Professor of Information Systems and Management at Warwick Business School. Learn more about WBS’ Digital Innovation & Entrepreneurship Executive Education courses here: Executive Education | Courses | Warwick Business School (wbs.ac.uk)

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There are very few early-stage European tech firms that can afford to ignore the question of profitability. 

Additionally, in recent years investors across the European venture capital ecosystem have found themselves increasingly capital-constrained – whether due to the challenging market conditions, lack of (DPI Distributed to Paid-In Capital), and a difficult fundraising environment.   

As such, investors are starting to pay close attention to profitability earlier in the startup growth lifecycle – which means founders need to do the same.  

The changing nature of valuations  

In the past, tech company valuations were largely pegged to their growth rates and unit economics, hence growth took priority over profitability.   

If a startup could show product/market fit and a repeatable sales model, it didn’t matter if they were losing money, as long as they were profitable on a unit economics basis. In many cases, the firms were simply channelling the profits back into aggressive customer acquisition and expansion.  

But in the current, capital constrained market, investors cannot afford to sacrifice profitability indefinitely for growth. From Series B onwards, they are now looking for evidence that a startup has a visible pathway to achieving profitability.   

If founders can’t demonstrate a credible plan, they could face an uphill battle to hold onto their valuations and livelihood. This is one of the major reasons why the number of down rounds doubled from 2022 to 2023. Founders have been trying everything in their power to conserve cash and cut costs on the pathway towards profitability, but in many recent cases, they’ve been left with no choice but to accept a depressed valuation, down round, or at best, flat round.   

The funding gap is growing 

Similarly, the time between Series A and B fundraises – typically classified as the gap between ‘early stage’ funding and the start of the ‘growth stage’ funding rounds – is now 28 months, the longest it has been for over a decade.   

Almost two-thirds of US startups that closed their Series A in 2020-21 are yet to raise a subsequent round. Many will never do so. In the UK, more than one-third of startups fail between Series A and B. 

First-time founders frequently underestimate the journey to closing a Series B, simply because their Series A experience had been comparatively quick and straightforward. However, as the gap widens, the risk increases that they may exhaust their runway before proving that near-to-mid-term profitability is achievable. 

Addressing the profitability question from the get-go 

Despite paying closer attention to profitability, investors understand that different sectors face radically different challenges to get there. There’s a world of difference between an eCommerce company, a B2B Enterprise SaaS company, and a chipmaking startup, for example, in terms of the time to profitability and the level of investment required to get there.   

Likewise, investors are still prepared to take risks on more complex, longer-term business cases that promise the possibility of much greater returns should the startup become successful.   

Regardless of their industry or specialism, however, founders are likely to face the same sorts of questions about future profitability.   

Series B investors want to understand the go-to-market plan, customer acquisition strategy, projected revenues, per-customer unit economics, and the founder’s overall plan for revenue aggregation and growth. And with each subsequent funding round, investors will want more evidence that break-even profitability is on the horizon. 

Forward-thinking founders should prioritise profitability from the earliest stages of their growth journey. Although it may not play a role in early-stage investor conversations, the market always defers to the downstream investors, their expectations, and current market conditions.   

Extension rounds can help founders overcome the funding gap  

Series A extension rounds allow a startup to raise a small round from its existing and specialised investors based on the same terms of the Series A to extend its runway and allow more preparation time for a proper growth round.  

Extension rounds have historically been an underutilised investment tool. But for the thousands of startups under pressure to demonstrate their pathway to profitability before they seek Series B funding, it can be an attractive option for any founder who still enjoys the belief and support of their early-stage investors. 

That said, it can be difficult for founders to secure the full amount they need from their existing investors, which is why we’re increasingly seeing VCs looking to specifically target extension rounds and work in partnership with existing investors to plug the capital shortfall.   

The winning combination 

From a founder perspective, it might feel as though investor expectations for a return on their capital are becoming unrealistic. Achieving rapid, outsized growth is one thing; achieving profitably is another altogether. 

Remember – Series B investors are not necessarily focused on immediate profitability, but on clear evidence that a startup is on the right path and actively addressing their industry challenge. Once they’re convinced, these investors will leverage their extensive experience to help the company realise its full potential.

About the Author  

With over 40 years of global C-level experience in tech, Ivan Nikkhoo is a seasoned investor, entrepreneur, advisor, board member, operator and educator. As the Founder and Managing Partner of Navigate Ventures, he leads a B2B Enterprise SaaS fund focused on entrepreneurs outside Silicon Valley between series A and B Growth rounds (A Extension Rounds).

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By Jenny Fernandez

Leaders often prioritise immediate results, but visionary leadership requires balancing short-term gains with long-term strategy. This involves embracing flexibility, empowering teams, and fostering innovation. By shifting focus from daily operations to strategic planning and external trends, leaders can drive both immediate success and sustainable growth in a rapidly changing business landscape.

When Sarah, a former client, was promoted to VP of Product Innovation at a cyber security firm, she embarked on a mission to prove herself. With a well-crafted 30-60-90-day onboarding transition plan, she aimed to quickly familiarise herself with her new team and make a tangible impact on the group’s strategy and direction. She expressed her desire to revamp the organisation’s projects, enhance the group’s capabilities, and shift their focus towards tangible results. Sarah wanted to deliver visible results before year-end, solidifying her reputation as an effective leader who can make an impact and turn around the trajectory of the business.

While some executives in the C-Suite embraced her approach, others believed the company required more than incremental change. They recognised that the rapid advancements in AI and technology demanded a proactive approach – uncovering new opportunities for growth, exploring untapped vertical channels, and identifying ways to “leap-frog” ahead of the competition. They desired transformational change.

“Management is doing things right; leadership is doing the right things,” said Peter Drucker, commonly known as the “Father of Management.” As a leader, it is critical to strike a balance between short-term results and long-term success. However, many organisations and work cultures often prioritise and reward immediate outcomes – the “what have you done for me lately” mentality. Consistently generating results helps you remain top of mind and on the shortlist for recognition, opportunities, and promotions.

Visionary leaders navigate uncertainty, think strategically, and connect the dots for transformative growth. They inspire others to embark on a change journey toward long-term success.

Yet, true visionary leadership entails making trade-offs between short-term gains and long-term growth. Visionary leaders navigate uncertainty, think strategically, and connect the dots for transformative growth. They inspire others to embark on a change journey toward long-term success. You must shift your mindset from the “What is?” to “What if?”1 You are able to envision possibilities that others overlook – a future characterised by new strategies and corporate culture that seamlessly integrates business trends, innovation, and emerging capabilities, ensuring the organisation thrives amid an evolving business landscape.

Becoming a visionary leader can serve as the catalyst that helps you stand out and secure your long-term success. However, we know that leaders don’t often have the luxury of time to achieve their vision, as highlighted by a Korn Ferry Study2 revealing that higher-level positions tend to have shorter tenures. Thus, embracing visionary leadership becomes a strategic bet on one’s career and future accomplishments.

If you find yourself struggling to embody this leadership style, it is crucial first to reflect and understand the underlying reasons. Only then can you actively work on developing this invaluable skill set.

Why Being Visionary Doesn’t Come Easy

Before you can improve, it’s critical to reflect on why being a visionary doesn’t come naturally to you. Here are some common reasons we’ve seen among leaders we’ve worked with.

1. Do you have a control-oriented style of leadership?

Many individuals who are driven by immediate results often exhibit a control-oriented3 style of leadership. They prefer to maintain a firm grip on every aspect of their projects and teams. This approach can hinder them from establishing a clear vision by stifling creativity and innovation. This is especially detrimental in fast-moving growth industries where technology, AI and data rapidly evolve.

In Sarah’s case, she had been asked to lead a new function. She needed to transition into a learning mode4, recognising that her role no longer required specialised expertise but, instead, demanded setting the vision for growth. To do this, you need to empower your team, delegate authority, and place trust in others to execute your vision. If you struggle to let go of control, you may encounter challenges in achieving this mindset.

2. Are you unable to scale your leadership?

If you discover that you are personally involved in every decision, insist on approving every project, and demand that your team meticulously present and defend their perspectives for even the smallest tasks, you may inadvertently be obstructing your organisation’s forward momentum. As a visionary leader, you must build the capacity to extend your influence and address long-term strategic objectives.

Often, an oversized ego or a hero mentality can significantly impede your ability to cultivate visionary leadership. For example, Sarah didn’t yet trust her new team to execute her strategies, so she took on a lot of the work herself. However, it’s vital to recognise that delegation is a cornerstone of leadership. By doing so, you can free yourself from the burden of micromanagement and empower your team to contribute to the broader vision, enabling your organisation’s progress towards its long-term strategic goals. Scaling your leadership is about shouldering increased responsibilities for the greater good and empowering others to embrace and achieve the shared vision and strategic objectives.

3. Are you more focused on the operations vs strategy?

Visionary leaders navigate uncertainty, think strategically, and connect the dots for transformative growth. They inspire others to embark on a change journey toward long-term success.

Leaders driven by immediate results often become consumed by day-to-day operations and short-term goals. While the importance of operational efficiency cannot be overstated, visionary leadership calls for a shift in focus towards long-term strategy and comprehensive planning.

To embark on a journey towards visionary leadership, it is essential to dedicate time to contemplating the future, recognise novel opportunities, and design a roadmap for transformative growth. This planful and proactive approach will yield tangible opportunities, including designing multiple planning5 options, building long-term team capabilities, forging key strategic external partnerships and charting a course for strategic change and growth. Leaders who remain solely focused on the present can miss out on visionary possibilities.

Second, Determine How to Reposition Yourself as a Visionary.

Repositioning yourself requires a deliberate shift in mindset, behaviour, and actions. Here are some ways to get started:

1. Be an empowering leader.

To become a visionary leader, you must learn to delegate effectively and empower your team to problem-solve without you. Trust your team’s capabilities and empower them to make decisions and take ownership of their projects. By doing so, you free up your time to focus on long-term strategy and innovation, rather than getting bogged down in the day-to-day details. Whether you are joining a new group like Sarah or being promoted to take on larger responsibility, start by understanding the roles and responsibilities of your team. Plan to increase your team’s autonomy, providing guidance and support when needed.

2. Balance short-term and long-term.

It’s essential to strike a balance between short-term commercial goals and long-term strategic vision. Allocate dedicated time for strategic thinking and planning. Set aside regular sessions for brainstorming, scenario analysis, and future-focused discussions as this will create a habit for you to sit in your thoughts and achieve flow6 making it a priority to explore emerging trends, technologies, and potential disruptors in your industry. By allocating time for both immediate tasks and future planning, you can effectively play the long game while delivering short-term results.

3. Be externally focused.

Shift your focus from internal dynamics to external factors that influence your industry and market. Spend time networking, attending industry events, and engaging with thought leaders. Encourage your team to do the same within their scope. By understanding external trends and customer needs, you can anticipate changes, identify growth opportunities, and adapt your strategy accordingly. Look for ways to connect with customers, partners, and competitors to gain insights that inform your vision.

4. Embrace uncertainty and change.

Embrace the discomfort of change and encourage a culture of innovation within your team or organisation. Remember that it all starts with you. As Jeff Dyer, Hal Gregersen, and Clayton M. Christensen wrote, “As we come to define ourselves as creative, we change our behaviors and we can actually become more creative.” Sarah faced this challenge. She had gotten to where she was by her relentless delivery of results. Now, she was being asked to focus on breakthrough innovation that could create a new vertical and step-change growth.

Through coaching, Sarah started to shift her focus on the long-term growth opportunities and designing the organisation structure, process, and capabilities that could drive breakthrough innovation. She redefined what success and winning meant for herself and her teams. By asking more open-ended questions, taking calculated risks, and embracing her new identity as an innovator, she started to create an environment where new ideas could flourish. When you foster a culture of innovation, you must create platforms for idea-sharing, provide resources for experimentation, and celebrate and recognise innovative initiatives and successes. This way you are motivating and rewarding your team for the right behaviours and innovative thinking.

Third, Take Action

Once you have repositioned yourself as a visionary leader, it is crucial to take action to bring your new identity to life. Here are some effective strategies to help you get started:

1. Lead the way.

To be visionary, you must ignite inspiration and earn the trust of the employees you are looking to lead. Leading by example means embodying the qualities and behaviours you want others to emulate. Align your actions with your vision and values. Paint a vivid picture of the desired culture and mindset. Let authenticity and integrity guide your decisions and actions. When you consistently act in alignment with your vision, you build trust among your team and stakeholders, inspiring others to follow suit. Show them what it means to lead with integrity, empathy, and resilience. Your actions will speak volumes, fostering a culture of trust, respect, and accountability.

2. Seek diverse perspectives.

Actively seek out diverse perspectives7 and opinions from your team and stakeholders. Encourage open dialogue, active listening, and constructive feedback to foster an inclusive environment that values different viewpoints. Steve Jobs said it best, “Creativity is just connecting things…The broader one’s understanding of the human experience, the better design we will have.” Practise transparency and communicate across all levels to create an open system. In addition, bring in new external perspectives, such as inspirational speakers or explore coaches to help your team break from old patterns and develop the skills needed for the long-term success of the organisation.

3. Become agile and adaptable.

Embrace flexibility and adaptability to navigate changing circumstances and seize new opportunities. Encourage a mindset of continuous improvement and learning, allowing for adjustments in strategies as needed. Recognise that being a visionary leader is an ongoing journey, requiring continuous assessment and adaptation of strategies in response to changing circumstances and evolving market dynamics.

4. Build strategic partnerships.

Collaborate with key stakeholders and build strategic partnerships both within and outside your organisation. Foster relationships that support your long-term goals and enhance your ability to drive positive change. As Jack Ma, co-founder of Alibaba Group famously said, “Never give up. Today is hard, tomorrow will be worse, but the day after tomorrow will be sunshine.” Remember, action is the catalyst for change. By implementing these strategies, you can demonstrate your commitment to your vision, inspire others, and cultivate a culture of long-term growth and success.

Repositioning yourself as a visionary leader is a transformative journey that requires time and effort. It involves letting go of some control, reevaluating priorities, and embracing a broader perspective. By actively working on these strategies, you can shift from focusing on immediate results to adopting a visionary leadership style that drives both short-term success and long-term growth and relevance in a rapidly changing business landscape.

About the Author

Jenny Fernandez is an award-winning executive and team coach, keynote speaker, and advisor. She helps senior leaders become more collaborative, innovative, and resilient. She works with Global companies and scaling start-ups, conducts leadership workshops, and teaches at Columbia Business and NYU. Learn more at www.jennyfernandez.com.

References:

1. How to make scenario planning more effective. February 2022. McKinsey & Company. https://www.mckinsey.com/~/media/mckinsey/email/classics/2022/2022-02-19b.html

2. Age and Tenure in the C-Suite: Korn Ferry Study Reveals Trends by Title and Industry. 21 January 2020. Nasdaq. https://www.nasdaq.com/press-release/age-and-tenure-in-the-c-suite:-korn-ferry-study-reveals-trends-by-title-and-industry

3. Becoming More Collaborative — When You Like to Be in Control. 23 March 2023. Harvard Business Review. https://hbr.org/2023/03/becoming-more-collaborative-when-you-like-to-be-in-control

4. How to get the world back on track. 27 March 2024. McKinsey & Company. https://www.mckinsey.com/featured-insights/themes/how-to-get-the-world-back-on-track

5. Anticipate – Build future-proof strategies based on scenario planning. Deloitte. https://www2.deloitte.com/de/de/pages/strategy/solutions/scenario-planning-and-future-strategy.html

6. Flow: The Psychology of Optimal Experience Paperback. Amazon. https://www.amazon.com/Flow-Psychology-Experience-Perennial-Classics/dp/0061339202

7. How building teams with diverse work experiences can drive success. 06 January 2023. Fast Company. https://www.fastcompany.com/90823224/ing-diversity-complementary-skills-success

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It has become increasingly common for companies to implement supply-chain diversity to maintain a good image and show commitment to sustainability efforts. Here are some insights into how Fortune Global 500 companies are diversifying their supply chains.

As companies face growing demands for supply-chain transparency and inclusive workplaces, many, especially in the US and Europe, are stepping up efforts to expand their supplier diversity.

Gone are the days when companies could consider their supply chain – the complex web of third-party contractors and sub-contractors – to be independent of headquarters. An important turning point came in 2013 with the collapse of the infamous Rana Plaza in Bangladesh which killed more than 1,100 people and revealed just how little many Western fashion brands knew about who was making their clothes and under what conditions.

Now global companies are expected to know who is producing their goods and providing their services, and that their basic values are aligned. Those who don’t, risk serious damage to their reputation. Additionally, for companies taking sustainability seriously, the supply chain forms part of Scope 3 emissions, which include not only a company’s directly owned or controlled activities but also its full value chain.

An increasing number of companies include diversity under the umbrella of social responsibility. As a consequence, supplier diversity efforts are a natural extension of the heightened awareness of supply chains and drives to create more inclusive and diverse companies.

To understand what companies are doing and where, we examined the supplier diversity initiatives of Fortune Global 500 companies in 2020 and 2022.¹ We found that, overall, North American companies lead the way in implementing diversity programmes, but Europe is gaining ground. At the other end of the spectrum, firms from East and Southeast Asia – the majority of the list of companies – have little demonstrated interest in the issue. 

The numbers speak for themselves. Of the 214 Asian companies among the Fortune Global 500 companies, only 7% had specific supplier diversity programmes in 2022; in 2020, that percentage was 5.4%. Of the 117 North American companies, 86% had programmes in 2022, up from 79% in 2020. Western Europe had 43 companies on the list: 35% of them had diversity programmes in 2022, up from 28% in 2020. 

History and Context of Supplier Diversity

In our recently published paper, and based on our analysis of the Fortune Global 500 companies as well as in previous academic literature, we define supplier diversity as the effort made by a company to increase the relationships it has with suppliers that are owned or operated by disadvantaged groups and to improve those already in place. What counts as a disadvantaged group varies by country and region; depending on cultural and historical context, different places have their own distinctive demographics and groups that have suffered from a lack of opportunities.

But while there are variations, companies do coalesce around certain areas. The dimensions with more than 100 mentions in our data are gender, disability, sexual orientation, age/generation, ethnicity, race, gender identity, nationality, religion/creed and veterans (disabled or not). We note that 96% of the companies with a specific supplier diversity definition refer to gender, far more than any other dimension; broken down by region, gender tops the list everywhere.

It is useful to understand how supply-chain diversity has evolved. While diversity, equity and inclusion (DEI) has become another salvo in the US culture wars in recent years, diversity initiatives in supply chains started there during the Civil Rights movement in the mid-1960s² as a way to reverse long-standing discrimination against companies owned by ethnic minorities and women. Initially, the US federal government spearheaded efforts, using its procurement practices to target support for minority corporations.³ Over the years, the private sector climbed on board.

Globally, the UK was the first country to follow the US in adopting intentional policies to increase supplier diversity, particularly among ethnic minority- and women-owned businesses.⁴ Western Europe has joined this trend over the last several years.

Because the US was a pioneer in this area, many concepts have been rooted in its demographics and the groups traditionally discriminated against there. But each region is putting its stamp on policies. Many companies worldwide refer to ethnicity, but this may involve different concepts in different places (for example, immigrants in Europe and Aboriginal peoples in Australia). Companies that work with suppliers based in India sometimes refer to caste. In definitions of diverse suppliers, the US includes those owned by military veterans. Age is mentioned in places such as Asia and Europe, but less so in North America. Sexual orientation is often referenced by firms in Western Europe and North America but not in other regions represented in the sample.

It is worth noting which diversity dimensions are found in East and Southeast Asia, even if the initiatives are relatively scarce since they do not coincide with those from North America. The areas most often referenced by Asian companies are age/generation, nationality, disability and religion/creed.

How Companies Diversify Their Supply Chains

We found that companies implement supplier diversity efforts in two main ways: by creating specific supplier diversity programmes and/or by embedding diversity requirements into supplier codes of conduct (SCoC). The programmes tend to be more proactive in seeking to do business with a diverse group of vendors. They have been shown to have a number of intangible benefits for the buyer firm, including a stronger reputation, recognised leadership and the building of more robust partnerships.⁵

Broader in scope, supplier codes of conduct cover a range of topics beyond diversity, in order to foster ethical conduct within all organisations in the supply chain. They can convey a company’s values, covering areas including labour conditions such as maximum hours and minimum wages and ethical behaviour such as zero tolerance for bribery. Whereas SCoCs are guidelines to be followed by all vendors, supplier diversity programmes can be targeted to specific and, potentially, small subsets of suppliers, such as firms owned by individuals of a specific ethnic minority.

Again, location played a role in which approach companies generally take. US companies seem to lean more toward running supplier diversity programmes, while European firms tend to incorporate their diversity goals into their supplier code of conduct.

Correlation With Internal Diversity and Sustainability

By sector, finance and healthcare companies most actively pursued diversity among vendors. From the 2022 Fortune Global 500 data, the sector with the highest proportion of supplier diversity programmes is healthcare, with 72%, followed by motor vehicles and parts (51%) and technology (50%). Regarding diversity in their SCoCs, firms in the financial sector show the most activity, with 60% of companies, followed by the healthcare sector with 56%.

But beyond sector, it is a certain type of company that pays attention to supplier diversity, one that is concerned about the composition of its workforce and is also committed to sustainability more broadly.

Of the 2022 sample of 500 companies, 379 reported some form of data on employee diversity (e.g., gender or racial composition of their workforce); those that did were much more likely to have a supplier diversity programme than those that did not. Some 45% of companies that reported on internal diversity also had a supplier diversity programme; in contrast, only 7% of companies that failed to report on their own diversity had a supplier diversity programme. 

A similar pattern is seen around supplier sustainability. Companies that responded to public pressure to reduce their negative environmental and social impact with initiatives that addressed those challenges in their internal operations and/or immediate communities⁶ are also more likely to have supplier diversity programmes. Companies lacking in supplier sustainability initiatives are also generally lacking in supplier diversity initiatives.

We expect supplier diversity initiatives to be increasingly common among top global companies in the coming years. They respond not only to public expectations but also to demographic realities. If populational trends continue, companies owned by ethnic minorities and women will represent a majority of small businesses in the future. Companies that overlook them will be at a growing disadvantage.

About the Authors

Anna Sáez de Tejada Cuenca is an assistant professor in IESE Business School’s Operations, Information and Technology Department. She holds a PhD in Operations Management from the UCLA Anderson School of Management, an MSc in Mathematical Engineering and a BSc in Mathematics from the Universitat Politècnica de Catalunya. Anna’s research interests include sustainability, social responsibility and the circular economy, with a focus on the fashion industry.

Gemma Berenguer is an associate professor at the Universidad Carlos III de Madrid and was an assistant professor at Purdue University. She holds a PhD in Operations Research from the University of California, Berkeley. She also holds a MEng in Logistics and Supply Chain Management from ZLC, an MSc in Economics from the Barcelona School of Economics and a BSc in Mathematics from the Universitat Politècnica de Catalunya. Her main research topics are nonprofit supply chain management, sustainable operations and supply chain design.

References

1. Berenguer G., Costas Lorenzo N. and Sáez de Tejada Cuenca A (2024). The State of Supplier Diversity Initiatives by Large Corporations: The New Sustainable Supply Chain? Production and Operations Management: 1–11.
2. Bateman A., Barrington A., Date K. (2020). Why You Need a Supplier-Diversity Program. Harvard Business Review, August 17.
3. Shah M. and Ram M. (2006). Supplier Diversity and Minority Business Enterprise Development: Case Study Experience of Three US Multinationals. Supply Chain Management: An International Journal 11(1): 75–81.
4. Ram M., Theodorakopoulos N. and Worthington I. (2007). Policy Transfer in Practice: Implementing Supplier Diversity in the UK. Public Administration 85(3): 779–803.
5. Porter KK. (2019). Implementing Supplier Diversity: Driver of Entrepreneurship. Springer.
6. Thorlakson T., de Zegher JF and Lambin EF. (2018). Companies’ Contribution to Sustainability through Global Supply Chains. Proceedings of the National Academy of Sciences of the United States of America 115(9): 2072–2077.

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Over the past decade and beyond, these pioneering companies have significantly advanced technology, embraced sustainable practices, and redefined user experiences, leaving an indelible mark on the global stage. Their achievements reflect a loyalty to quality and a vision for a brighter, more connected future.

The accomplishments of these companies in 2024 and their contributions to their respective sectors have cemented their status as leaders and forerunners in global technological progress. World Future Awards honors each brand in the TOP 100 and extends recognition to their distinguished contributions to shaping a more connected and secure world of tomorrow.

Key Contributors Of The 100 Global Innovation Companies

1. Alphabet Inc. (Google): Pioneering developments in artificial intelligence and quantum computing, revolutionizing how we interact with technology and access information.
2. Tesla, Inc.: Leading the charge in electric vehicle innovation and sustainable energy solutions, driving the world toward a greener future.
3. SpaceX: Transforming space exploration and satellite deployment, making space more accessible and inspiring a new era of interplanetary travel.
4. Microsoft Corporation: Innovating in cloud computing and artificial intelligence, enhancing productivity and connectivity across the globe.
5. Amazon.com, Inc.: Redefining e-commerce and logistics, setting new standards in customer experience and supply chain efficiency.
6. Samsung Electronics: Advancing consumer electronics and semiconductor technology, shaping the future of smart devices and digital connectivity.
7. Apple Inc.: Continually pushing the boundaries of design and functionality in consumer electronics, creating products that redefine user experience.
8. Siemens AG: Innovating in industrial automation and smart infrastructure, promoting efficient and intelligent systems.
9. Dyson: Dyson Ltd is a British technology company renowned for its innovative vacuum cleaners, air purifiers, hand dryers, bladeless fans, heaters, and hair dryers. Founded by Sir James Dyson, the company emphasizes cutting-edge engineering and design.
10. Grubhub: Grubhub Inc. is an American online and mobile food ordering and delivery marketplace that connects diners with local restaurants. It provides a convenient way to order food from a wide variety of cuisines and delivery options.
11. Nike: Nike, Inc. is a multinational corporation that designs, manufactures, and markets footwear, apparel, equipment, and accessories. Known for its iconic “Swoosh” logo and “Just Do It” slogan, Nike is a global leader in sportswear and athletic products.
12. Belkin: Belkin International, Inc. is an American consumer electronics and networking company that produces products like wireless chargers, home automation devices, networking solutions, and various accessories for computers and mobile devices.
13. Xerox: Xerox Holdings Corporation is an American corporation that sells print and digital document products and services. It is best known for its photocopiers, printers, and office solutions that revolutionized document management.
14. Oral-B: Oral-B is an American brand of oral hygiene products, including toothbrushes, toothpaste, and dental floss. It is a leader in dental care technology, particularly known for its electric toothbrushes.
15. Figma: Figma is a collaborative interface design tool used for web and mobile application development. It allows multiple users to design, prototype, and share feedback in real-time, fostering collaboration among design teams.
16. Rivian: Rivian Automotive, Inc. is an American electric vehicle automaker known for its electric trucks and SUVs. The company focuses on adventure-oriented EVs with advanced technology and sustainability at its core.
17. Toshiba: Toshiba Corporation is a Japanese multinational conglomerate that manufactures a diverse range of products and services including electronics, power systems, and IT solutions. It is known for its innovations in consumer electronics and infrastructure systems.
18. DoorDash: DoorDash, Inc. is an American on-demand prepared food delivery service. It connects customers with local restaurants and provides quick delivery of meals, making dining more convenient.
19. Samsara: Samsara Inc. is a provider of Internet of Things (IoT) solutions that help businesses improve their operational efficiency. It offers products for fleet management, industrial process monitoring, and other applications using sensors and cloud-based software.
20. Mirror: Mirror is a nearly invisible interactive home gym that streams live and on-demand fitness classes. Acquired by Lululemon, it offers a wide variety of workouts and personal training sessions.
21. Krups: Krups is a German brand of kitchen appliances known for its coffee makers and precision-engineered products. It emphasizes innovation, quality, and user-friendly design in its appliances.
22. Canon: Canon Inc. is a Japanese multinational corporation specializing in imaging and optical products, including cameras, camcorders, printers, and medical equipment. Canon is a leader in the imaging industry with a reputation for high-quality products.
23. Netflix: Netflix, Inc. is an American streaming service and production company. It offers a wide variety of TV shows, movies, documentaries, and original programming across numerous genres and languages.
24. Miro: Miro is an online collaborative whiteboard platform designed to facilitate remote work. It provides tools for brainstorming, planning, and collaboration, making it easier for teams to work together from different locations.
25. Brex: Brex Inc. is a financial services company that offers business credit cards and cash management accounts. It is designed to help startups and growing companies manage their finances more efficiently.
26. Gemini: Gemini is a cryptocurrency exchange and custodian that allows users to buy, sell, and store digital assets. It is known for its security and regulatory compliance in the crypto industry.
27. Cameo: Cameo is an online platform that allows celebrities to send personalized video messages to fans. It has become popular for connecting fans with their favorite stars in a unique and personal way.
28. MetaQuest: MetaQuest (formerly Oculus Quest) is a line of virtual reality headsets developed by Meta Platforms. It offers an immersive VR experience for gaming, social interaction, and productivity.
29. Kiswe: Kiswe is a video streaming technology company that specializes in interactive live streaming. It provides solutions for broadcasters to engage with their audiences in innovative ways.
30. NIO: NIO Inc. is a Chinese electric vehicle manufacturer known for its innovative and high-performance electric vehicles. NIO focuses on creating a premium EV.
31. Sony: Sony Group Corporation is a Japanese multinational conglomerate known for its electronics, gaming, entertainment, and financial services. Sony is a leader in the development of consumer electronics and entertainment products.
32. Nuro: Nuro is a robotics company that specializes in autonomous delivery vehicles. These vehicles are designed to transport goods locally, offering a safe, efficient, and sustainable delivery solution.
33. GoPro: GoPro, Inc. is an American technology company known for its action cameras. GoPro cameras are widely used for capturing high-quality video in extreme conditions and are popular in sports and adventure videography.
34. Glossier: Glossier, Inc. is an American skincare and cosmetics company that sells products directly to consumers through e-commerce. It is known for its minimalist packaging and focus on natural beauty.
35. Google Fi: Google Fi is a telecommunications service by Google that provides phone calls, SMS, and mobile broadband using cellular networks and Wi-Fi. It aims to offer flexible and high-quality mobile services.
36. Jura: Jura Elektroapparate AG is a Swiss developer and distributor of home appliances, particularly known for its fully automatic espresso machines. Jura products are celebrated for their quality, design, and innovation in coffee making.
37. Spotify: A major player in digital music streaming, innovating in music discovery and personalized recommendations.
38. Adobe: Known for creative software like Photoshop and Premiere, Adobe also excels in digital marketing solutions.
39. Square: Innovating in financial services and mobile payments, making transactions easier for small businesses.
40. Stripe: Innovating in fintech, Stripe provides powerful payment processing solutions for internet businesses.
41. Huawei: A leader in telecommunications and consumer electronics, with significant advancements in 5G technology.
42. Meta (formerly Facebook): Innovating in social media, virtual reality (Oculus), and augmented reality.
43. Intel: A key player in semiconductor manufacturing, Intel drives innovation in processors and various computing technologies.
44. IBM: Focused on AI, cloud computing, and quantum computing, IBM continues to innovate in enterprise technology solutions.
45. Salesforce: Leading in customer relationship management (CRM) software and cloud-based enterprise solutions.
46. Oracle Corporation: Recognized for its innovations in database management systems and enterprise software solutions, Oracle has been a cornerstone in the technology sector, enhancing data management and business applications.
47. Cisco Systems: A leader in networking technology, Cisco has transformed global communications with its pioneering solutions in internet networking, cybersecurity, and IoT.
48. QUALCOMM Incorporated: At the forefront of wireless technology, QUALCOMM has driven advancements in mobile communications, including 5G, enabling faster and more reliable connectivity worldwide.
49. Eli Lilly and Company: A prominent name in pharmaceuticals, Eli Lilly has made significant contributions to medical research and drug development, improving healthcare outcomes globally.
50. SAP SE: Known for its enterprise software, SAP has revolutionized business operations with its comprehensive solutions in ERP, analytics, and cloud computing.
51. Mastercard: Innovating in the financial services industry, Mastercard has enhanced payment systems and financial inclusion with its secure and efficient transaction solutions.
52. Airbus SE: A leading aerospace manufacturer, Airbus has advanced aviation technology, contributing to more efficient and sustainable air travel.
53. BASF: A global leader in chemical manufacturing, BASF has driven innovation in materials science, agriculture, and sustainability.
54. Pernod Ricard: Renowned for its premium spirits and wines, Pernod Ricard has combined tradition with innovation in the beverage industry.
55. Takeda Pharmaceutical: As a major pharmaceutical company, Takeda has focused on innovative treatments and therapies, particularly in oncology and gastroenterology.
56. ZTE Corporation: A key player in telecommunications, ZTE has advanced mobile communications and networking technology, including 5G infrastructure.
57. DUPONT: With a long history of scientific innovation, DUPONT has contributed to advancements in materials science, agriculture, and electronics.
58. 3M: Known for its diverse range of products, 3M has led innovations in health care, consumer goods, and industrial solutions.
59. Expedia Group: Transforming travel and tourism, Expedia has provided innovative online travel booking and services, enhancing the travel experience.
60. Visa Inc.: A global leader in digital payments, Visa has developed secure and efficient payment systems, facilitating global commerce.
61. Baidu: As a major technology company in China, Baidu has pioneered advancements in AI, search engines, and autonomous driving.
62. UPS (United Parcel Service): A leader in logistics, UPS has innovated in supply chain management and delivery services, improving global logistics efficiency.
63. L’Oréal: A global leader in beauty and cosmetics, L’Oréal has driven innovation in skincare, makeup, and sustainable beauty products.
64. Diageo: A prominent player in the beverage industry, Diageo has combined heritage and innovation in its portfolio of spirits and beers.
65. Nestlé: As a leading food and beverage company, Nestlé has innovated in nutrition, health, and wellness, offering a wide range of products.
66. ABB Ltd.: A leader in industrial automation and robotics, ABB has advanced technologies in electrification, robotics, and motion.
67. Rolls-Royce Holdings plc: Known for its high-performance engines, Rolls-Royce has innovated in the aerospace, marine, and energy sectors.
68. TOTAL S.A.: A major energy company, TOTAL has driven advancements in oil, gas, and renewable energy, contributing to the global energy transition.
69. Ferrari N.V.: Renowned for its luxury sports cars, Ferrari has combined cutting-edge automotive technology with incomparable design and performance.
70. PepsiCo, Inc.: A global leader in food and beverages, PepsiCo has innovated in product development and sustainability in its diverse portfolio.
71. Thomson Reuters Corporation: A leading provider of business information services, Thomson Reuters has advanced data analytics and media solutions.
72. X, Inc.: As a social media giant, X (formerly Twitter) has revolutionized communication and social interaction in the digital age.
73. Nikon Corporation: Known for its optical and imaging products, Nikon has driven innovation in cameras, microscopes, and precision equipment.
74. Tata Motors Limited: A major automotive manufacturer, Tata Motors has advanced vehicle design and technology, contributing to global automotive innovation.
75. POSCO: One of the world’s largest steelmakers, POSCO has driven advancements in steel production and materials technology.
76. AB Electrolux: A leader in household appliances, Electrolux has innovated in-home care and appliances, enhancing everyday living.
77. Chevron Corporation: A major energy company, Chevron has driven advancements in oil and gas exploration and production, as well as renewable energy.
78. Kawasaki Heavy Industries: Known for its diverse range of products, Kawasaki has innovated in aerospace, energy, industrial equipment, and transportation.
79. Danone SA: A global leader in food and beverages, Danone has focused on nutrition and health, innovating in dairy, plant-based products, and water.
80. Dropbox, Inc.: A pioneer in cloud storage and collaboration tools, Dropbox has enhanced how people and businesses store and share information.
81. RWE Aktiengesellschaft: A major energy company, RWE has driven advancements in renewable energy and power generation.
82. HOYA Corporation: Known for its optical products, HOYA has innovated in healthcare, medical technology, and electronics.
83. Keihin Corporation: A leader in automotive components, Keihin has advanced fuel injection systems and air conditioning technologies.
84. Taisho Pharmaceutical: A major pharmaceutical company, Taisho has focused on over-the-counter medicines and healthcare products.
85. Daimler AG: A leading automotive manufacturer, Daimler has driven innovations in vehicle design, safety, and autonomous driving.
86. Hitachi, Ltd.: A global technology company, Hitachi has advanced solutions in IT, energy, industry, and healthcare.
87. Valeo SA: An automotive supplier, Valeo has driven advancements in smart mobility, electrification, and autonomous driving technologies.
88. Schaeffler AG: A global automotive and industrial supplier, Schaeffler has innovated in precision components and systems.
89. Konica Minolta, Inc.: Known for its imaging and optical products, Konica Minolta has driven innovation in digital imaging and office solutions.
90. Gensler: A global architecture and design firm, Gensler has advanced sustainable and innovative design solutions for the built environment.
91. Mattel, Inc.: A leader in the toy industry, Mattel has driven creativity and innovation in children’s toys and entertainment.
92. OpenAI: At the forefront of artificial intelligence research, OpenAI has driven advancements in AI technologies and applications.
93. KinetX: A leader in aerospace engineering, KinetX has advanced satellite navigation and space mission design.
94. Hopper: A travel technology company, Hopper has innovated in predictive analytics for travel booking and planning.
95. Vanta: Specializing in security and compliance automation, Vanta has enhanced data protection and regulatory compliance for businesses.
96. Symbotic: A leader in warehouse automation, Symbotic has driven innovations in robotics and AI for supply chain efficiency.
97. Honda Motor Co., Ltd.: A major automotive manufacturer, Honda has advanced vehicle technology, robotics, and sustainable mobility solutions.
98. Bitcoin: Bitcoin is a decentralized digital currency that operates on a peer-to-peer network, allowing transactions without the need for intermediaries. Created in 2009 by the pseudonymous Satoshi Nakamoto, it introduced blockchain technology, revolutionizing the concept of digital assets and finance.
99. Airbnb: Airbnb is an online marketplace that connects people looking to rent accommodations. Founded in 2008, it has grown into a global platform facilitating unique travel experiences.
100. Johnson & Johnson: Recognized for their groundbreaking work in medical devices, pharmaceuticals, and consumer health products, Johnson & Johnson has consistently driven healthcare innovation, improving patient outcomes worldwide.

Recognizing Their Lasting Impact

The team at World Future Awards praises the dedication and achievements of the abovementioned trailblazers, acknowledging their lasting impact on the global stage. Each company’s visionary work not only addresses current challenges but also paves the way for a more prosperous and sustainable future.

To learn more about World Future Awards, explore their website here: https://worldfutureawards.com/

About World Future Awards

The World Future Awards is dedicated to celebrating and promoting innovation across various sectors. Our mission is to highlight the achievements of visionary companies and individuals who are making significant contributions to the advancement of society and the betterment of our world.

The post World Future Awards Honors the TOP 100 Global Innovation Companies of 2024 appeared first on The European Business Review.

Generating and harnessing energy within an organisation isn’t just a fleeting or whimsical notion: it is a powerhouse that ignites the entire community.   

At Insights, we recently brought our entire leadership team together in Poland, sparking inspiration to grow and thrive for our customers in the coming years. While setting strategies and rallying around core projects are crucial, it’s all too easy for people to burn out or fall into repetitive routines. We have set ambitious goals and rely on the energy of all our teams and people to deliver. Sustaining momentum in the workplace over the weeks, months, and years ahead is a real challenge.  

That’s why our theme this year was “Energising Together.” By tapping into the collective and unique energies of our community, we aim to sustain momentum and continually break new ground. The concept of “energising together” empowers companies to outpace competitors and pioneer groundbreaking ideas. It is so infectious that it inspires communities to want more. 

For me, the key factors of “energising together” as an organisation are: 

Harnessing the unique energy of each individual. This is the essence of the “energise” part. To achieve true collective synergy, everyone must cultivate profound self-awareness, understanding their own sources of energy. This process is akin to a superhero discovering their powers and learning how to use them for the greater good, rather than to the detriment of themselves or others. It involves recognising one’s strengths, weaknesses, leadership style, and preferred ways of being led. 

At Insights, we express these preferences through the language of color, with each person being a unique blend of Fiery Red, Sunshine Yellow, Cool Blue, and Earth Green. In Poland, we celebrated our 10 millionth Insights Discovery Profile completion. Now, everyone in the company is re-experiencing their profiles and refreshing their understanding of personal preferences. This practice is vital as we grow, ensuring we maintain a clear understanding of how we present ourselves as an organisation, the preferences we lead with, and where there might be gaps that lead to disconnects in our relationships. 

Enabling those energies to bounce off one another is the essence of the “together” part. We aim to create an environment where individuals not only find their energy but also amplify it collectively, becoming greater than the sum of their parts. Carl Jung highlighted the difference between extraversion and introversion—people gain energy in different ways. Those who prefer introversion recharge from within, often through reflection, reading, or time away from the thick of the action. Conversely, those who lean towards extraversion thrive on quick action, the challenge of the moment and interaction with others. 

“Energising together” means crafting a space where introverts aren’t drained by a fast-paced, bustling environment but can replenish their energy. Likewise, it ensures that extroverts aren’t isolated, working without an outlet for their dynamism. It’s crucial for everyone to understand and effectively use their unique leadership styles and preferences within the cultural context. There is no right or wrong way, yet their needs to be understanding and awareness. This balance fosters a dynamic and inclusive atmosphere where all types of energy can flourish to be the best version of themselves. 

Nurturing a culture where everyone feels empowered to use their energy means creating an environment where taking calculated risks is not only accepted but encouraged. It’s about fostering a space where people feel safe to voice their opinions, knowing they’ll be supported every step of the way. This kind of culture sparks innovation and growth, allowing creativity to flourish and new ideas to thrive without the fear of failure holding anyone back. 

At Insights, we weave golden threads that sustain our culture—like our daily check-in card game where we encourage moments of reflection, creative global events where we connect more deeply with our purpose and our culture, and our communication styles, so that as we deliver against our strategy we are doing it through collaboration with others towards purposeful outcomes. These elements create an authentic environment which allows everyone to bring their whole selves to the conversation. 

Crafting an inclusive culture where everyone’s voice is valued means ensuring that every individual, regardless of their background, location, or preferences, feels heard and respected. It’s about creating a space where leaders transform into mentors and guides, empowering their team members to make decisions and take ownership of their roles. In this environment, everyone is seen as a leader, contributing their unique perspectives and expertise to drive collective success.  

This inclusive approach empowers everyone to articulate and communicate the company’s strategy in a manner that resonates with diverse audiences, fostering unity and a shared sense of purpose throughout the organisation. Our strategic focus revolves around inspiring our practitioners by being inspirational ourselves. Each individual can express, in their unique way, how they contribute to this strategic direction. 

Creating a dynamic learning environment where knowledge seamlessly intertwines with daily tasks is the ultimate goal. It’s all about nurturing a bond between employees and employers founded on mutual support and growth. You’re not just a cog in the machine; you’re encouraged and empowered to chase your dreams and evolve continuously, with your company by your side every step of the journey. 

During our recent event in Poland, we infused gamification techniques throughout the experience. This helped us flex our muscles in embodying our ‘good day’ behaviors, all in alignment with our organizational values. The outcomes left everyone buzzing as we basked in the glow of progress, striving to become better versions of ourselves in each other’s company. 

Championing innovation is critical for organisations. We’ve discussed the importance of feeling empowered to use your energy; the next step is to embrace bold ideas that push the boundaries of customer expectations. It’s about the thrill of crafting new products and solutions that surprise and delight. Together, we unleash a wave of ingenuity that propels us beyond the ordinary, shaping a future where the possibilities are endless. 

In today’s rapidly evolving business landscape, generating and harnessing energy within an organisation is essential. Through energising together you too can create a future where possibilities are endless and collective potential knows no bounds. Not just meeting challenges but transforming them into opportunities for growth and success.

About the Author 

Marcus Wylie is currently Head of Culture at Insights.  Over the years he has led the creation of just about every product that Insights has to offer, partnering with some of the world’s leading organisations around the globe to build, pilot and implement new products.  He holds vast experience in delivering training virtually and face to face with multi-hundreds of people, as well as facilitating intimate, purposeful and high-impact workshop experiences with leadership teams and Executives. 

The post Energising Together: The Art of Unleashing Collective Potential  appeared first on The European Business Review.

Could generative AI breathe new life into the old continent? Europe’s technology deficit with North America is well-documented; last year our research explored how the region’s lower technology maturity poses a threat to business reinvention efforts.^[i] The advent of generative AI, however, presents a chance to catch up, by boosting the creativity and efficiency of Europe’s large cohort of knowledge workers. We estimate that generative AI could raise the forecast rate of economic expansion across the region by 0.6 percentage points per annum over the next 15 years.^[ii]

Europe’s technology industry is dwarfed by that of the US, which is home to nearly five (4.5) times as many of the world’s 100 largest technology companies.^[iii] What is more concerning is that companies headquartered in Europe tend to be less tech-savvy than their peers across the Atlantic. Accenture’s latest Resiliency Indexiv finds that European companies rank 30 percentage points below their North American competitors on technology maturity—a composite measure of investment in applications, infrastructure and cybersecurity.^[v] 

European executives recognise that these technology shortfalls are affecting performance: more than one in five say enterprise systems deficiencies have a large negative impact on competitiveness. This compares with one in eight executives globally.^[vi]   

New tech, new value

How can generative AI help to close the gap? We estimate that globally, generative AI has the potential to impact 36% of working hours either through automation or augmentation. Given Europe’s relatively high proportion of knowledge- and language task-based workers, 44% of hours could be transformed here.^[vii]  

This, in turn, would free up workers to focus on higher value-add activities. Indeed, by adopting generative AI responsibly and at scale, organizations could boost economic output across the 10 European countriesviii we studied by €2.3 trillion by 2038. This would raise the forecast rate of regional economic expansion by more than half—a major boon in today’s low-growth environment.^[ix]

The pivotal question is, are European companies primed to seize this opportunity?

The early signs are promising. The proportion of “Reinventors” in Europe – companies ahead of the pack in using new technologies and new ways of working to reach a new performance frontier – doubled to 11 per cent over the past 12 months.^[x] Moreover, 84 per cent of European executives (vs 80 per cent of those in other regions) say that generative AI is key to their reinvention strategy. And 72 per cent (vs 59 per cent) expect it to significantly improve performance.^[xi]

Thus, Europe sits at a competitive crossroads. Will it become a “maker” of the rules, governing everything from people to responsibility, and shape this new AI-powered business environment to its advantage? Or will it be simply a “taker”, following the lead of China and the US? That will depend on how companies address the five imperatives we explore below.

1. Lead with value

We are still in our infancy in terms of recognising and realising the potential of generative AI. Companies, therefore, need to adopt a value-led approach that fully accounts for the risks and returns when determining which business capabilities to reinvent through generative AI investments. This should include both “no regrets” investments (that offer efficiency and productivity improvements) and strategic bets (that promise a distinct, even industry-shaping, competitive advantage).

Early applications have focused on narrow use cases in functional processes that sit across industries. The top three components of the business to which European organisations plan to make fundamental changes using generative AI over the next three years are IT (74 per cent), marketing (47 per cent), and finance (43 per cent). The companies that gain a competitive edge will increasingly pivot from these “no regrets” applications to addressing critical areas of their industry’s value chain.

In doing so, the continent can play to its strengths in areas such as engineering and manufacturing in industrials, and capital project management in the renewables sector. The region can also leverage its diversity of cultures and languages to build models that are less prone to cultural and linguistic bias. For example, the multilingual model built by French start-up Mistral AI, which recently secured investment from Microsoft, is better able to overcome the English-language bias apparent in many of the models developed by US competitors. ^[xii]

2. Develop an AI-enabled, secure digital core

Companies with legacy systems and siloed data will struggle to realise the potential of foundation models, large deep-learning models that can be adapted to support multiple purposes. This is a particular concern in Europe, given that its businesses spend less in key IT areas such as cloud, mobility, data, and AI compared with their North American counterparts.^[xiii]

To move faster from piloting to scaling initiatives, European companies need to build a strong data and AI “backbone” into their digital core, a secure, cloud-based technology capability that both creates and empowers reinvention. They need to develop both a robust architecture for integrating diverse foundation models, and new capabilities to handle unstructured and synthetic data.

Building data products (high-quality, ready-to-use data formatted so that people and systems across an organisation can easily access it) and developing data pipelines are essential for assimilating the diverse data sources required for generative AI. Half of European companies recognise that they will need to make significant changes to their data strategy as a result.

Business leaders should also challenge their teams to use generative AI as an accelerator. Among European executives, 74% expect it to fundamentally reinvent their IT function (vs 60 per cent of peers globally). A case in point is Unilever’s global AI lab “Horizon3 Labs”.^[xiv] Here, the consumer goods multinational is working with Accenture, drawing on assets from our AI Navigator and proprietary model “switchboard”, which allows users to select a combination of models to address the unique business context.^[xv] The collaboration aims to surface new applications to enhance productivity, drive efficiencies, and accelerate disruptive and AI-powered innovations at scale.

3. Reinvent talent and ways of working

Generative AI is set to trigger the most significant shift in work since the agricultural and industrial revolutions. Anders Romare, Chief Digital and Information Officer at Novo Nordisk, captures the magnitude of the opportunity succinctly: “The data we generate from clinical trials is just enormous: it’s starting to be beyond the human capability to actually sort and understand and digest.” He says that generative AI can help aggregate and summarise the vast information to deliver a much “higher quality output”.^[xvi]

But if organisations adopt generative AI hastily – primarily to cut costs – it is likely to significantly reduce the potential economic gains outlined above. Companies must not overlook the need to reskill or upskill employees at scale. The full potential of generative AI will only be realised through a people-centric approach, in which employers focus on how to apply the technology to boost employee productivity and well-being.^[xvii]

In this context, Europe can capitalise on existing strengths. Companies across the region enjoy.^[xviii] As AI expands into more areas, individuals will need to reskill and upskill more often. European companies’ leading capabilities in people enablement could therefore be a source of significant competitive advantage.

4. Close the gap on responsible AI

To win people’s trust, the unparalleled potential of generative AI must be counterbalanced with an unwavering commitment to responsible innovation. Current limitations, such as “hallucinations”, IP infringement, and data explainability, are holding some companies back from investment. Employees, too, are apprehensive; they are three times as fearful as their bosses on the accuracy of tool output, and more than twice as likely to worry about job displacement.^[xix] Such concerns mean that 77 per cent of European business leaders are approaching associated investments with more caution, compared with 59 per cent of peers in North America.^[xx]

European companies must move swiftly to earn trust, for example by ensuring that algorithms and underlying data are as unbiased and as representative as possible. The incoming EU AI Act helps by providing a clear, consistent responsibility framework.^[xxi] The Act will support standardisation of responsible AI efforts across Europe, which will translate into easier collaboration and faster development times between companies, as well as enhanced experiences for customers. For example, Vodafone’s generative AI chatbot, now in pilot, improves user experience through an AI safety framework that protects customers.^[xxii]

5. Drive continuous reinvention

Just as species continuously adapt to survive, so too must business leaders. Reinvention is not a one-and-done endeavour. Most European executives (59 per cent) say they are at least somewhat effective in executing new strategies and performance goals continuously, but only 22 per cent say they are doing so “very effectively”. The companies that build the organisational capability to continuously reinvent, and take advantage of new technologies such as generative AI to do so, will be those best positioned to succeed.

In recent years, European companies have rapidly transformed to meet challenges ranging from the pandemic and supply chain disruption to the energy crisis and high inflation. Generative AI has the potential to bolster reinvention efforts and open new performance frontiers, but only if companies double down on technology, talent, and trust. It’s an opportunity that Europe must seize.

The authors would like to thank Mike Moore, Ana Ruiz Hernanz, and Jakub Wiatrak for their contributions to this article.

About the Authors

Jean-Marc Ollagnier is the Chief Executive Officer of Accenture in Europe and a member of Accenture’s global management committee.

Jack Azagury, Group Chief Executive – Accenture Strategy & Consulting and a member of Accenture’s global management committee.

Dominic King, EMEA Lead – Accenture Research.

References

1. Accenture (2023), “Accelerating Europe’s path to reinvention”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Accelerating-path-reinvention-Europe.pdf
2. Accenture analysis; for method, see Accenture (2024), “Work, workforce, workers: Reinvented in the age of generative AI”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf
3. By market capitalisation; https://companiesmarketcap.com/tech/largest-tech-companies-by-market-cap/, accessed on 1 May 2024
4. Accenture (2023), “Reinventing for resilience: A CEO’s guide”; https://www.accenture.com/gb-en/insights/strategy/reinventing-resilience
5. European companies rank in the 41^st percentile on average. North American companies in the 71^st percentile.
6. Accenture Pulse of Change Quarterly C-suite survey, October 2023; N=1500 executives of globally, of which N=390 from Germany, France, Italy, and the UK
7. Accenture analysis; for method, see Accenture (2024), “Work, workforce, workers: Reinvented in the age of generative AI”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf
8. Germany, UK, France, Italy, Spain, Switzerland, Sweden, Norway, Denmark, Finland; these 10 countries account for ~67 per cent of regional GDP.
9. Accenture analysis; for method, see Accenture (2024), “Work, workforce, workers: Reinvented in the age of generative AI”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf
10. Accenture (2024), “Reinvention in the age of generative AI”; https://www.accenture.com/gb-en/insights/consulting/total-enterprise-reinvention
11. Accenture Pulse of Change Quarterly C-suite survey, October 2023; N=1500 executives of globally, of which N=390 from Germany, France, Italy, and the UK
12. Sifted (2024), “Microsoft takes stake in French AI startup Mistral to push its multilingual models”; https://sifted.eu/articles/mistral-microsoft-multilingual-model
13. Accenture (2023), “Innovate or Fade”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Innovate-Fade-3July2023.pdf
14. Accenture (2023), “Unilever and Accenture Collaborate on Next Generation AI”; https://newsroom.accenture.com/news/2023/unilever-and-accenture-collaborate-on-next-generation-ai
15. Accenture (2023), “Accenture Launches Specialized Services to Help Companies Customize and Manage Foundation Models”; https://newsroom.accenture.com/news/2023/accenture-launches-specialized-services-to-help-companies-customize-and-manage-foundation-models
16. CDO Magazine (2023), “We Can Have More Innovation Capacity With Generative AI – Novo Nordisk Chief Digital and Information Officer”; https://www.cdomagazine.tech/talent-development/emea-video-we-can-have-more-innovation-capacity-with-generative-ai-novo-nordisk-chief-digital-and-information-officer
17. Accenture (2024), “Work, workforce, workers: Reinvented in the age of generative AI”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf
18. European companies rank in the 59^th percentile on average. North American companies in the 44^th percentile.
19. Accenture (2024), “Work, workforce, workers: Reinvented in the age of generative AI”; https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf
20. Accenture Pulse of Change Quarterly C-suite survey, October 2023; N=1500 executives of globally, of which N=390 from Germany, France, Italy, and the UK
21. Arnab Chakraborty (2024), “The EU AI Act: Are you ready for regulated AI?”; https://www.linkedin.com/pulse/eu-ai-act-you-ready-regulated-arnab-chakraborty-levy-chakraborty-8fgzc/
22. Vodafone (2024), “Vodafone youth brand VOXI launches large language model generative AI chatbot to enhance customer experience”; https://www.vodafone.co.uk/newscentre/press-release/voxi-launch-ai-chatbot/

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By Peter Weill & Stephanie L. Woerner

Top-performing firms reorganise several times to effectively use digital to capture value. In a series of CEO interviews, we identified four successful levers for maximising value from digital. Then, in a global survey, we found that the companies in the top quartile of effectiveness on these four levers were also top financial performers, growing 12 percentage points above their industry average, and leaders in innovation, with 45 per cent of their annual revenue coming from new products introduced in the last three years – a huge premium. In this paper, we describe the four levers and the reorganisation required, illustrating with examples including Standard Bank Group, the largest bank in Africa. To become a top performer takes persistence, as companies must perform organisational surgery – reorganising on average seven times to create the industry-leading value. It is like solving an organisational Rubik’s cube, with a big payoff.

How many major organisational changes has your company been through in the last five years, and did those changes create value? At MIT CISR, we studied over 700 companies to understand how companies unlock new digital value.¹  We found that a company must perform organisational surgery, often reorganising many times to create the value. The top-performing companies in our research underwent, on average, 7.2 major organisational changes in the preceding five years, but the results were worth the disruption, as the companies grew well above their industry average.

Historically, organising a company to maximise value from digital started with the technology leader looking out of the IT organisation to understand what the business needed.

We found that the companies in the top quartile of effectiveness at using these four levers were also top financial performers, growing at almost 12 percentage points above their industry average, and leaders in innovation, with 45 per cent of their annual revenue coming from new products introduced in the last three years. From the interviews, we learned that taking a top-executive perspective rather than a tech leader perspective can enable the kind of persistence, organisational buy-in, and change needed to unlock industry-leading digital value enterprise-wide.

In this paper, we describe the four levers and illustrate them with examples from companies including Standard Bank Group and ANZ, and discuss how to move from the technology-led governance to the enterprise-wide governance that is now needed to succeed.

The Four Levers to Create New Digital Value

Historically, organising a company to maximise value from digital started with the technology leader looking out of the IT organisation to understand what the business needed. But in today’s world of technology everywhere, it’s time to take, first, a CEO perspective and, then, an enterprise-wide one to design the organisation to maximise value from digital. To understand how top-performing companies organise for digital, we began by interviewing eight CEOs of large organisations and then followed up with their colleagues, to learn what organisational levers were used to create new digital value. Four levers to unlocking value emerged. Each of these levers needed to be supported by CEO involvement to drive the necessary changes in company and employee behaviour. Then we surveyed executives from 721 companies to understand best practices and the impacts of employing the levers on company performance.

Companies focused on these four levers to unlock new digital value:

1. Customer: Identifying and delighting the most important unique customer types.
2. Capability: Providing and reusing a shared capability as a service across customer types.
3. Commercialisation: Commercialising what the company is great at to generate new revenue.
4. Component: Designing, embedding, and reusing digital modules of self-contained business capabilities.

Each lever produced a specific type of value to help drive top performance:

1. Value from customer – focus: Customer loyalty and increased revenue per customer via tailored customer journeys and customer focus.
2. Value from capability – scale: Consistency and efficiency across different customer types while capturing key data.
3. Value from commercialisation – new revenues: New revenues from providing services to other companies based on what the company is great at.
4. Value from component – speed via reuse: Faster time to market using best practices and decentralised governance with better compliance.

Let’s go into more detail on each of the levers.

Identifying Unique Customer Types

To unlock new digital value from customers, a company’s senior executive team must first identify their set of unique customer types to focus on, describing each type’s persona, customer journey, data model, channels for engagement, and more. In financial services, customer types typically include home buyers, small business enterprises, corporations, and high-wealth individuals and families. Developing an understanding of its most important customer types helps a company to really empathise and focus on meeting customer needs. The top-quartile performers on growth focused on an average of 8.9 unique customer types, typically describing for each type how they preferred to engage with the company, the typical products and solutions needed, the kinds of offers found attractive, and the associated data profile and systems that made the customer journey easy. In our interviews, CEOs reported that each customer type needed a senior executive who had both decision rights and accountability for success and, increasingly, customer journeys were supported by providing curated access to complementary and partner service providers.

Driving a Shared Capability as a Service

Leveraging business capabilities as a shared service helps a company to generate speed and efficiency. Here, senior executives must first identify what capabilities are common across customer types. Standardising, automating, branding, and reusing these capabilities allows the company to drive consistency, which both provides the customer with a common experience across products and increases efficiencies for the company. Shared capabilities can lead to better insights, because the data collected is more consistent and in one place. For example, a key shared capability in banking is a unified customer profile that details a customer’s current assets, products, and a forecast of their future needs, along with their identity, credit score, risk tolerance, and other factors.

The top-quartile growth companies provided an average of 6.3 separate business capabilities as a service across (almost) all their customer types. Because this lever can be hard to implement politically, as they were often centralised, top performers were selective about which services to share across customer types, thereby ensuring that the services were strategically important and there were a manageable number.

Commercialising What the Company Is Great At

The top-quartile growth companies selected internal capabilities they were great at – their crown jewels – and commercialised them as a service to produce a new revenue stream. This anything-as-a-service model, which we call XaaS, is becoming an important growth area for many companies as digital connections between companies become easier. Examples of XaaS that some banks have developed include anti-money-laundering (AML), payments, know your customer (KYC), and foreign exchange (FX). Often, such services are essentially selling compliance as a service, allowing the company to derive more value from its own efforts to address increasing compliance costs and create increasing scale.

Australian bank ANZ has recently focused on providing XaaS in areas including international payments and anti-money-laundering (AML). ANZ CEO Shayne Elliott described the bank’s AML efforts:

We saw one major player exit this business as a result of some AML issues, which meant their customers had sixty days to find another provider. Of those, there were seventeen major mandates and we won sixteen of them. That took our [AML] market share from the low 40s to 58 per cent.² 

In our top-quartile companies on growth, an astounding 56 per cent of revenues were generated using the XaaS approach, unlocking a lot of previously untapped value.

Embedding, Nurturing, and Reusing Digital Modules

Embedded digital modules, sometimes called components, create new digital value for the company by driving consistency, compliance, and speed to market. Digital modules are “atomic” business capabilities, in that they are fully self-contained and right-sized. They are fine-tuned, automated, and reused in every possible application in the company, and nurtured by their owners to ensure they maintain best practice.

In financial services, typical examples of such modules are establishing the customer identity, onboarding a new customer, establishing or accessing a customer’s credit score, assessing risk, assessing compliance, and many other often-reused business capabilities. Often the motivation for these modules is to increase speed to market of different groups, while meeting compliance with regulations via consistency of approach and common reporting. Modules are built into the other three levers – customer types, shared capabilities, and XaaS – as well as other opportunities for reuse. The top-quartile companies on growth were 80 per cent effective at digital module reuse, improving their time to market and helping to generate an industry-leading percentage of revenues from new products introduced in the last three years.

Once a company has identified which business capability to modularise, it typically uses decentralised governance and APIs or some other kind of digital service to create the module and share it easily.

Top Performers on Growth and Innovation Used All Four Levers Effectively

Companies that were more effective at using the four levers individually grew faster than their peers. And the companies that were in the top quartile of effectiveness of all four levers combined grew even faster, at 11.7 percentage points above industry average.

Standard Bank Group, the largest financial services group in Africa,³  has used all four levers to unlock new digital value as part of the bank’s digital business transformation.

Unlocking New Value at Standard Bank Group

In its strategic transformation plan, Standard Bank Group describes serving the needs of clients in financial services and beyond by “banking the ecosystem” – i.e., providing financial services in all the ecosystems the bank is targeting. Behind this vision is Standard Bank’s inspiring purpose: “Africa is our home, we drive her growth.”⁴

The bank started by focusing on three client segments (Customer): consumer and high-net-worth clients, business and commercial clients, and wholesale clients. It identified client acquisition and engagement as the drivers for sustainable growth. The bank also initially targeted 10 ecosystems to operate in (Customer) – five that it would drive, such as agriculture and trade, and five that it would participate in, such as energy and education. It has since narrowed its focus to ecosystems where it is able to achieve the most competitiveness, including trade and home services. Standard Bank’s participation in an ecosystem typically involves offering B2B financial services the bank is great at (Commercialisation), such as FX and payments.

We found that in a digital / AI everywhere world, companies should rethink the traditional model of the technology organisation.

To enable shared capabilities as a service (Capability), the bank created a new group, called Client Solutions, that serviced the client segments with banking, insurance, and investment services. However, as the transformation progressed, the bank found that it was more efficient to provide these services within the client segments and reverted the segments to being more traditional business units.

Finally, a great deal of effort went into architecting modularity (Components). Standard Bank’s modularity relies on standardisation and simplification, as well as the technological capability to connect both internally and with partners, enabled by API readiness and integration and scalable and interoperable platforms. The bank calls developing modularity in this way “unpacking the honeycomb”, and tracks the number of digital solutions as a percentage of total solutions it has achieved. In 2021, 24 per cent of the bank’s banking solutions and 22 per cent of all solutions were digital solutions, and it was aiming for a target of 50 per cent across all solutions by 2025.

Standard Bank is making great progress toward its transformation goals, with the bank’s 2022 results demonstrating record revenue and earnings.⁵ The positive impacts continue in the first half of 2023, when the bank’s cost-income ratio (a common measure of efficiency) improved from varying between 55 and 58 per cent over the previous 10 years to 50.5 per cent.⁶

The Importance of Lever Governance in Unlocking Value

To unlock its value, each lever needs to be governed and nurtured differently (see figure 1). The Customer lever is typically owned and governed by business unit heads with responsibility for engaging each customer type. The governance of the Capability lever, because it spans different customer types, is typically owned centrally by a shared services group, COO, or CIO who operates those services for the rest of the company, perhaps on a chargeback basis. We have also seen leader-follower models, where one business unit takes the lead on a particular service and then provides it to the other business units. The ownership of the Commercialisation lever frequently belongs to a combination of people who sell business-to-business solutions and the specific business service owner (e.g., payments), often using a two-in-a-box model.⁷ Finally, components are typically owned and governed by the business owner of the business capability embedded in the component, such as risk management (owned by the head of risk), know your customer (the head of compliance), credit scoring (the CFO), or payments (the head of the payment service), often in partnership with a technology leader.

The Key to Realising Value from the Four Levers

We found that in a digital / AI everywhere world, companies should rethink the traditional model of the technology organisation. Instead of taking a technology-led perspective, we recommend taking the CEO, enterprise-wide perspective on designing the technology capability to unlock maximum value from digital. To be a top-quartile growth company in the digital era requires focusing on four levers to create digital value. But companies must iterate several times to get the levers to work together to unlock that value. And they have to implement an ownership and governance model that encourages nurturing and reuse of the four levers. They also need very good real-time metrics that measure the effectiveness of the levers, their impact on performance, and the capabilities needed to deliver them, shared widely via a dashboard. Finally, they need the support and vision of the CEO and top management team, along with the board, to help exploit the levers throughout the company. It is like solving an organisational Rubik’s cube with a big payoff.

This paper draws on Weill, Peter and Stephanie L. Woerner. “Unlocking New Digital Value.” MIT Sloan Center for Information Systems Research, Research Briefing, XXIII-7, July 2023.

About the Authors

Peter Weill, PhD, is an MIT Senior Research Scientist and Chairman of the Center for Information Systems Research (CISR) at the MIT Sloan School of Management, which studies and works with companies on how to transform for success in the digital era. MIT CISR has approximately 75 company members globally who use, debate, support and participate in the research. Peter’s work centres on the role, value, and governance of digitisation in enterprises and their ecosystems and has coauthored 10 books. Ziff Davis recognised Peter as #24 of “The Top 100 Most Influential People in IT” and the highest-ranked academic.

Stephanie L. Woerner, PhD, is a Principal Research Scientist at the MIT Sloan School of Management and Director of MIT CISR. She is a renowned researcher and speaker, and coauthor of Future Ready: The Four Pathways to Capturing Digital Value and What’s Your Digital Business Model? Six Questions to Help You Build the Next-Generation Enterprise, both published by Harvard Business Review Press. Stephanie studies how companies use technology and data to create more effective business models as well as how they manage the associated organisational change and governance and strategy implications. Stephanie’s research has appeared in MIT Sloan Management Review, Harvard Business Review, CNBC, Forbes, Chief Executive, and CIO.

References

1. This research is based on the MIT CISR 2022 Future Ready Survey (N=721), plus interviews with eight CEOs conducted in 2021–2 and case vignettes of five large companies in manufacturing, medical technology, financial services, and real estate.

2. Shayne Elliott, “Elliott: Accelerating Our Strategy”, ANZ bluenotes, 27 May 2021, https://bluenotes.anz.com/posts/2021/05/anz-ceo-shayne-elliott-banking-future.

3. Standard Bank Group was the largest financial services group in Africa, based on Tier 1 capital, in 2023; see T. Minney, “Africa’s Top 100 Banks in 2023”, African Business, 4 October 2023, https://african.business/2023/10/finance-services/africas-top-100-banks-in-2023

4. “Purpose and Values”, Standard Bank Group, https://www.standardbank.com/sbg/standard-bank-group/about-us/who-we-are/purpose-and-values.

5. See “Overview of Financial Results”, Investor Relations, Standard Bank Group, https://reporting.standardbank.com/overview-financial-results-2022/ .

6. https://reporting.standardbank.com/about-us/key-performance-indicators/

7. Two-in-a-box is a management model in which two (or more) people are given equal leadership authority and responsibility for a task or set of tasks, often in complementary roles. Read about a two-in-a-box model in use at DBS in S.K. Sia, P. Weill, and M. Xu, “DBS: From the ‘World’s Best Bank’ to Building the Future-Ready Enterprise”, MIT CISR Working Paper No. 436, 19 March 2019, https://cisr.mit.edu/publication/MIT_CISRwp436_DBS-FutureReadyEnterprise_SiaWeillXu.

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While you wait for your ship to come in, have you given any thought to building a lighthouse, or even dredging the harbour? Sometimes luck needs a little help, as Avi Liran explains.

Do you consider yourself lucky? Do you want to increase your luck?

It is believed that Napoleon Bonaparte countered criticisms about his reliance on luck in battles by stating, “I prefer lucky generals to skilled ones.” Napoleon ignored his Foreign Minister Maurice de Talleyrand-Périgord’s advice against the invasion of Russia in 1812, where he lost the war to “General Winter”. The lessons of history reveal that excessive reliance on luck and neglecting constructive criticism can exhaust one’s lucky streak.

Despite amassing billions through his telecommunications empire bearing his name, the former Thai Prime Minister Thaksin Shinawatra’s decision to evade taxes on the $2 billion sale of his conglomerate to the Singaporean Temasek Holdings accelerated his downfall because of corruption. While fortune favours the bold, it tends to evaporate when the arrogant are blinded by greed.

Before we embark on a quest for greater luck, let’s cast aside the shadows and identify the lurking enemies that threaten to swallow our good fortune whole. These are the biggest black holes of luck: greed, hubris, complacency, impulsivity, neglect of ethics, not listening to feedback, inflexibility, and short-sightedness and paralysis because of the fear of taking risks.

If you’re a fan of astrology or fortune tellers, beware. Just the other day, my fortune cookie declared, “Changing your hairstyle may bring you luck.” The irony? I’m bald. I think I’ll stick to more reliable sources of luck, like the five strategies I suggest in this article.

Brian Tracy once said, “I’ve found that luck is quite predictable. If you want more luck, take more chances. Be more active. Show up more often.”

Elivahy Goldratt said, “Good luck is when opportunity meets preparation, while bad luck is when lack of preparation meets reality.”

Luck is commonly associated with chance, but it turns out that there are science-backed tricks to improve your luck. A decade-long piece of research by psychology professor and author of “The Luck Factor”, Richard Wiseman, suggests that one’s actions, mindset, and behaviours can influence and increase their likelihood of experiencing good fortune or luck. Wiseman interviewed 400 people who self-identified themselves as “lucky” or “unlucky” and found that those who continually had good luck, professionally and personally, had some common traits. They responded to situations in similar ways.

Be open to new experiences

In 1928, amidst the clutter of his lab, Scottish physician Alexander Fleming stumbled upon a serendipitous discovery. A forgotten sandwich, nestled near a staphylococci culture, revealed a curious sight: a mouldy halo engulfing a bacteria-free zone. Intrigued, Fleming embraced his good luck and embarked on a journey of experimentation, eventually unlocking the power of penicillin, the antibiotic that would one day save countless millions.

To increase your luck, be open and notice the opportunities that come your way. In an experiment conducted by Dr Wiseman, he observed that lucky individuals seem to consistently stumble upon opportunities that their unlucky counterparts often overlook. He handed out newspapers to both lucky and unlucky participants, asking them to count the number of photographs inside.

Wiseman’s studies suggested that individuals who consider themselves lucky often find something positive about an “unlucky” situation and transform setbacks into springboards for new ventures, fuelling their remarkable fortune.

Listen to your intuition

Gabrielle ‘Coco’ Chanel’s rebel story is a fascinating example of how intuition against the norm can create luck. She was the first designer to dare to take elements from menswear and use them to make women’s clothing more functional. At a time when jersey fabric was primarily used for men’s underwear, Chanel’s intuitive gamble to use it for women’s clothing was unconventional. Her intuition paid off, making her designs both popular and accessible. She said in an interview, “Fashion is not simply a matter of clothes. Fashion is in the air, borne upon the wind. One intuits it. It is in the sky and on the road.”

People who see themselves as lucky tend to be more decisive. They make swift decisions by tuning into their intuition. They’re more likely to take risks, take action, and expose themselves to new opportunities.

Use Optimism and Positive Expectancy

Blind optimism rarely brews success, but Howard Schultz’s journey with Starbucks is a classic tale of how optimism can fundamentally change one’s trajectory, turning challenges into opportunities and creating what appears to be “luck”. In his book “Pour Your Heart Into It: How Starbucks Built a Company One Cup at a Time”, he shared that he faced scepticism from investors. After the original Starbucks owners rejected his idea of creating a coffeehouse culture, Schultz decided to pursue the concept independently and go to investors. He was turned down by 217 of the 242 investors he pitched to.

In my funny resilience talk “Bounce Forward with a Smile”, I share five to seven tips on how to recycle the trash of adversity into fertiliser. Wiseman’s studies suggested that individuals who consider themselves lucky often find something positive about an “unlucky” situation and transform setbacks into springboards for new ventures, fuelling their remarkable fortune. In general, these lucky people tend to possess a more positive attitude towards life, are happier, and notice and capitalise on opportunities that others might miss.

Be Flexible

As the COVID-19 pandemic erupted, Uber faced a major crisis, with plummeting ride-hailing demand due to lockdowns and travel restrictions. Recognising the increased demand for contactless food delivery, Uber Eats stepped into the spotlight. They invested heavily in marketing and promotions, attracting new customers and restaurants to the platform. They streamlined delivery operations, focusing on efficiency and contactless procedures, and expanded their offerings by adding grocery delivery, alcohol delivery, and partnerships with convenience stores.

“Lucky” folks often possess that invisible advantage. If plans change, they’re ready to pivot like a nimble dancer, finding luck in new circumstances.

The ability to adapt to changing circumstances is a key factor in capitalising on opportunities and overcoming and adapting to life’s unpredictable twists and turns. People who see themselves as lucky tend to be more decisive. They make swift decisions by tuning into their intuition. They’re more likely to take risks, take action, and expose themselves to new opportunities.

“Do it. Easier Done Than Said”

said Lenny Ravich, the humorist and guru of optimism. “People often hide behind the excuse of ’Easier Said than Done’ to avoid taking risks, only to later regret missed opportunities, while the achievements of those who dared prove it to be a testament to the contrary.”

Benjamin Franklin, in his renowned Poor Richard’s Almanack, revived the profound quote: “God helps those who help themselves.” But helping ourselves goes beyond self, because we nourish our soul when we can share our luck.

In the early 1990s, PepsiCo was facing stiff competition in the beverage industry. Indra Nooyi, a rising star who later became the CEO, was brimming with vision. Recognising the need for diversification into healthy food and beverages, she zeroed in on Tropicana, the undisputed king of orange juice. Nooyi led the charge in convincing PepsiCo’s board of directors to acquire Tropicana, despite some initial resistance. She saw Tropicana as a strategic fit that would complement PepsiCo’s existing product lineup and provide a stronger foothold in the health and wellness sector. Her decisiveness came through in the final negotiations. When the acquisition was on the line, Nooyi said, “We are buying it. Period. If we don’t buy it, I’m not sure we have a future in juices.”

Being decisive is often linked to creating one’s own luck, because it involves taking action and making choices that can lead to new opportunities and outcomes. Decisiveness allows individuals to seize moments, make the most of situations, and move forward, even under uncertainty. In contrast, unlucky individuals often have a knack for talking themselves out of opportunities, ignoring serendipity by focusing on reasons to avoid action rather than taking a chance. As Woody Allen succinctly puts it: “80 per cent of success is showing up.”

In conclusion: If you’re reading this, you’re luckier than many. There are at least 7 billion people for whom access to electricity, computing, and the internet is a privilege, one that eludes the countless people worldwide who lack even basics like housing, personal safety, and clean water.

In the tapestry of life, luck isn’t merely a whimsical stroke of chance but can serve you as a skilful embroidery of attitude, action, and awareness.

As Dr Tina Seelig from Stanford shared in her famous TED talk about luck: “Luck is rarely a lightning strike, isolated and dramatic. It’s much more like the wind, blowing constantly. Sometimes it’s calm, and sometimes it blows in gusts, and sometimes it comes from directions that you didn’t even imagine.” Therefore, we need to use our “sails” through tiny behaviours of taking small risks that catch these winds of luck, thereby creating our fortunate circumstances.

“Lucky by Design” elucidates the essence of luck as not just serendipity but the offspring of preparation meeting opportunity. By embracing openness to experiences, listening to intuition, wielding optimism, flexing adaptability, and choosing decisiveness to take risks, we can architect our own fortune.

Benjamin Franklin, in his renowned Poor Richard’s Almanack, revived the profound quote: “God helps those who help themselves.” But helping ourselves goes beyond self, because we nourish our soul when we can share our luck.

Growing up in a loving, modest home, my parents, who were resilient refugee holocaust survivors, instilled in us profound lessons through their hard work and generosity. Despite the need to be prudent, they consistently felt lucky that they were able to give to us and others. Whenever we expressed gratitude to our dad for purchasing something for us, fully aware of the effort and sacrifice behind it, he would respond, “Just bless me that every time I open my wallet, I have something to give to others.”

Embracing this wisdom, let us bolster our fortune by aiding the less fortunate, thereby granting them the opportunity to improve their luck. This act of service not only enhances our lives but also upholds our duty to nurture a better world for all of us.

About the Author

Avi Liran (CSP, MBA) is a Global Chief Delighting Officer, an economist, author, humorist, and energetic motivational and twice TEDx speaker. Avi goes above and beyond to deliver tangible results to organisations, creating delightful customer and employee experiences. As a beacon of Contagious Positivity, he’s celebrated for leading businesses towards profitability and people’s success with a smile.

The post Lucky By Design 5 Clever Attitudes to Tilt Odds in Your Favour appeared first on The European Business Review.

By Stephan Kudyba and Agnel D’Cruz

The power of generative artificial intelligence (GEN AI) has organisations of all types intrigued and clamouring to leverage its functionality to enhance productivity, improve their financial bottom line and maintain market share or possibly achieve a competitive advantage. Increasing the speed and robustness of information assets presents ample opportunities for process applications. However, the jury is still out on a few issues for implementing this technology to achieve truly valuable results. Issues involving the data that must be accessible for large language models (LLMs), verifying the output generated and where to apply the platform to operationalise it for a sustained production environment introduces difficulties in its adoption.

Individuals who understand GEN AI capabilities and best applications in a given area need to collaborate in order to optimise potential roll-outs.

The following steps provide a high-level methodology on how to best approach the implementation of GEN AI to produce effective results that will justify the cost of the strategic initiative.

Throughout the step-wise approach, a major factor must be emphasised, and this is the involvement of expert knowledge of workers at all levels. It is an essential element to achieving success. A phrase that sums up the process is best stated….true value in Generative AI involves a collaborative environment integrating top-down strategy and bottom-up implementation.

1. Establish knowledge transfer to strategic management and SMEs regarding the functionality of GEN AI.

This goes beyond simply presenting generic prompting and content creation but involves prominent process applications.

In other words, knowledge experts within a given organisation must be informed of what GEN AI can actually do. Examples include:

• Devising marketing correspondence for a production environment
• Examining and extracting information from complex and lengthy documents
• Creating computer code and reverseengineering legacy systems
• Creating imagery
• Identifying gaps and new, evolving elements in existing content

Possible GEN AI functionality can help maintain parity with the market given its adoption by competitors. Competitive advantage could be achieved through faster time to market of custom information creation (e.g. combining internal data with that of open source).

2. Conduct collaborative knowledge transfer among informed knowledge experts along with GEN AI technicians (e.g. vendors) to achieve optimal organisational applications.

Knowledge creation is best achieved through an open collaboration of knowledge assets (e.g. SMEs). Individuals who understand GEN AI capabilities and best applications in a given area need to collaborate in order to optimise potential roll-outs. Diverse perspectives and cross-functional input can uncover both routine and innovative opportunities to create value with LLMs.

For example, leverage customer feedback from voice and online sources to enhance product attributes according to consumer (sizing, delivery, price, etc.).

This step not only entails the identification of best areas of GEN AI applications but also should involve estimations of potential returns. In the case above, adjusting product attributes yields increased customer satisfaction, sales, repeat buying, etc. Or in the case of a more routine application (streamlining marketing resources), estimate the expected reduction in labour and the value of re-allocated labour to more productive activities in the firm.

3. Once realistic GEN AI applications that prove tangible value have been identified, cost estimates need to be generated to measure implementation versus potential gains.

Technology And Technology Labour Costs

Data resources that must be accessed by LLMs must be identified, which involves the incorporation of data engineers when considering internal data or the combination of open source and internal data for competitive advantage. These engineers must estimate the time for alignment and optimisation of required data (e.g. cloud-based, internal repository based).

Computer processing costs entailed in LLMs utilisation must be included.

Editing And Verification Costs

True value in Generative AI involves a collaborative environment integrating top-down strategy and bottom-up implementation.

Costs required for the selection of editorial staff time must be initiated. This entails labour resources required to authenticate created content (e.g. safeguarding against adverse, incorrect, outdated content or hallucinations) and potential copyright infringement. This mitigates the risk of costly legal or accountability issues.

Total cost must then be weighed against the expected value created by GEN AI incorporation. The estimation of value must be recognised with variances, given the uncertainty of outcomes achieved, where probabilities should be considered.

4. Value estimation consideration: 

“Reduction” in cost (e.g. savings in a reduction in labour hours through streamlined processes).

“Enhanced” market share through competitive advantage in producing timely custom content. This may include knowledge-enhancing content for internal processes (e.g. adjusting product attributes to consumer needs) or creating custom content of timely information for sources external to the organisations (e.g. customers, suppliers).

“Reduction” in risk of losing market share to competitor activities who adopt GEN AI .

Risk Management is Key

As is the case with many innovative technologies available to the entire market, organisations must not only consider if the functionality is a fit for their organisation but whether they are exposed to loss of market position by competitors effectively adopting it. One of the main advantages of GEN AI is speed, or how quickly content can be created. This speed element includes the ability to generate ideas (identify critical content initially not thought of etc.). Speed also entails vast processing capabilities of information resources to streamline operations. Both of these can increase the exposure of losing market share.

Risk also involves the exposure and accountability of missing adverse content created (e.g. a missed hallucination or simply including inaccurate sources for creating content). This opens exposure to legal ramifications and loss of market share by producing content violating copyright laws, or releasing inaccurate content to customers.

5. Prioritise projects according to value and risk reduction.

After consideration of the previous steps, organisations must answer a major question. Is the project really worth it?

This considers the company’s risk profile and cost/value analysis. If the answer is YES, then move on.

It is time to select the application that best fits the organisation’s situation. What this involves is an examination of some previous steps. Prioritisation of a GEN AI implementation should focus on the following elements:

1. How exposed is the company to loss of market share by not taking action?
2. How significant is the process that will be augmented with GEN AI (will the implementation make a real difference to its performance?)

To illustrate these points, consider a hypothetical case in the insurance industry.

The application of GEN AI may augment an insurance provider’s ability to identify the elements required for custom coverage to an entity (individual, group, etc.) in a timelier manner than industry standards.

The ability to provide a quote for custom coverage faster than the industry norms may increase market share, given the augmentation of the customer experience. The risk exposure of not moving on GEN AI may be high. However, an additional risk that must be considered is that of devising coverage elements with inaccurate information.

6. The final stage is the roll-out of GEN AI for the application.

At this stage, data sources should be aligned, LLMs trained through the engagement of data scientists and prompters, and SMEs should be in place to measure accuracy. An overall assessment of the entire performance of the platform must take place, where the critical elements to focus on are the accuracy of content and time to production. The new process must evolve regarding new data sources and LLM accuracy.

About the Authors

Stephan Kudyba is a professor of analytics and information systems at the Martin Tuchman School of Business, New Jersey Institute of Technology. He has held senior management positions at prominent organisations and has been a researcher, professor, and practitioner of AI applications in business for over 20 years. Email: SKudybs@gmx.com

Agnel J D’Cruz is a seasoned data professional who is currently a principal of data strategy and partnerships at ZoomInfo. Agnel has been published by HBR for his outstanding work at Honeywell International where he led large-scale data and AI implementations.

The post Strategic Excellence: Steps to Maximise ROI in GEN AI Implementations appeared first on The European Business Review.

By Louise Muhdi

Companies are starting to understand why it is important to cultivate curiosity among their workforce. Yet, only a few possess a good grasp on how to activate, embed, and leverage it throughout the organisation. In this article, we propose a practical, human-centric approach to help managers design for, lead with, and operationalise curiosity in the workplace.

How many times have you heard recently of an organisation or a process that is due for reimagining, rebuilding, or future-proofing? We live in a time where organisational wisdom has shifted from a company’s sum of experience and expertise to a willingness to open up, to be flexible, and to play with the boundaries of how we see the world and our place in it. Underpinning this pursuit of how things could be and possibly will be is curiosity — organisational and collective, as well as individual.

Indeed, curiosity is seeing a renaissance, particularly across innovation-focused industries such as pharma, tech, and media. Corporations including Merck, Nike, Disney, Target, GE, NASA, Novartis, Facebook, the LEGO Group, Microsoft, and Dell have recognised and established curiosity as a key component in their corporate branding. For a company to be seen as curious has become a ticket to higher quality of investor relations, recruitment, and talent retention.

In writing this article, I drew on a long-term dialogue with corporate champions of curiosity in the workplace, as well as discussions with executive education programme participants across industries. I coupled their input with years of experience in conducting experimental, action-oriented problem-solving modules and interventions for large businesses.

For a company to be seen as curious has become a ticket to higher quality of investor relations, recruitment, and talent retention.

Based on this ongoing research, I propose that unlocking an organisation’s curiosity can deliver a host of fundamental benefits. In this age of disruption and large-scale organisational transformations, it can enable rapid adaptability. Curiosity can also be that key ingredient that wards off a return to complacency and protects employees from transformation fatigue and burnout. On the innovation front, an outlook of curiosity about others will spur collaboration within ecosystems as gateways to value creation and solving complex challenges.

Nonetheless, there are several factors at play that make embracing curiosity an uphill battle for companies. To start with, we have yet to reach a standard definition of what curiosity in the workplace looks like. In its place, misconceptions abound: of curiosity as a distraction, unless demonstrated by those at the very top; a general willingness to ask questions but not much more than that; or a quality that only comes in handy in creative occupations like product design.

Meanwhile, businesses’ traditional reliance on experts means that curiosity goes into a decline the minute we have convinced ourselves that we have all the in-house expertise we need. As a result, what could be a critical business skill and a key driver of growth, innovation, problem-solving, stronger leadership, and rapid adaptability in the workplace is often regarded as a nice-to-have soft skill.

Operationalising curiosity in your organisation: Where to start

Curiosity is an innate human quality. Researchers have pointed out that cognitive needs are just as fundamental as physiological and social needs. In other words, just as we cannot go without food, in many situations we cannot bear not to know what’s out there, who we are dealing with, what happens next. See how skilfully this instinct has been co-opted and ritualised by social media companies. It is what makes us click and swipe and scroll through the mass of unpredictability that is online content.

The difficult part is that curiosity as a concept tends to defy a firm grasp. Its emotional roots make it prone to outbursts which flare up one minute and dissipate the next. The key challenge has to do with connecting these into a more malleable and predictable continuum. Fortunately, we can take inspiration from industry frontrunners who have made heavy bets on transmuting the power of being curious into a tangible value, process, methodology, and organising principle. In dozens of interviews with talented executives, I have identified the following design principles^.

1. Nurturing the mindsets is great – but your best bet is to actively shape behaviours

Many executives labour under the assumption that simply by talking about curiosity or writing it into vision and mission statements, it will trickle down to form a part of employees’ day-to-day work. The reality is, of course, much more complex and stubbornly non-linear. Neither is building curiosity about “fixing” people in order to make them more curious, or simply encouraging them to ask questions, no matter how probing and incisive.

Nurturing curiosity requires a steady infusion of new, on-the-job tasks, challenges, experiences and, at times, even introducing a healthy degree of controlled instability.

Curiosity is anchored in what scientists call neuroplasticity, the brain’s ability to reorganise and rewire itself in response to learning, experiences, and environmental influences. “Action” is the operative word in this context. It is predominantly as a result of action and movement that the brain responds to challenges and creates new neural pathways. Nurturing curiosity requires a steady infusion of new, on-the-job tasks, challenges, experiences and, at times, even introducing a healthy degree of controlled instability.

Therefore, a simple act of physically moving things and people around can be a good start.

Branding and community expert Patrick Hanlon described it as follows: Scramble the desks, force people to regroup and continually rewire their brains to know more. Encourage lateral or associative thinking by rubbing together different groups, cultures, skill sets, and department silos.¹

An online (virtual) intervention guarantees a wide reach against a low cost. Norway’s state-owned renewable energy player Statkraft has learned that short-burst, online collaborative problem-solving modules can stretch its workers’ traditional engineering mindset.²  DBS bank in Singapore runs regular hackathons where innovation managers share concepts and practices of innovation with their colleagues. For your company, choose whatever mix of social and tech-enabled formats is likely to grab your employees’ attention and motivation.

Stimulating curious behaviours can also be a gateway to collective learning and inclusivity. Much too often, the way companies traditionally relied on experts and expert knowledge has kept workers “in their place” and reluctant to demonstrate natural curiosity beyond their own expertise. In today’s age of uncertainty, where advances in technology have nearly obliterated the idea of established expertise, structured curiosity exercises and interventions can place people in a zone where there is something new to be learned and where their input is desired, acknowledged, and rewarded.

Managers at Merck have shared with us stories of lab technicians who were, possibly for the first time ever, emboldened to speak up and share insights that proved essential for rethinking and redesigning a specific innovation process. The stories reflect the reality of the mainstream workplace where bureaucracy and hierarchy have been corrosive of curiosity. In the 2018 edition of Merck’s “State of Curiosity” survey, 64 per cent of the 3,000 respondents reported grappling with barriers to curiosity and innovation in the working environment, such as a lack of communication with colleagues outside of their own team and working under strict supervision.³

In many organisations, teams approach problem solving by brainstorming, typically starting with a clean slate. Merck employees learned that there was a better way. By tapping into the diversity of a team’s potentials and behaviours with regard to curiosity, their teams’ interactions turned out to be more creative and productive. In particular, they realised that curiosity could give creativity an organic boost by linking different ideas better, i.e., using a colleague’s idea as a stepping stone to the next idea — “Yes, and…” rather than “Yes, but…”.

Amid complex transformations, employees are told to have trust in the big plan – trust that the change will pan out well and bring the organisation to the desired business outcomes. This is where behaviours that build on curiosity can go a long way. People believe because they have seen outcomes of their new behaviours. They also observe and mimic others. Actions coalesce into habits and are eventually automated. When it comes to curiosity, the magic of action is that it often precedes motivation. Pedro Guerrero, Senior Global Project Manager for Merck Life Science and a participant in Merck’s Activate Curiosity pilot programme, observed: People’s motivation received a big boost. They realised that the company was walking the talk. As if saying, we want to be innovative, we are a curious company, and we want to invite you and give you the opportunity as well as the tools to contribute.

2. Curiosity needs to be prioritised and architected into your organisation’s systems and processes

Channelling curiosity in productive ways requires what most channelling does: dedicated dimensions of time and space. One-time events make for good publicity. But connecting curious behaviours in a deliberate way, through team interactions in controlled environments, around meaningful work, and repeating these over time can yield so much more. Companies can use it to construct a workable long-term framework of continuous learning, collaboration, and innovation. In the words of Christine Blum-Heuser, Senior Manager for Brand Communication at Merck, who spearheaded several of the company’s initiatives in this space: Instead of something vague and inchoate like a state of mind, we soon started to think of curiosity as a process — and from there on, as a framework, not only for solving problems but for effectively navigating the entire process of exploration, R&D, and ultimately innovation. We could consciously channel curiosity to create something new and impactful in the organisation.

Processes and mechanisms that enhance curiosity include personal ownership of projects, using instruments of one’s choice to accomplish tasks, and having sufficient time for exploration.

When Merck launched its Activate Curiosity programme in 2019, it ran a six-month pilot. It involved 133 people in 10 groups – a mix of intact and cross-functional as well as virtual teams representing a diversity of Merck’s business segments and key markets. Team members completed a “State of Curiosity” survey (similar to the 2018 and 2020 surveys) in order to understand their curiosity profiles and the curiosity dimensions they could improve upon. Each group was assigned a business innovation challenge to work on.

Crucially, extrapolating from the pilot, Merck succeeded in instituting specific behaviours and routines into its “new normal” ways of working. Among these, curiosity serves as the underpinning of Merck’s key behaviours such as discuss, disagree openly, decide, deliver (“4Ds”), which have been putting down roots as “the way we do things around here” – in other words, the unique Merck culture. Furthermore, staff are actively encouraged to call out actions and behaviours that go against the grain of these practices.

As a shortcut, think about embedding curiosity and the related behaviours in the standard levers of organisational change (see Figure). On the people front, companies like Roche have gone to great lengths to install leaders who exhibited systems thinking and a holistic perspective on healthcare delivery in local markets. These executives see themselves as connectors (Roche talks about Visionaries, Architects, Coaches, and Catalysts), rather than leaders in the hierarchical sense. Similarly, recruiting young people can be a powerful conduit for infusing curiosity into the company. Staff surveys conducted at Merck showed that young hires were by far the most curious cohort within the workforce.

Processes and mechanisms that enhance curiosity include personal ownership of projects, using instruments of one’s choice to accomplish tasks, and having sufficient time for exploration. Likewise, measuring and rewarding behaviours and outcomes linked to curiosity can be done in simple ways. You could start tracking the percentage of staff that come forward with new ideas. Indirect indicators like staff engagement and satisfaction can also be tweaked to gauge whether employees are finding outlets for their curiosity in day-to-day interactions and processes. Additionally, companies that have been the leaders in curiosity have encouraged their people managers to pick a specific behaviour underpinned by curiosity, complete related tasks throughout the year, and ground them in solid KPIs. Top leadership at Novartis has been explicit about setting a goal of people spending 5 per cent of their time or 100 hours a year on learning, curiosity, and development.⁴

3. Curiosity is contagious: Empowering people through repeated practices

In any type of short-burst problem-solving intervention, game, or other team activity, curiosity — and, by extension, trust in one’s collaborators — is typically heightened within a couple of hours. People are empowered to speak up, make comments, and share observations. Working against time, ramping up one’s concentration, and focusing on solving a real-world problem; in tandem, these parameters work like a crucible that melts away hierarchy along with personal insecurities, rivalries, and office politics.

The systematic approach can be enriched with informal, loosely structured experiences. These are important, because the curiosity muscle will atrophy without use. Practise, repeat, keep experimenting and expanding through small steps — ideally in an environment of psychological safety where team members obtain a sense of connection, develop deep trust of their peers’ intentions, become comfortable with taking risks, and learn to move on constructively from things that didn’t pan out.

By the people, for the people: Practical outcomes for companies that get it right

Enhancing curiosity and putting it to work won’t turn every employee into a systems thinker and innovator. But it will give people a voice, help them better understand their own roles, and provide them with a common language as a foundation for holding each other accountable.

Encouraged to think outside their own narrow frame of reference, they become more exploratory and future-oriented. As employees’ trust in the process is strengthened, they obtain a real feel for “this is a company where I can develop myself, where I have the freedom to experiment and learn. I can make a difference. I get to see results.” This makes organisational transformations more human-centric and sustainable in the long term.

The sense of engagement works both ways. Our studies show that managers who have experimented with curiosity become curious about their own workforce. They are keen to learn about what drives and what inhibits workers’ curiosity. Renee Connolly, Merck’s Chief Diversity, Equity & Inclusion Officer and Head of Innovation HR Engagement & Inclusion, reflected: We find that consistently and systematically feeding the curiosity sentiment has provided us with better inside analysis of what makes our employees tick, flourish, feel energised, do their best work, as well as which of the world’s regions are the most curious. DE&I metrics tend to improve significantly. As an employer, we now have a better understanding of, for instance, what kind of benefits are the most effective in making our employees want to be here and want to succeed.

Embracing and role-modelling curiosity helps leaders evolve and adapt their leadership styles. To the rest of your organisation, it sends a signal that the best way to tackle real-world problems is to get one’s hands dirty. Action also solves the conundrum of connecting the fresh spark of curiosity to longer-term projects that fuel transformation — team learning, product development, problem solving, staff recruitment and onboarding. When properly constructed and channelled, curiosity minimises the trade-offs between learning and performance. It can be the driving force as well as the accelerator of developing a culture of adaptability and agility.

About the Author

Dr. Louise Muhdi, PhD, a distinguished Professor of Innovation and Strategy at IMD Business School, is renowned as an author and advisor. Focused on empowering executives across industries, she accelerates transformation, fostering positive change at all organisational levels with her expertise and guidance.

References

1. Hanlon, P. (2013). Curiosity Didn’t Kill The Cat, It Created The Mousetrap. Forbes. Available at: https://www.forbes.com/sites/patrickhanlon/2013/05/06/curiosity-didnt-kill-the-cat-it-created-the-mousetrap/ [Accessed 15 Feb. 2024].

2. Muhdi, L. and Králik, M. 2023. “Statkraft: Building a culture of collaboration in a fast-growing state-owned company”. Case study. IMD-7-2432. IMD International.

3. Merck. “State of Curiosity Report 2018”. Available at: https://www.merckgroup.com/en/company/curiosity/curiosity-report.html#:~:text=The%20Merck%202018%20State%20of,D. [Accessed 10 Feb. 2024].

4. Green, D. (2020). How Novartis Promotes Learning Curiosity to Drive Business Value (Interview with Simon Brown). Available at: https://www.myhrfuture.com/digital-hr-leaders-podcast/2020/10/6/how-novartis-promotes-learning-curiosity-to-drive-business-value [Accessed 10 Feb. 2024].

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The demand for green skills in Europe is surging, but there’s currently a shortage of talent to meet it. Román Campa, CEO of Adevinta Spain and Head of Real Estate & Emerging Verticals at Adevinta, discusses below how AI is the key to the puzzle, offering solutions that can elevate the recruitment process for both job seekers and employers. 

As the need to transition to more sustainable ways of living and doing business has become more urgent, the demand for green skills has accelerated across Europe.   

With the green economy requiring roles ranging from engineering and building to science, tech, and operational management, more employers than ever are jostling to track down top talent with the experience to meet their needs.   

But with an estimated 18 million people needing to be reskilled across the continent for it to reach its climate goals, there’s a limited pool of candidates to draw from. It’s an unprecedented problem that endangers Europe’s ability to meet net zero targets. 

Overcoming the shortfall in the long-term calls for concerted action from policymakers and large-scale funding. Whilst corporates and governments alike work towards these objectives, the jobs market is under pressure to innovate to make best use of the talent available.  

Enter AI. It has the potential to be transformative for the recruitment and job-search industry over the next few years, and its value to the sector will grow exponentially as it becomes more advanced.   

However, with increased innovation comes increased risk. As artificial intelligence evolves, technology platforms must ensure that AI is used both ethically and responsibly, with humans remaining firmly in the driving seat when it comes to decision-making. 

In the here and now, the recruitment industry is largely operating with the help of “still” non-autonomous AI-assisted technology, which already offers game-changing tools for both employers and candidates to elevate the recruitment process. 

Empowering employers with AI   

By harnessing the power of AI, companies can overcome pain points in the recruitment process and take their talent hunting to the next level. Online job marketplaces are pivotal to this process, facilitating the connection between candidates and employers. Add AI into the equation and you have a formidable combination.    

So, how can AI help? AI-powered assessment tools implemented on jobs marketplaces can now be used to guide employers on the suitability of potential matches, calculating a suitability profile for a candidate using a range of factors — such as the years of sector experience they have, their location, academic credentials, relevant green skills, and the languages they speak. Recruiters can then use the information generated to help them filter applicants according to a job description.   

And recent leaps forward in generative AI mean recruiters at larger organisations can do away with the sometimes tedious task of writing vast numbers of job descriptions. With just a few thoughtful and well-selected prompts, the technology can generate these descriptions itself, significantly speeding up the recruitment process. 

Naturally, ethics and transparency must remain front and centre in the utilisation of these tools to avoid introducing unnecessary bias. When AI is used to profile and score a candidate’s suitability, for example, information such as gender, race, or age, must be excluded, and it’s critical that the process by which the result has been calculated is always clear to the user. With these rules adhered to by jobs marketplaces and boards, companies and job seekers alike stand to benefit.   

Given that since 2021, EU countries have witnessed an increase of 12% in labour market vacancies for green jobs, these tools will fast prove invaluable, particularly for large corporates with blossoming sustainability departments to fill.   

Empowering candidates with AI  

AI is also a game changer for jobseekers. Candidates want to better understand whether a job is a good fit for them before they apply, and the same suitability profile that’s created by AI can help them just as much as it does employers. By accessing the information it generates, candidates can better understand whether a job is a good fit for them before they apply.   

In fact, most AI tools can provide a two-way street. As well as enabling companies to produce job descriptions more efficiently, generative AI technology can also help candidates to make their job applications better. Inputting their skills and career history, job hunters can generate a description of their experience that they can then edit, refine and personalise.  

But these simple efficiencies are only the tip of the iceberg. As jobseekers themselves become more comfortable with using AI-enabled functions when job searching, they will find themselves able to enjoy increasingly more sophisticated advantages. For example, AI can be used to analyse data from across job postings and resumes — to give candidates insight into emerging trends in the green economy. This information can show how employers’ skills requirements are evolving, meaning candidates can identify the green skills that are in high demand and upskill or tailor their applications accordingly. In the near future, these kinds of useful insights will become more and more widely accessible. 

Future-proofing the green skills talent market  

According to data from the World Economic Forum, Gen Z will make up 27% of the global workforce by 2025 — with this percentage only set to grow. For a generation that has zero tolerance for friction and lofty expectations for seamless user experience, AI technologies are a welcome addition to the job searching experience and soon set to become commonplace.  

But whilst Gen Z are widely considered to be the most climate conscious generation, this alone doesn’t present an easy fix for the green skills gap. Employers and jobs marketplaces alike have a crucial role to play in showcasing the opportunities available in green careers, and indirectly influencing junior jobseekers to pursue training in green skills — and any tools able to provide efficiencies in this respect will only aid the achievement of this objective.   

Looking to the future, the growing demand for green skills in Europe clearly calls for urgent action. Rising to the challenge will require collaboration from policymakers, the corporate sector and the talent industry, and AI is already proving pivotal in helping both employers and job seekers to navigate the green jobs market more efficiently. By integrating AI solutions Jobs marketplaces – as critical matchmakers – can help make a material impact on the green agenda. It’s by embracing AI, rather than fearing it, that Europe can accelerate its progress towards net zero. 

About the Author

Román Campa is the CEO of Adevinta Spain and Head of Real Estate & Emerging Verticals at Adevinta. He previously led the Finance, Strategy and Growth area of ​​Adevinta in Spain and was General Director of InfoJobs. 10 years before coming to Adevinta, he worked at the consulting firm McKinsey, an experience that helped him understand the importance of commitment and transparency.  

He has a bachelor’s degree in business administration from ESADE Business School and a master’s degree from the MIT Sloan School of Management. His great strategic and analytical capacity stands out. He is passionate about connecting people with data and throughout his career he has specialised in helping companies adapt to the demands of the digital economy, creating value-added projects. 

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By Jonathan Trevor and Kazuhiro Asakawa

In the first of a two-part series, we explore how firms are reaping the benefits of leveraging a network of external resources for enhanced performance and innovation, but only when their organisational ecosystems are strategically aligned and fit for purpose.

Managing organisations to be highly aligned and capable of implementing their chosen strategy is an age-old challenge. It has only become harder now that many firms and public sector organisations embrace ecosystem principles in their organisational design.

Because they are more open, flexible, and integrated than the industrial-age hierarchy, ecosystem-based organisations can leverage external resources (think partners) to offer customers enhanced value upstream (think novel product and service development) and downstream (think flexible delivery) than they ever could be if relying upon internal resources alone.¹ However, published research indicates that up to 75% of ecosystems are considered failures.² The leaders we spoke to acknowledge the considerable potential of ecosystem thinking for their businesses but also expressed concern over the complexity of organising along such lines.

We studied a sample of leading international and Japanese firms with a stated ecosystem strategy to understand how they strategically align their organisational ecosystems to be fit for purpose and high performing. Strategic alignment, in this context, refers to the careful arrangement of the different components of an organisational ecosystem — from its purpose (its raison d’etre) to its strategy and structure — required to leverage external resources for strategic value successfully.³ Each component represents a strategic choice. Ecosystem leaders must select from various options the one that suits their circumstances best. All components should be highly aligned, ideally.

Whether to create or participate in ecosystems, our study helps managers work through these critical strategic choices and improve their chances of success. First, we organise ecosystem purpose, strategy, and structure into first, second, and third-order strategic choices. Second, we present a practical framework to help ecosystem leaders choose between their various options at each stage. The first and second-order choices are the focus of this article, Part A. Third-order choices and the unique implementation challenges presented by organisational ecosystems are the focus of a second linked article, Part B.

Good choices establish an organisational eco-system (ecosystem) as a functioning equilibrium capable of high performance, regardless of field. Poor choices create misalignment and dysfunction, perhaps explaining the reported high failure rate.

First Order Choice – For What Purpose?

Firms within our study sought to leverage external resources for one or more of the following three strategic reasons:

1. Enhanced technical innovation,
2. Enhanced customer offerings in the form of product and service design and delivery, and
3. Enhanced channels to market. Broadly, these correspond to upstream and downstream innovation.

Consider the example of blue-chip multinational IBM. IBM has had a long journey with its ecosystem, now considered a single business division and its fastest growing. As part of a wider corporate realignment, IBM renewed its emphasis on its partner ecosystem and Kate Woolley to provide a single point of leadership. IBM also doubled down on technology and consulting services, spinning out its managed service business to form Kyndryl, arguably to allow it to focus on its ecosystem and to remove managed services as a business and avoid causing tension with prospective partners.

The IBM ecosystem serves three key purposes centred around exploiting external resources to achieve strategic outcomes that would not be possible by relying upon internal resources alone. These include partners selling IBM technology (via a channel business), partners building on or with IBM technology (project-based partnerships), and strategic service partners who use IBM technology to build a bespoke managed service solution for their clients or to enhance their existing service offerings. In other words, IBM has one ecosystem operating under one leader but actively pursues three different ecosystem strategies simultaneously.

For a long time, IBM has operated an external network in the form of its channel business (think reseller network). Comprising thousands of vendors, the channel business aims to provide an efficient channel to market for IBM technology products. As part of a broader corporate realignment, IBM has doubled down on creating strategic partnerships with other industry-leading firms to pool resources and offer new and enhanced services to the market. Woolley says, “I think of partner ecosystems as one of the most powerful forces in technology. That’s where companies come together to solve the toughest business problems”.⁴

Or consider the example of the Development Bank of Japan (DBJ), a wholly-owned subsidiary of the Japanese Ministry of Finance. Created immediately post-World War II to facilitate Japan’s economic and social reconstruction, DBJ occupies a unique role in Japanese society, and its remit extends internationally, with offices in London, Singapore, Beijing, and New York. Through loans, investment, asset management, and advisory services, DBJ supports the development of nationally important industries, infrastructure, technologies, and social concerns. For instance, during COVID-19 and the dramatic decrease in travel and the potential collapse of the inbound tourism sector, DBJ provided emergency loans to small and large businesses to help them weather the storm, even in cases where it was unprofitable.

In our experience, ecosystems are often referred to generically under a single concept. A better way is to recognise that there are different types of ecosystems, each representing a distinctive strategy with unique implementation challenges.

In the long term, a key role of DBJ’s financial experts is to create and support ecosystems between different industry actors to encourage economic development. For example, DBJ convenes various aviation industry players, from airlines, unions, manufacturers, airports, and regulators, to transform the sector to be more sustainable in line with stated national targets for compliance with UN Sustainability Development Goals. DBJ represents a focal organisation, sitting atop an ecosystem of potentially disparate industry actors and encouraging collective action to transform an entire sector to be more environmentally sustainable through aligned incentives, reduced information asymmetry, technological collaboration, and collective action.

However, Japan has a tradition of embracing ecosystem principles in all sectors. Shiseido, a leading Japanese cosmetic company, was a pioneer among the Japanese firms in creating its ecosystem back in the 1990s to tap into state-of-the-art French fragrance knowledge through informal collaboration with fragrance experts in France.⁵

Whatever the reason for adopting ecosystem principles, it should be clear and compelling to all concerned, including (perhaps especially) external stakeholders, partners and clients. Every year, IBM invests considerably in enhancing the value of its relationships and networks across its entire ecosystem to create alignment with its purpose. Its primary vehicle is an event, ‘‘IBM Think’’. Before COVID-19, the IBM Think conference hosted audiences of 40,000 people in one location annually. Today, it is a hybrid event, including a smaller global in-person event for 5,000 invited employees, partners, clients, and even competitors; and a ‘‘Think on Tour’’ series of events in key geographies designed to bring “IBM, partners and clients together locally in the market where they do business.”

IBM Think creates a ‘‘melting pot’’ environment for its stakeholders to engage with the technology company and its upstream and downstream ecosystems, including innovation partners, strategic partners, and an extensive reseller network. According to Simon Meredith, Principal in Strategic Partnerships at IBM, the “Assumption of protectiveness is misplaced”, even with competitors, because the explicit purpose is to engage, learn, and co-create. Therefore, trust is essential in an ecosystem working to develop strategically valuable social capital, reduce the transaction costs of collaborating with external parties at scale, and mitigate the risk of conflicting interests.

Consider four things about your own organization: Does relying upon internal resources, while simpler, represent a capability trap? Do you need to leverage external resources to be competitive? If so, for what purpose? Is it to develop a network as an additional marketing channel(s) (i.e., primarily a sales network)? Or is it to capture knowledge for upstream product and service innovation, as in the case of Shiseido? Or is it to develop downstream capability to deliver enhanced products and services to your customers and clients, such as IBM strategic partnerships? Of course, it can be all three.

Second Order Choice — Which Ecosystem Strategy?

Once an organisation has committed to embracing ecosystem principles, the second-order management challenge is to choose which ecosystem strategy represents the best option for going about doing so. In our experience, ecosystems are often referred to generically under a single concept. A better way is to recognise that there are different types of ecosystems, each representing a distinctive strategy with unique implementation challenges.

Within our sample of companies and wider research, we identified four principal ecosystem strategies according to their openness to external actors and whether they were vertically or horizontally integrated. A critical risk is that failing to recognise these different types may lead managers to sleepwalk into creating, maintaining, or participating in ecosystems that are suitable for their purposes.

Closed And Vertically Integrated Ecosystems

Are as the name would suggest, a designated group of specialised partnering organisations operating within a closed network under the supervision of a dominant focal organisation. The focal organisation appoints constituent members and coordinates efforts against explicitly mandated targets and standards. The purpose is to ensure efficient performance delivery against required standards in efficient and predictable ways.

The McDonald’s supply chain is a good example of this type of ecosystem in action. Serving over 70 million customers worldwide daily, it is vertically integrated into every link of its supply chain to ensure it efficiently matches supply with demand. Whilst there are thousands of third-party suppliers supporting McDonald’s operations around the world, the firm relies upon a closed network of several long-standing partnerships with key suppliers. For example, the Martin-Brower Company has formed a key part of the US supply chain, delivering supplies to all of McDonald’s 15,000 restaurant locations in North America for decades.⁶

Sharp’s “black box” strategy in the 1990s also falls into this category. The Japanese consumer electronics firm enjoyed a significant competitive advantage in LCD-TFT technology in the 1990s by internalising the production of its LCD-TFT TV and the LCD-TFT panels, including partner operations, inside the firm on its huge production site in Kameyama, Mie-Prefecture. Sharp created its own closed and vertically integrated ecosystem of technical innovation and manufacturing, which was designed to isolate itself from other rival firms to avoid technology leakage.⁷ Regardless of physical footprint, this type of “closed” ecosystem is well established, and partnerships are often long-lived and highly stable.

Closed And Horizontally Integrated Ecosystems

Focus closely on membership of their ecosystem but encourage many more horizontal connections between the focal organisation and network members and between network members directly. The role of the focal organisation is less supervisory, and the nature of partnering is less transactional. It is more about nourishing connections between ecosystem partners for upstream and downstream innovation purposes.

An early example of this type of ecosystem strategy is the fast-moving consumer goods company, Nestle. Nestle has pursued a strategy of acquiring complementary firms as well as setting up research and development centres worldwide to act as dispersed “antennas” to sense and source local market knowledge and creativity. Acting as a focal point for this distributed network is Nestle’s R&D coordination unit, which coordinates, exchanges, and encodes locally acquired new knowledge in its product innovation and then pushes new products out to sales and marketing functions in those same geographically dispersed end markets.⁸

One of the interesting challenges with closed horizontal ecosystems is that they may involve partnering between companies that might previously have been — and still can be — competitors. Such ‘‘Frenemy’’ (i.e., friends who are also enemies) arrangements are common in ARM (described later) and its close and long-term manufacturing relationship with its biggest competitor, Intel.

IBM’s key strategic partners include deep commercial collaborations with hyperscalers (think Amazon Web Services), infrastructure partners, and global consultancies such as Ernst & Young. All strategic partnerships operate under a single internal organisational structure, the IBM Ecosystem, and one leader, Woolley. To reduce competitive conflicts and greater freedom for ecosystem engagement, IBM divested itself of its managed infrastructure business, Kindryl, as mentioned previously. A second challenge is to find the right partners and invest in the resources necessary to form and capitalise upon productive relationships.

Open And Vertically Integrated Ecosystems

Are much more open than their closed-vertical counterparts, resembling marketplaces more than supply chains. The focal organisation acting as a platform maintains a dominant supervisory role within the ecosystem, but membership is much more open and scalable, with potentially many thousands of external actors interacting with the focal organisation and its customer, if not with each other.

One of the interesting challenges with closed horizontal ecosystems is that they may involve partnering between companies that might previously have been — and still can be — competitors.

The Apple App Store is an obvious example. The purpose is to draw upon the creative resources of many thousands of developers to offer Apple product users enhanced choice over applications available through the App Store and through which they can personalise the functionality of what would otherwise be a standardised (albeit smart) device. Apple, and Google, its main rival, control over 95% of the app store market outside of China, worth an estimated $6.3 trillion.⁹ Other platform firms, from Uber to the Amazon marketplace, also use digital platform technology to efficiently match supply (from many thousands of drivers or sellers, respectively) and demand from customers.

In the internal context, such arrangements are prevalent in the form of global value chains (GVCs), in which the different stages of production activities are performed across different countries, each of which may be its own supporting ecosystem made up of local partners, suppliers, and innovators, to match local market customer requirements. Firms often disperse value chain activities ranging from R&D, design, production, and marketing for this purpose.¹⁰

Extending the logic of openness even further, some ecosystems are highly decentralised and geared around tapping into the wisdom of the crowd. Consider the example of the Linux community, with its many thousands of contributors. Being a crowd-sourced development, the Linux computer operation system relies upon individual developers to contribute their time and expertise to a common endeavour for free. The incentive is to create something new, and participation is voluntary and collaborative. In that sense, Linux is open to a virtually unlimited external talent pool.

Compared with the first two “closed” types, this more open type of ecosystem is a recent strategy, and the subject of considerable focus, especially in terms of the digital transformation agenda.

Open And Horizontally Integrated Ecosystems

Are characterised by their openness to many diverse network actors and the horizontal nature of their connection. Horizontal Open ecosystems resemble communities, where the focal organisation provides the environment for the discretionary effort of the many associated partnering individuals and organisations to lead upstream and downstream innovation within a field of technology or industry.

Consider the example of the technology company ARM Holdings. ARM chips power 80% of the world’s smart devices, everything from phones to tablets to the emerging Internet of Things. Its strength is its ability to harness the power of its network resources, in the form of knowledge, human capital, technological expertise, and innovation capability, to design the most powerful and efficient (think low power consumption) chips available to the market. And yet, ARM employs only 7,500 people, mostly located at its headquarters in Cambridge, UK, where it originally started life in a converted farm building in the ‘‘Silicon Fen’’ cluster of high-tech start-ups around Cambridge University. But despite its modest headcount, ARM has over 20,000 external partners within its global innovation ecosystem.¹¹

The same principles can apply but in a physical location. Woven City is the Toyota Motor Company’s (Toyota) purpose-built innovation community located in the city of Susono near Mt Fuji, Japan. Analogous to Silicon Valley in the US or Silicon ‘‘Fen’’ in the UK, of which ARM is a product, Woven City is, by design, an open ecosystem integrating the delegated efforts of many thousands of partnering companies. They operate side by side, physically and virtually, to further Toyota’s goal of realising radical new mobility technologies.

Each form of ecosystem must be structured appropriately if it is to perform its strategic function capably as intended.

Sosei Group Corporation is a holding company of biopharmaceutical companies specialising in drug development. Sosei Group enters into license agreements primarily with US, EU, and Japanese companies to market the licensed drugs in Japan and find alternative usage for such drugs.  Sosei, in its foundation era, chose to locate itself in the UK to engage in R&D collaboration with local universities and venture firms to tap into the innovation ecosystem in the UK.¹² Similarly, Takeda, a leading Japanese pharma, adopted this type of ecosystem by deciding to engage in drug discovery through open partnerships worldwide.¹³

IBM’s “Collaboratory” strategy also falls into this type of ecosystem strategy, for the company engaged in open innovation even without setting up its own R&D labs through active collaboration with universities, government, and commercial partners within host country ecosystems. Open and horizontal ecosystems represent the most recent and the most complex type to emerge in theory and practice.

Summary

Each of the four ecosystem strategies presented here is distinctive in its own right. Each presents managers with unique strategic advantages. So, which is best? It depends upon requirements, of course. Consider, in your case, how open and integrated you need your ecosystem(s) to be.

If your purpose is to develop an efficient supply chain, a closed and vertical strategy may be most appropriate. Or, if it is to create a platform to fuel a market around your product or service, open and vertically integrated is the best option. Or, if it is to create an innovation community highly aligned with your product development cycle, a select group of highly integrated strategic partnerships might be best.

Whichever ecosystem strategy is chosen, each also presents managers with unique implementation challenges. Each form of ecosystem must be structured appropriately if it is to perform its strategic function capably as intended. Designing an ecosystem structure to be fit for purpose is an additional — and critical — alignment consideration and the focus of Part B of this series: Designing Organisational Ecosystems & Overcoming Barriers to Implementation.

About the Authors

Jonathan Trevor is a Professor of Management Practice at Oxford Said Business School, University of Oxford, UK.

Kazuhiro Asakawa is a Professor of Global Innovation Management at Keio University Graduate School of Business Administration, Keio University, Japan.

References:

1. Williamson, P. J., & De Meyer, A. (2012). Ecosystem Advantage: How to Successfully Harness the Power of Partners. California Management Review, 55(1), 24-46.

2. Reeves, M., Lotan, H., Legrand, J., & Jacobides, M. G. (2019). How Business Ecosystems Rise (and often fall). MIT Sloan Management Review, 60(4), 1-6.,

3. Trevor, J. & Varcoe, B., (2017). How Aligned is Your Organization? Harvard Business Review. 7 February. Harvard Business School Publishing.

4. https://www.ibm.com/blog/qa_kate_woolley/

5. Asakawa, K, & Doz, Y. (2002) Shiseido France 1998. INSEAD Case #4934.

6. https://www.allthingssupplychain.com/the-amazing-supply-chain-of-mcdonalds/

7. Murtha, T., Lenway, S. & Hart, J. (2001) Managing New Industry Creation: Global Knowledge Formation and Entrepreneurship in High Technology. Stanford Business Books.

8. DeMeyer, A. (2003) Nestle S.A., INSEAD Case, #2692.

9. https://www.businessofapps.com/data/app-stores/

10. https://www.oecd.org/industry/global-value-chains/

11. Trevor, J. (2022). Re: Align: A Leadership Blueprint for Overcoming Disruption and Improving Performance. Bloomsbury Publishing.

12. Asakawa, K. & Osada, E. (2003) Sosei (A) & (B), Keio Business School Case, #20030712J.

13. Korine, H. & Asakawa, K. (2019) Takeda: The Governance of Strategic Transformation (A) & (B), London Business School Case. #LBD Ref: CS-18-24/25; HBP: LBS222/223.

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By Peter Lorange and Karin Mugnaini

In business, as in a host of other contexts, timing is everything. While sensing the optimum moment for a given course of action may require more art than science, we can at least be aware of the indicators that we should be looking out for.

In businesses’ quest for profitability, in a world that seems to be more and more demanding, and also in a journey where achieving success is increasingly challenging for most business leaders – high competition, rapid technological changes, various sorts of crises (economic, political, health, …) and so on, to be able to better understand and obtain a certain excellence in timing could the most promising way to secure a reasonable profit margin. To know when to accelerate one’s engagement in a business, as well as when to decelerate, appears key. It seems to be a matter of skill regarding “ins and outs”.

It is also important to consider that these “ins and outs” are not only about entering and exiting a business, but rather can also refer to turning on or off a “business dial”, which can be more another type of action, e.g. opening or closing a division, changing or upscaling or phasing out a product, growing or stabilising a revenue stream, spending or saving, etc. There are signals out there for all of those types of decisions, too. Perhaps by concentrating more broadly on “ins and outs” and its classical reference to only entering and exiting a business, we are thinking too narrowly. We suggest considering timing, breakpoints, and signals in different contexts depending on significant business decisions.

All businesses are different. This implies that each business leader must develop their own lead indicators. Our book The Future Ready Leader (Lorange and Mugnaini, 2024) provides support when it comes to this. In our work we have reviewed some 70 books and also conducted around 21 high-level interviews. While none of these explicitly identify lead indicators for guiding “in/out” decisions, they all seem to have been developed in this spirit. Thus, many authors whose works we have reviewed, as well as most of the executives interviewed, seem to have had a central concern for lead indicators, i.e., how to perceive indicators and better forecast various types of decisions. Accordingly, leaders might be inspired by our book to establish their own tailored factors.

So, how can leaders come up with better ways of doing this? Are there factors that leaders might follow which might signal that there is time for action? And such signals may have value only if they can be considered to be exclusive for a given decision-maker. If the signal-reading is available to all, in contrast, there could be relatively little to gain. In such cases, it can be unrealistic to come up with better timing decisions, at least those that others in the market would not have picked up on. The trick will be to identify factors that are unique to that person or entity, ideally before others see similar or comparable indicators. Our aim, with our book, has been to contribute towards this.

To explore how to find such “weak” signals for guiding in/out decisions, we thus surveyed 70 books, written by a wide array of practitioners totalling some 15,000 pages. Further, we interviewed some 21 senior leaders from business and politics. The result is summarised in The Future Ready Leader. In the following, we shall discuss how these learnings could help leaders to improve timing decisions. We shall offer a conceptual scheme for coming up with lead indicators, based on inputs from our book. Further, we will aim to illustrate how our approach might work when applying this to three specific businesses.

We tout the importance of intuitive and counter-intuitive thinking, creative thinking, and ways that recognise that weak signals are just as valid or important as strong ones. In other words, learn by the not-so obvious, learn through the “side door”, learn through daily nuggets, not necessarily from the established teacher or guide but also from learners or the unexpected. Thus, it may become critical for an executive to be willing to break typical learning patterns and go beyond what may be at first the most obvious of lessons. In many large organisations, perhaps particularly in significant, bureaucratic ones, it could be particularly important to keep this in mind. Impact from support entities might tend to be particularly “frozen” in many established organisations.

A Conceptual Scheme for Better Timing

We have developed a four-step conceptual scheme for coming up with better lead indicators, to make better in/out decisions. Every business is, of course, unique. A senior leader must thus be prepared to strive to identify their own lead indicators, tailored to their own distinctive business, within their relevant market/s. While our book provides valuable inputs in such a process, it is absolutely fundamental that further tailoring of factors take place, such as “combining” the content from our book with the conceptual scheme below:

• Step 1: Identify a preliminary set of critical success factors, based on a senior executive’s understanding of their business.
• Step 2: List what might influence (“drive”) these critical success factors. Are there other critical success factors that might have been overlooked initially? (Draw on our book).
• Step 3: Develop several scenarios for how one’s critical success factors might evolve (again, drawing on the book).
• Step 4: Select measurable surrogates for each of these factors to track the development of the scenarios.

A senior leader must thus be prepared to strive to identify their own lead indicators, tailored to their own distinctive business, within their relevant market/s.

This process is, of course, both interactive and iterative. There may be iterative loops, triggered by initiatives from the decision-maker, so as to create revised inputs. In the following, we shall attempt to illustrate how this process might work through discussing four examples. While all examples are disguised, they nevertheless represent real cases taken from one of the authors’ experiences.

There are several bases for support when it comes to this type of exit decision in our book. Particularly, the interview with Kristian Jebsen (Part 4) is useful. Also, the interviews with Jan Jenisch (Part 5) and of Morten Hannesbo (Part 5) are helpful. In addition, many of the book reviews seem relevant, especially several of those in Parts 4 and 5.

Example: Offshore Shipping

Offshore supply shipping basically consists of two major segments, anchor-handlers, to assist the redeploying of oil rigs, and platform supply ships (PSVs), to transport supplies to offshore rigs (provisions, drilling mud, pipes,…). In addition, there are several smaller, specialised, niches (diving support, ROV,…). However, in this example, we shall focus solely on PSVs.

After considering several factors for how to decide where to order new PSV ships, and when to sell, we came up with the following simple paradigm, that also was easy to track: tonnage of the PSV fleet presently “in the water”, relative to new tonnage on order. When new tonnage on order shot up, it was perhaps time to sell. When there were relatively few new ships on order on the other hand, then it might be time to order new buildings, or to buy secondhand tonnage.

At one point, new building orders could be rapidly rising. And the secondhand price for PSVs would thus also tend to be good, as might be expected, since the market would still be strong, with nothing of the new tonnage yet depressing the market. One might want to sell.

But there might be objections, say, from employees. Here are two factors to consider when it comes to exit decisions:

Timing decisions (“ins” as well as “outs”) should typically be taken by the CEO alone. If group-based decision-making is at work, then subsidiary factors, such as protecting one’s job, safeguarding one’s turf, etc., will easily lead to inaction. Also, more decision-makers involved can naturally risk slowing down the speed to decision.

It follows from the above that these types of decisions often tend to be relatively unpopular. A robust CEO is therefore needed. They must be ready to make unpopular decisions, anticipating questions, preparing replies, etc.

Example: A Medical Testing Firm

A decision to go public was raised by several minority shareholders, but this was rejected by the majority shareholder. For the majority owner, a more extreme long-term focus seemed acceptable, setting aside aspiration to take advantage of shorter-term positive movement in the firm’s share-value cycle. So how might one come up with lead indicators for a more specific indication of what may be good timing then, still as seen from the vantage point of the minority shareholders?

Here are some inputs that might be taken from our book. The book by Rosling (Part 3) offers important analytical support. And Sethi’s book (Part 4) discusses several of these issues directly. Carryou’s book is also relevant.

One important assertion should be made at this stage, namely that it is important that a firm’s top leadership be in a position to actually act when an opportunity comes up. The counterpoint might be more fundamental disagreement among leading stakeholders, such as between various shareholder groupings, top management, the board, and so on. Again, it is important that there is someone at the helm with clear decision-making authority.

Example: A Land-Owning Firm

The local political authorities have tentatively approved the building of several semi-detached dwellings on around one-third of a land parcel outside a European capital city, and the land-owning firm has provisionally sold this land parcel to a developer. A main condition from the local political authority to allow the construction to take place, however, is a requirement that the local access road should be improved. While the cost of this rests on the local community and county, there might be relatively low willingness by the authorities to go ahead, due to other, competing priorities for them. A large development project nearby seems to have led to increased pressure to start the road-improvement project, however. But when could the road construction take place, triggering the land development firm to receive its sales compensation from the developer?

While there are many inputs from our book that might shed light on this issue, several of the books reviewed in Part 1 may be particularly relevant. Andrew McAfee’s book appears to be particularly so. Also, the book by Sam Zell (Part 8) is also helpful.

Example: Purchase Of A Chemical Tanker

There was an opportunity to purchase a part of a secondhand chemical tanker, which was to be operated by a well-represented shipping group, considered to be a world leader with a pool of ships designated to the transportation of chemicals. There seemed to be signals that it was a good time to enter, with the price of the ship being relatively low, a somewhat low new-building order book, as well as an apparent global uptake for the transportation of chemicals.

The reviews and interviews in Part 5 could shed important light on the issues affecting the attractiveness of chemical shipping. Several of the book reviews in Part 3 are also relevant, perhaps above all that of Siilasmaa’s book.

A portfolio strategic perspective is also important here, however, that there should be enough free cash available to execute attractive investments. In-decisions/in-opportunities typically come about rather randomly. Cash is needed to be ready to act when such opportunities arise.

Conclusions

As we are always stressing, it is especially critical to be able to anticipate so-called breakpoints, to be able to take timely actions, typically ahead of “the rest of the flock”. By breakpoints, we mean business interruptions that can arise from a variety of reasons, including environment, process, people, and so on. Some breakpoints are expected, others not. For those not anticipated, being in tune with or alert to the not-so-easy-to-see data points or the weak signals can help leaders to catch them.

Cycle management is a key concept here too, namely, to anticipate low parts of a cycle and to “get in”, as well as upper parts of a cycle, and to “get out”. In most types of shipping, for instance, this is particularly important. Cycle management does of course apply to many other business areas, too. And we can turn to successful investors who have turned this almost into a science, for inspiration. Breakpoint understanding represents a central premise for successful cycle management!

Do not ignore the weak signals that indicate the existence or probability of breakpoints. In quick-paced environments, we acknowledge how critical speed is. Yet we suggest that you can be fast, and focused (see the review of Hoffman and Yeh’s book in particular – Part 5). You can accelerate forward, you can build an awareness level in such a way that even small, minute impulses can serve as moments of transformation.

Weak signals can indicate that change can occur, for example in leadership. While strong signals may stream almost automatically into actions, tiny data points, weak signals are often unseen, set aside or misinterpreted. Scientists, doctors, economists, and even security experts or detectives, are examples of professions whose work relies heavily on their ability to look for signals and breakpoints.

So, a “new” managerial discipline is emerging – the sensing of signals regarding breakpoints, not only strong, but also weak ones. Effective leaders must develop an approach to understand these themselves. For each business leader, these will be different! Business schools might also be useful here, by focusing more on (typically weak) signals; how to gain understanding and how to measure. But, in the end, it is all about the effective leader him- or herself. Observation, listening, reflection are part of this critical process and mindset.

In summary, in-out decisions can yield success if made with the highest degree of observation of patterns, capture of signals, analysis, and solid doses of clear decision-making. We must not only ask our teachers and guides to help us to acquire these skills, but we ourselves must shift our leadership mindsets to that of a “signal sensitivity” mindset.

About the Authors

Peter Lorange, Honorary President, IMD, is a successful entrepreneur and the former owner of a highly diversified family investment company.  He is regarded as one of the world’s foremost business school academics, having held the position of President at IMD, Lausanne (Switzerland) for 15 years, having also been President of Norwegian School of Business, as well as a Professor at Wharton and at Sloan School (MIT). He has had several positions on various boards. His entrepreneurial journey spans key areas such as education, shipping, investments, and real estate businesses.

Karin Mugnaini is the Head of the International Alumni Association at IMD (Lausanne, Switzerland), and has been involved in international business since 1989, with engagements across the United States, Europe, Hong Kong, and currently in Switzerland. She has held numerous leadership positions in corporations as well as in startups, with a particular emphasis on new business initiatives. Ms. Mugnaini was formerly President & COO of the Lorange Network, working closely with Peter Lorange.

The post A New Business Leadership Paradigm to Understand Signals and Timing: When to ENTER a Business and When to EXIT appeared first on The European Business Review.

Nvidia’s growth has skyrocketed in the current AI boom, but the company also finds itself in the middle of geopolitical tech-tensions between the US and China. And now Big Tech wants to make their own chips.

“Who’s getting how many H100s and when is top gossip of the valley rn,” OpenAI’s Andrej Karpathy tweeted in August. H100 is an Nvidia chip powering the AI boom.

Nvidia, originally a niche graphics card maker for video games, has become a giant that Big Tech relies heavily on to build AI software.

The demand and dependence translate into their skyrocketing market value: Last week, Nvidia became the world’s fourth most valuable company, only surpassed by the likes of Microsoft and Apple​​. As of this writing, Nvidia has a market cap of $1.98 trillion.

To anyone wondering how Nvidia could reach that valuation: a single of their in-demand H100 chips costs between $15,000 and $40,000, depending on packaging and other factors.

However, several factors, from in-house production of AI chips to geopolitical competition, threaten Nvidia’s impressive market cap. We will return to their challenges after a dive into Nvidia’s ascent.

The semiconductors supporting the crypto- and AI booms

Those who had the foresight to invest in Nvidia early have seen values soaring in the last five years, from $36.90 in March 2019 to $792.38 as of this writing.

This graph from Macrotrends illustrates the meteoric rise of Nvidia over the past years.

When Nvidia passed Intel as the biggest chip maker in 2020, it was their bet on powering cryptocurrencies that paid off: Nvidia’s GPUs, initially designed for gaming, proved exceptionally capable of performing the complex calculations required for cryptocurrency mining, driving up demand among miners worldwide. (The subsequent fall in Nvidia’s stock occurred as the cryptocurrency market experienced volatility and decline.)

ChatGPT’s public release in November 2022 sparked the latest meteoric rise, and Nvidia has grown exponentially – and dramatically so – ever since. In the AI gold rush, Nvidia has been the shovel, the enabler that has allowed software companies to participate in the AI race. And that has paid off: While AI companies generally struggle to monetize their AI-related products, Nvidia’s AI enablers are one of the few AI-related products that have been profitable at scale.

Today, Nvidia accounts for 70 percent of AI chip sales – their share is even higher when it comes to generative AI.

How did Nvidia beat Intel?

Nvidia has been better than Intel in crypto and AI for several reasons. Firstly, utilizing AI requires handling massive data sets. Nvidia’s chips feature a highly specialized architecture optimized for efficient parallel processing, a critical requirement for handling the massive datasets associated with AI workloads and crypto mining. A quicker recognition and adaption to the market shifts towards AI and machine learning has helped them position themselves as a leader in this space.

Nvidia has invested heavily in AI, developing hardware for AI and software and platforms like CUDA for AI development. That has created a community of programmers who consistently invent using the company’s technology. Today, Nvidia is a company that produces computers, software, cloud services, trained A.I. models, and processors.

Naveen Rao, a founder of an AI chip start-up bought by Intel, says that everybody “builds on Nvidia first[…] If you come out with a new piece of hardware, you’re racing to catch up.”

Jensen Huang: A new power player in tech

Nvidia’s ascent has made CEO and co-founder Jen-Hsun Huang, also known as Jensen Huang, a power player in tech. Often seen in a trademark leather jacket and black t-shirt, Huang has become someone tech leaders want to rub shoulders with to secure more H100s before their competitors.

On Nvidia’s position in the AI boom, Huang recently said: “The thing that we understood is that this is a reinvention of how computing is done. And we built everything from the ground up, from the processor all the way up to the end.”

This understanding has brought Nvidia close to the biggest companies in tech.

Big Tech’s biggest supplier

Nvidia is the biggest supplier for Big Tech, currently competing to dominate generative AI.

In 2023, Meta and Microsoft spent $4.5 billion on Nvidia’s H100 chips, with Amazon and Alphabet (Google’s parent company) following, spending 1.5 billion dollars each.

Big Tech’s reliance on Nvidia is a blessing and a curse for the chip maker, who’s grown equally dependent on those few companies. And now, several Big Tech companies are looking to end their Nvidia dependence.

In-house chip production

As The New York Times writes, the “boom in generative A.I. over the last year exposed just how dependent big tech companies had become on Nvidia. They cannot build chatbots and other A.I. systems without a special kind of chip that Nvidia has mastered over the past several years”.

The surge in demands has seen Nvidia struggle to keep up. And now Nvidia’s largest customers – Amazon, Microsoft, Google, and Meta – are all designing their own chips. To reduce costs and dependency on a company that also supplies their competitors.

Sam Altman, CEO of OpenAI, is also pursuing chip independence. He is currently seeking a whopping five to seven trillion in an attempt to reestablish competition and a steady supply chain of chips: “the world needs more ai infrastructure[…] than people are currently planning to build[…] building massive-scale AI infrastructure, and a resilient supply chain, is crucial to economic competitiveness,” Altman recently tweeted.

In 2023, Google, the leading chip developer among big tech companies, spent two to three billion dollars producing their own chips. According to the New York Times, Nvidia sells its chips from $15,000 and up. The search giant can build relatively similar chips for 2-3000 USD each.

However, after ten years of independent chip development, Google still relies on Nvidia’s chips for certain products.

Independent chip development could pose a future challenge for Nvidia. A more immediate threat is the tensions between the US and China.

Geopolitical showstoppers

Few resources are as vital to the supply chains in the modern world as semiconductors and chips. As a prerequisite for most technological products – from gaming consoles to modern cars to AI software – they also create substantial tensions.

Taiwan is home to Taiwan Semiconductor Manufacturing Company (TSMC), the world’s largest contract chipmaker, which produces the majority of Nvidia’s chips. The semiconductor factory has become a focal point of global technology and geopolitical rivalry between the United States and China. As such, Nvidia, a company that many companies are deeply dependent on, is deeply dependent on TSMC and relative political stability in Taiwan.

And that’s not the only way the rivalry between China and the US affects Nvidia. Also the US curbs on AI chip sales to China have significantly impacted the chip giant. Aiming to undercut China’s AI development, the US has tightened regulations, blocking access to advanced chips from companies like Nvidia.

Nvidia has faced a direct hit from these restrictions, with expectations of a significant decline in sales to China, which previously constituted a substantial portion of its revenue. To limit the losses, the company has been developing new processors tailored to Chinese customers to comply with US regulations.

Nvidia has stated that while it has managed to comply with regulations, the long-term impact could be detrimental, as Chinese companies may seek alternatives, potentially eroding Nvidia’s market share and influence in one of the world’s largest markets​​.

What does the future hold for the chip giant?

Amid its massive success, Nvidia is challenged by Big Tech chip independence and geopolitical strides. On the other hand, their chips are among the fastest on the market, and the company has a headstart with its community of developers and offerings combining hardware and software.

Nasdaq writes that Wall Street analysts expect Nvidia’s rally to continue and that it has a consensus rating of “Strong Buy” from analysts.

Nasdaq even goes as far as speculating that Nvidia could become the world’s biggest company: “While you might have been ridiculed just a few years back for talking about the possibility of Nvidia becoming the world’s biggest company, it looks like a real possibility now.“

Only time will tell if Big Tech and geopolitical tensions will slow down Nvidia’s ascent or if a hardware company fuelling the AI boom can, in fact, become the largest company in the world.

One thing is certain. Nvidia is no longer an underdog niche graphics card maker for video games.

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This year, the World Economic Forum (WEF) has chosen a compelling theme: ‘Rebuilding Trust’.  

As outlined on the WEF’s website, it’s all about rekindling trust in our future, fostering cohesion within societies, and fortifying the ties among nations. Following the disruptive upheavals of 2023, a dose of trust-building feels appropriate. 

Notably, AI, took the spotlight at the Forum for the first time along with other crucial themes like security, jobs, and climate. This acknowledgement underscores the profound impact AI is set to have on the global stage. 

Given its dominant presence in the headlines, AI’s central role shouldn’t raise many eyebrows. And honing in on ‘Trust’ is an important guiding principle for business leaders navigating AI in 2024, as they align their strategies with ethical considerations and societal expectations. In a world increasingly shaped by technological advancements, instilling trust is imperative for both sustainable and responsible innovation. 

Charting AI’s Next Phase: Innovation Anchored in Responsibility 

The AI landscape is brimming with potential, providing an opportunity to shape the first genuinely creative human, freeing time for innovation, opening doors to novel work methods, and layering machine-driven data analysis to enhance our decision-making. 

But it’s not without challenges. Operating without responsibility risks damaging confidence, empowering malicious actors, and causing significant harm. Navigating a course that seamlessly integrates both innovation and responsibility is paramount. 

Over the past year, global efforts have been made to address this. The UK hosted the AI Safety Summit, introducing the Bletchley Declaration, the inaugural international agreement for a secure AI framework, endorsed by 28 countries. The EU created the AI Act, the US crafted an ambitious blueprint for an AI Bill of Rights. Numerous nations are refining their distinctive AI governance strategies, showcasing a collective commitment to responsible AI advancement. 

Looking ahead to 2024, I foresee sustained momentum toward AI regulation, emphasizing ethical deployment, transparency and robust risk management. This should help usher in a safer, more accountable global environment for AI development. 

To assess the current landscape, EY recently published a revealing report on key global AI regulatory trends. Standout trends identified in the report include the adoption of AI governance frameworks, compliance systems, risk-based action plans, industry-specific rules and comprehensive approaches in sync with other digital policy priorities. Additionally, collaboration among policymakers, the private sector and civil society is critical for successful implementation.  

These trends have significant implications for business leaders and policymakers worldwide. Remaining agile and well-informed is imperative if businesses are to navigate the evolving legal terrain. Policymakers, meanwhile, face the challenging task of crafting effective regulation while moving toward convergence with other key jurisdictions – without stifling innovation. Together, they play a pivotal role in guiding investments to translate regulatory initiatives into tangible growth for the global AI sector. 

So, what’s my message for business leaders who gathered in Davos looking to chart an AI course in 2024 that includes both responsibility and innovation? Here are three critical steps: 

1. Understand your legal, governance, and compliance obligations. As a crucial first step, and to make sure companies are meeting the expectations of investors, regulators, and other stakeholders, it is imperative that businesses possess a deep understanding of their responsibilities under the laws and regulations of the jurisdictions wherever they do business and establish policies and procedures designed to meet them. Some key new AI regulations have significant extra-territorial implications. Organizations will also need to understand how new AI codes and regulations interact with existing laws, including sector regulations. 
2. Implement strong AI governance procedures throughout all levels of the organization. This comprehensive approach should encompass governance frameworks, clearly defined responsibilities, a meticulous inventory, and stringent controls for the use of AI, spanning from the board to operations levels. The establishment of an AI ethics board  can play a pivotal role in providing independent guidance to management, particularly concerning ethical considerations in AI development and deployment.[Text Wrapping Break] 
3. Be proactive – initiate conversations with regulators, governments, NGOs, and other stakeholders. This is important for helping businesses gain an in-depth understanding of the continually evolving regulatory landscape. These kinds of engagements also contribute potentially invaluable information and insights for policymakers as they navigate the complex process of shaping rules and regulations, fostering collaboration, and enhancing the effectiveness of regulatory frameworks. 

2024 is undoubtedly a pivotal moment for AI; A balancing act for both policymakers and business leaders as they move toward AI advancement, innovation, and responsibility. As we reflect on Davos, these conversations will assume utmost significance. Succeeding isn’t merely an ethical choice – it’s an imperative. 

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms. 

About the Author 

Julie Linn Teigland has nearly three decades of experience in professional services for international clients, Julie’s focus is on transformation processes, in particular on the challenges of digital transformation, and is committed to the sustainable development of capital markets and their framework conditions. Julie has served as lead partner for several Fortune 500 clients. 

The post Navigating Trust and Innovation: AI in 2024  appeared first on The European Business Review.

If you’ve ever thought that there must be a more positive, less damaging way of resolving workplace disputes than that offered by the traditional approaches, the resolution framework could well be what you’ve been looking for. 

There are very few people who haven’t experienced some form of conflict at work at some point in their career. Managers fall out with their direct reports over performance issues, team members come to blows as a result of differing working styles, colleagues clash with each other over whether work has been allocated fairly or whether some are being treated more favourably than others. 

As recent headlines graphically illustrate, we are also seeing an increasing amount of alleged bullying, sexual harassment, misconduct, and discrimination of all kinds. The working world is clearly not a happy place for many people. It seems that our offices, shops, and factories are becoming increasingly confrontational, vitriolic, and toxic. 

It’s a problem that is costing industry dearly, in both human and financial terms. Research from the CIPD suggests that nearly 4 in 10 UK employees experience some kind of interpersonal conflict at work over the course of a year. A report from the UK conciliation service ACAS puts the cost of this workplace conflict at £28.5 billion every year, equating to just over £1k on average for every employee.  

The causes of workplace disputes are complex and varied. However, with over 20 years’ experience of mediating in some of the most complex disputes imaginable, I firmly believe that the way organisations typically handle conflicts, complaints, and concerns is contributing to this rising tide of dissent, disagreement, and dysfunctional behaviour. We need a fresh approach to resolving the myriad of issues that inevitably arise at work, one that is more appropriate for today’s fast-changing modern workplace. 

A growing number of forward-thinking organisations – Burberry, HSBC, Aviva, and the BBC to name just a few – have recognised this and are reframing the damaging and divisive disciplinary, grievance, and whistleblowing policies and processes of the past. They are developing an overarching resolution framework which allows them to resolve conflicts and concerns in a more compassionate, people-centred, and values-driven way. 

Says Claire Salter, Director of Global Employee Relations at Burberry: “We know that conflict is unavoidable, but we know that when it’s handled well, it can be a driver for positive change. In fact we strongly believe that positive and constructive conflict can fuel our creativity – and as a creative business, creativity is at the core of everything we do. That’s what excites us about implementing a resolution framework – it’s an opportunity for us to reframe the conversations that we’re having about conflict across the business, and it gives our leaders the tools and space they need to resolve those issues early, informally and constructively.”  

So what does a resolution framework look like, and how does it work in practice? 

From retributive to restorative 

The traditional processes used by organisations to manage conflicts and concerns are adversarial in nature. They are based on a retributive model of justice that has blame and punishment as its primary outcomes. This model of justice is reductive, i.e. it encourages right / wrong, win / lose, and blame / shame mindsets and behaviours. It infantilises our workforces, meaning that, when a problem arises, instead of encouraging employees to sit down and sort it out through face-to-face, adult dialogue, people are typically plunged straight into damaging and divisive formal and often deeply damaging and unsafe processes. 

This causes a huge amount of stress and distress to the people involved. Employees become increasingly anxious and upset as the sense of psychological safety diminishes. As their stress levels rise, their performance starts to suffer, with little option but to take time away from work or, ultimately, leave the organisation. It’s not just the people directly embroiled in the conflict who are affected. Everyone around them is impacted, too. Colleagues take sides, a tense atmosphere takes hold, and productivity declines, so much HR and management time is wasted. 

These formal processes rarely, if ever, result in a successful outcome. Relationships are irretrievably damaged, good people leave their jobs, corporate reputation takes a hit and, ultimately, no one wins. 

A resolution framework, by contrast, is restorative in nature. As an integrated people policy (IPP), it offers organisations a variety of proactive and empowering approaches for securing a constructive and lasting resolution to all types of workplace conflict. These might include early, informal dialogue, facilitated conversations, mediation, team facilitation, and coaching. The ability to access more formal processes, up to and including dismissal or legal action, is retained for the rare occasions where it is identified that this is the most appropriate course of action. 

These frameworks put people before process. They shift the dial towards adult-to-adult dialogue, allowing organisations to develop positive workplace cultures that have empathy, inclusion, and well-being at their heart. They engender a culture of cooperation and collaboration, leading to happy, healthy, and harmonious workplaces. 

As Heather Palmer, Senior HR Business Partner in Culture, Policy and Employee Relations at the BBC, explained in a recent webinar, there is also a strong business case for adopting this more progressive, restorative approach: “We’ve used diagnostics to identify that moving to a resolution framework is not just about improving the people-centred experience in dealing with conflict resolution, but there’s a business and economic benefit in terms of the money and time that we’re spending in formal processes.” 

Getting up and running 

The involvement and collaboration of key organisational stakeholders – senior leaders, managers, HR, employees, and union partners – is key to successful development and implementation of a resolution framework. Companies who have successfully introduced this new approach have typically involved all interested parties from the outset in developing overarching frameworks that work in their specific operational circumstances and align to their organisational purpose and values. 

Three core elements of the resolution framework are the resolution centre, the resolution index, and resolution champions. 

The resolution centre is a central hub which coordinates the day-to-day operation of the framework and manages the triage process (see below) used to identify the most appropriate route to resolution for any conflicts, complaints, and concerns that are raised. The centre also typically coordinates conflict management training for front-line managers and resolution champions (see below) and, in some cases, manages in-house communication and development of tool kits and resources to support employees as they embrace the new approach. The resolution centre also has an important role to play in gathering data, feedback, and intelligence around the resolution process, so that the organisation can continually learn and improve its conflict-management competence. 

The resolution index is used to triage any requests for resolution that come through to the central hub. Some of the criteria used in the triage process include the seriousness of the issue being raised, the impact of the situation on the parties, previous attempts to resolve the situation and their outcomes, the number or frequency of previous complaints, and the risk of the situation to the parties and the organisation. Each request is scored against the criteria, and the most appropriate route to resolution is assessed. The lower the score, the more informal the remedy (such as local resolution, a facilitated conversation, coaching, or mediation). In higher-scoring incidences, organisations may consider undertaking a detailed fact-find, which may in turn lead to a more formal resolution meeting. 

Resolution champions are an internal cadre of trained volunteers who support the parties through the resolution process and for at least a year after, to ensure that no further issues arise and that the agreed outcomes or improved relationships are retained. 

How it works in practice 

The resolution framework encompasses the following key steps: 

Step 1: An issue arises 

The resolution framework starts with the premise that it is the responsibility of the local line manager to resolve any situations as early and constructively as possible. This usually takes the form of an early, informal resolution meeting, where the people concerned are able to discuss their disagreements or concerns openly and honestly, in a safe and supportive space. In the vast majority of cases, this approach generates a successful resolution and no further action is needed. Should problems start to arise again, a resolution champion will be on hand to help nip any issues in the bud and get everyone back on track. The success of an early-resolution meeting does, of course, depend greatly on the line manager’s having an understanding of the nature of conflict and how to resolve it. Organisations cannot assume that their managers will naturally have the confidence and competence to do this; they will need training to support them in this important role. 

Step 2: Request for resolution 

If attempts to resolve an issue locally and at source are not successful, the next step is for the parties involved to submit a “request for resolution” to the resolution centre. Trained staff within the centre will triage the request against the predetermined criteria in the resolution index, and will make a recommendation for the most appropriate route to resolution. This step is the restorative alternative to the more retributive approach of “raising a grievance”. 

Step 3: Early resolution 

Requests that are triaged at this early stage are most likely to be well suited for one of a number of early-resolution methods. This might include a facilitated conversation, where both parties are able to share their concerns, express their needs, and find a mutually acceptable way of restoring the relationship and moving forward. Some cases will be suited to mediation, where a trained, independent mediator will bring people together to engage in powerful dialogue that will help to transform their dispute from dysfunctional and destructive to constructive and functional. Other options might include team facilitation or coaching. Each approach is suited to a particular type of conflict and its relative complexity or severity. 

Step 4: Formal resolution 

For higher-scoring cases, the triage process will lead to a more formal resolution process. This might be a fact-find (an alternative, more restorative approach to the traditional investigation) or a resolution meeting (as opposed to a disciplinary or grievance hearing).  

Organisations that have reframed their traditional approaches to managing conflict and adopted a resolution framework are benefiting in a number of ways. They are resolving issues sooner and more effectively and protecting workplace relationships, with a corresponding impact on performance, reputation, and competitive advantage. 

Anthony Fitzpatrick, Head of Colleague Experience and Employment Policy at Aviva, sums it up well: “The introduction of the resolution framework changed the whole concept and dynamic of managing conflicts and complaints within the workplace. Culturally, the change in language and emphasis have been so important. We aren’t focusing on being aggrieved, we are focusing on resolution, and that is a fundamental difference. We have seen that the vast majority of cases are settled either at triage or through a facilitated conversation. This allows everyone to focus on their job and increases morale and motivation, which is good for personal well-being; it’s good for the business and it’s good for the customer, too.” 

About the Author

David Liddle is the founder and chief consultant at The TCM Group and author of the book Managing Conflict: A practical guide to resolution in the workplace, Kogan Page, 2nd edition, 2023. 

The post Why We Need A Resolution Revolution  appeared first on The European Business Review.

Interview with Ala Shaabana, Co-founder of Opentensor Foundation 

Amid widespread concern regarding possible built-in bias, opacity, and misalignment in big-tech-dominated AI, one strategy that offers the potential for more balanced machine learning processes is to decentralise them. Ala Shaabana of the Opentensor Foundation explains. 

Hello, Mr Shaabana. It’s a pleasure to have you here. To begin, would you tell our readers a little bit about your background and personal journey in the field of AI, leading up to your role as a co-founder of Opentensor Foundation?

I started my journey in graduate school, where I obtained my PhD in applied artificial intelligence on human-centric sensing in 2017 from McMaster University. I then joined VMware in Palo Alto, California, working on problems in distributed computing. In 2019, I met my current co-founder Jacob Steeves, who had been working on the problem of decentralised AI since 2016, on an online AI research community. We then decided to work together on Bittensor and start building the protocol and together co-founded the Opentensor Foundation.

From your perspective, what do you think are the key moral considerations driving the recent discussions within the AI industry, and how might they influence the path AI development takes? 

I believe that AI transparency and explainability, bias, and alignment are some of the most important considerations surrounding AI today. Transparency is ensuring that AI training processes and code are always made available to the general public for review and scrutiny. The Biden administration’s recent executive order is loosely aimed at solving this issue. However, open source AI already solves it, indicating just how ill informed governments are about technologies and AI in general. AI bias is centred around moral questions about fairness and equality, especially in critical applications like hiring, law enforcement, and loan approvals. As a result, there’s a growing emphasis on creating AI that is fair, unbiased, and inclusive, which may lead to more rigorous data handling and algorithmic accountability measures. Finally, the AI alignment problem refers to the challenge of ensuring that artificial intelligence systems’ goals, decisions, and actions are aligned with human values and intentions. This problem becomes increasingly critical as AI systems grow more complex and capable, particularly when they are given more autonomy in decision-making. 

When it comes to decentralised AI and collective ownership, how does this philosophy align with your personal vision for the future of artificial intelligence? What concrete benefits do you think decentralisation brings to the AI landscape? 

AI transparency, bias, and alignment are central to my vision for Bittensor and the future of AI in general. Decentralisation ensures that all three of these are dealt with by the community at large, and not by one company whose bottom line is truly its profits. When AI is placed in the hands of everyone, and not just one entity, it loses its bias, is forced to be transparent, and is aligned with everyone’s interests by default, as everyone is contributing to it. 

The conversation often revolves around the concentration of AI power in tech giants. In your view, how can decentralised AI models play a role in disrupting this concentration, and what challenges or opportunities does this dynamic present for the industry?

Decentralised AI models have the potential to disrupt the concentration of AI power in the hands of tech giants, offering both challenges and opportunities for the industry. Let’s start with opportunities. Decentralised AI models can enable a wider range of stakeholders, including smaller companies, researchers, and individual developers, to contribute to and influence AI development. This democratisation can lead to more innovative and diverse AI solutions that reflect a broader range of needs and values. There’s also more potential for greater creativity and a wider array of AI applications. Finally, decentralised systems can be more resilient to failures and cyberattacks, as they don’t rely on a single centralised entity. This enhances the overall stability and security of the AI ecosystem. However, challenges still exist in the system that must be resolved first. For example, decentralising AI development could lead to challenges in coordinating efforts and maintaining standards across different projects. Additionally, establishing effective regulatory frameworks that can adapt to the rapidly evolving and diverse landscape of decentralised AI is a significant challenge. Decentralised models may struggle with resource allocation, as smaller entities might lack the computing power and data access that larger corporations possess.

To give us a clearer picture, could you walk us through a real-world example of how the Bittensor protocol operates and contributes to the broader goal of decentralised AI? 

By incentivising the creation of decentralised AI models, the Bittensor protocol incentivises AI engineers and researchers to create state-of-the-art AI models to compete with each other to provide the best-possible output to users. As an example, a user can build a state-of-the-art model and deploy it on Bittensor’s text language subnetwork. The model’s performance is judged by the validators on the system. Validators will reward the model with more Tao than its peers if it outperforms its peers. Users, on the other hand, can interface with validators with their prompts, who will send these prompts to the models on the network and deliver back the best response. Thus, users will always get the best response for their queries and models will always be rewarded in proportion to their performance.

Reflecting on the recent success of Ritual in securing substantial funding, how do you interpret this within the broader industry trends? What implications does it carry for the future landscape of decentralised AI platforms? 

This is a positive indicator that many are starting to embrace the decentralised AI narrative, and the idea of taking this power away from centralised tech giants. However, it is vitally important that these companies continue to embrace the decentralisation aspect as well as ethics, and not simply assume that, just because a system is decentralised, then it is ethical. 

Thinking about international collaborations in establishing ethical standards for decentralised AI, how do you see organisations like Opentensor Foundation contributing to and fostering such collaborative efforts? 

International collaborations in establishing ethical standards for decentralised AI are crucial, given the global nature of technology and its impacts. Organisations like the Opentensor Foundation can play a significant role in fostering these collaborative efforts in several ways. 

Developing Open Standards and Protocols: Organisations like the Opentensor Foundation can lead or contribute to the development of open standards and protocols for decentralised AI. By promoting a set of universally accepted standards, they can ensure interoperability, fairness, and ethical compliance across different systems and regions. 

Facilitating Global Dialogue and Consensus Building: These organisations can serve as platforms for dialogue between various stakeholders, including governments, tech companies, academia, and civil society. By bringing together diverse perspectives, they can help in building a global consensus on ethical AI practices. 

Research and Innovation in Ethical AI: Organisations dedicated to decentralised AI can invest in and support research focused on ethical considerations, bias mitigation, transparency, and accountability in AI systems. This research can provide valuable insights and guidelines for the development of ethical AI. 

Education and Awareness Campaigns: Educating AI developers, users, and the broader public about the importance of ethical AI is crucial. Organisations like Opentensor can organise workshops, seminars, and campaigns to raise awareness about ethical AI practices and the significance of decentralisation in promoting fairness and transparency. 

Policy Advocacy and Advisory Roles: By actively engaging in policy discussions and serving as advisors to governments and regulatory bodies, such organisations can influence the development of policies and regulations that govern decentralised AI, ensuring they align with ethical standards. 

Building Ethical AI Tools and Frameworks: Developing and providing open-source tools and frameworks that embody ethical AI principles can significantly aid developers in creating AI systems that are inherently ethical, transparent, and unbiased. 

Encouraging Community Involvement and Diversity: Promoting community involvement in AI development can ensure that AI systems are not only technically sound but also socially relevant and beneficial. Diverse community participation can help in understanding and addressing a wide range of ethical concerns. 

Partnerships and Collaborations: Forming strategic partnerships with other organisations, universities, and research institutions can amplify their efforts in promoting ethical standards. Collaboration can lead to pooling resources, sharing expertise, and aligning goals for a more significant impact.

Looking ahead, where do you personally see significant growth opportunities, both for yourself and the broader AI industry? Particularly, how do you envision these opportunities within the context of the ongoing moral discussions and the push for decentralised technologies? 

I believe the Opentensor Foundation is well positioned to be a central player in the decentralised AI movement, as more and more entities start to embrace decentralised AI as the ethical future of AI. It is inevitable that people will look to entities like the foundation for moral and ethical guidance, and in this case it becomes extremely important that the foundation lead by example and ensure that all moral considerations are taken into account and align AI with the planet. 

Executive Profile

Ala Shaabana is a co-founder of the Opentensor Foundation, an organisation dedicated to the building and maintenance of the Bittensor protocol, a peer-to-peer machine-learning protocol that incentivises participants to train and operate machine learning models in a distributed manner. By interconnecting neural networks on the internet, Bittensor aims to create a global, distributed, and incentivised machine learning system. 

Educated at McMaster University in Canada, Ala holds a PhD in Computer Science with a dissertation focus on human-centric sensing, creating extremely small machine learning models that fit on IoT devices to detect signals coming from the human body. Prior to founding the Opentensor Foundation, Ala worked on distributed computing research at VMware, where he led three projects on neural architecture search, language modelling, and load prediction in distributed environments. Subsequently, this led him down the path of distributed AI and how models across the internet might be able to work together to accomplish tasks. 

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Until recently, Taiwan’s central position in the global supply chain of advanced semiconductors was not seen as an issue. But today, in an uncertain geopolitical climate, governments around the world have good reason to reexamine the security of supply of these increasingly crucial components.

Economic prosperity and global power in the twentieth century were defined by oil. Today, economic growth and our very way of life are defined by silicon. Semiconductors that are thinner than a strand of human hair power everything from our electric toothbrush to our smartphones to the most sophisticated fighter jets.
The global semiconductor market was valued at US$573.44 billion in 2022 and is projected to exceed over 1 trillion dollars by 2030. To put this into perspective, in 2021 China spent US$432 billion on imported microprocessors, the equivalent of its total expenditure on grain and crude oil imports.

Given the crucial role of semiconductors, often referred to as chips, in the modern-day economic system, it is surprising that it has taken increased tensions with China and the supply chain disruptions caused by COVID-19 for heads of state to view seriously the vulnerabilities in these global supply chains.

Supplying chips

The quirk of history that located the most advanced semiconductor manufacturing in Taiwan was a product of the far-sightedness of the government, which invested billions in the sector, the decision of Western policymakers to leave the location of manufacturing facilities to market forces and, within the EU, the system of regulation and taxation, which has created an environment inhospitable to the emergence of domestic tech champions.

The Taiwan Semiconductor Manufacturing Company (TSMC), which manufactures the most advanced chips, stands at the apex of a complex global supply chain, comprising thousands of specialised companies across the world. The Semiconductor Industry Association estimates that, prior to the pandemic, one of its members had more than 16,000 suppliers, of which more than 8,500 were outside the US. The raw materials and the components of a chip, criss-cross the world before eventually ending up as the brains of a device.

The quest for cost savings meant that this global complexity was acceptable for much of the past 30 years. Now, the vulnerabilities of global supply chains, revealed by COVID-19 and the geopolitical tensions between the US and China, are putting pressure on chip manufacturers to onshore or friend-shore part of the manufacturing process.

Given the complexity of the sector, from the raw materials to the human talent and the vast investment required to fabricate chips, the industry may be confronting its greatest challenge.

What’s in a chip?

Chips are made from silicon. Each chip has hundreds of tiny layers, made up of transistors and electrical circuits, which determine what the chip can do. The miniscule circuitry is printed on each layer using lithography, extremely precise rays of light. The smaller the width of the transistor gate – 5nm, 3nm – the more processing power can fit in a given space, with less power needed. The smallest transistors are more than 10,000 times thinner than a human hair.

Different-sized chips are used in different equipment. Intel manufactures a lot of 10nm and 14nm chips that are used in computer CPUs and GPUs. Less-advanced 28-40nm chips are primarily used in the automotive industry and in household devices such as coffee makers and electric toothbrushes. Chips of 5mn are sought after for advanced data processing and AI. They are used in the latest smartphones, NASA Rovers, and F35 fighter jets.

The insatiable appetite for chips

A record 1.5 trillion semiconductors were shipped in 2021 and demand is expected to double by 2030. The rising consumption of consumer electronic devices fuels the market, as does demand from the industrial and military sectors. New technologies such as the Internet of Things, artificial intelligence, and machine learning create new opportunities for market development and enable chips to process large amounts of data in less time.

The challenge with chips

Access to semiconductors is an integral part of national security and governments across the political spectrum are seeking to develop domestic manufacturing capability. To be successful, this will require the adoption of government-directed industrial policy on an unprecedented scale.

Costs

Chip fabrication requires massive fixed-asset investment and, therefore, large subsidies, but with no guarantee of success. In August 2022, the Biden administration announced US$52 billion in subsidies for chip manufacturing and research in a piece of legislation that became known as the “Chips Act”. This was a significant step forward for US domestic manufacturing but, to put in perspective the sums required to compete in the semiconductor space, this investment was dwarfed in March 2023, when South Korea announced it would build the biggest chip centre in the world, using US$230 billion of private investment from electronics giant Samsung over the next 20 years.

Each fab easily costs US$15 billion to build, and the essential piece of equipment to yield the most advanced chips costs upwards of US$180 million. Creating 5 nm chips and below requires the use of an extreme ultraviolet lithography machine. It uses small rays of light to etch the miniscule circuitry onto the chips. Only one company, ASML, based in the Netherlands, makes this EUV machine, the price of each one being over US$180 million. Buying these machines means that production costs will soar, but if you can’t implement the process without the machine, you have no choice but to buy it. There is fierce competition to be the company that buys the next machine to be manufactured among the three main players in the market, TSMC, Intel, and Samsung, who can afford the hefty price tag.

Building plants

Once the funding for fabs is made available, building time is three years and the project requires 6,000 construction workers to complete. Each fab is a manufacturing marvel. It is at least 250 thousand square feet, and houses 9 million metres of cabling, 1,200 multimillion-dollar tools, and 1,500 pieces of utility equipment.

Talent

Once the fab is constructed, multiple layers of talent are required for each step of the design and manufacturing process. A large, fab-less semiconductor company may well need 100 doctorate-level designers at the design stage. A sizeable fab needs about 4,000 workers with skills in production engineering, logistics and support, and production operations, plus thousands of lower-skilled workers. As technology evolves, with greater analytics and automation, the talent and skills required will also evolve and employment requirements will change.

To expand domestic manufacturing, the US and the EU will need to rethink their educational priorities and incentives for talented individuals to work in the sector. In 2021, the global semiconductor industry had about 2 million direct employees worldwide. The number is projected to increase to 3 million by 2030 if current forecasts for increased production are to be met.

The EU and, more notably, the US have an asymmetric advantage in attracting talented individuals, given their high living standards and opportunities for personal-wealth creation. Current immigration requirements are undermining the allure of the regions as employment destinations. As a consequence, the unanswered question remains: where the talent will come from.

Raw materials

Once the talent is in place, the 17 rare earth elements, which cluster near the bottom of the periodic table, become vital to the manufacture of semiconductors. While the US government lists these minerals among those deemed critical to the country’s economic and national security, the term “rare earth” is misleading. These metals are relatively abundant in the Earth’s crust, but extraction is complicated because such elements are jumbled together with many other minerals in different concentrations.
China currently controls the majority of the world’s separation facilities that produce the purified metals. In the event of increased geopolitical tensions or supply chain disruptions caused by other factors, the US and EU could quickly face shortages of these metals.

Investment in domestic mining infrastructure and securing supplies in other regions of the world is crucial if the US and EU are to enhance their security of supply, particularly as demand for these metals increases. While this is achievable, the costs involved are significant and, for the EU, sustainability and environmental considerations may act as an impediment.

Newer materials that are used in the production of chips that are capable of handling high voltages and currents, as required for electric vehicles, solar panels, and wind turbines, are a field where the US and EU can be relatively self-sufficient. Gallium nitride (GaN) and silicon carbide (SiC) can run at thousands of volts (in contrast to silicon, which can’t handle extreme heat) and are quickly becoming multibillion-dollar markets.

Chips are the new geopolitical battlefield

Technology will define the future of geopolitics. Advanced semiconductors will define the future of military capability. The price of a fab is the same as a new aircraft carrier, with the fab now being of greater importance to national security.
The silicon shield that protects Taiwan was, until recently, considered by many to be impervious. It gave the world a reason to defend the island from invasion and, perhaps, created a reason not to invade. New geopolitical realities are challenging this assumption and Taiwan is a major vulnerability to all importers of advanced semiconductors.

The worldwide semiconductor industry is expected to double its capacity by 2030. The question is where this capacity will be built and whether the US and EU will demonstrate the political will necessary to revolutionise domestic production. It is non-negotiable if the regions are to remain economically, politically, and militarily competitive and if their domestic manufacturers are to have access to an abundant supply of chips.

This article was originally published on 10 June 2023.

About the Author

Dr. Elizabeth Stephens is an investment and country risk advisor and managing director of Geopolitical Risk Advisory, a tech company that uses AI and data analytics to map geopolitical instability. She is a regular conference speaker and visiting lecturer at London and Henley Business Schools.

The post Chips Everywhere and with Everything appeared first on The European Business Review.

In the aftermath of the initial AI tidal wave that has rolled across business and industry, there are signs that the emphasis may now be shifting from how best to apply the technology to how best to demonstrate its trustworthiness.

The crux

A glimpse at the journey

1. Companies are not standing still. About 80 per cent of companies have launched some form of trustworthy AI.
   
2. Companies are, however, rarely embracing a full range of practices that are the backbone of trustworthy AI. On average, firms use four out of 10 organisational practices reviews, and only 3 per cent of companies are embracing all the practices.
3. Among the practices considered, none has been deployed mainstream yet (table 1).
4. Country and sector seem to be playing a role in the degree of operationalisation. Europe lags in comparison with Asia (India and Japan), Canada leads over the US, and high tech is not that far ahead of other sectors.
   
5. Operationalisation of trustworthy AI is a top priority for about 30 per cent of companies, not necessarily to further expand their efforts, but to catch up on their peers.

Learning from leaders

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To stay relevant and achieve resilience, company leaders need to focus not only on speed but also innovation. In this article, the authors discuss how the right combination of these two parameters will make your company a top performer.

In the many workshops that the MIT Center for Information Systems Research (CISR) conducts with senior executive teams globally, we often hear senior leaders say “If only we could go faster.” So we decided to research what happens if a company goes faster, and the answer was surprising: speed alone doesn’t differentiate performance much. In our research, companies that were top performing in both growth and margin relative to their industries not only went faster to market but also innovated more effectively.

The Need for More Than Speed

To better understand the impact of speed on performance and what it takes to get there, we surveyed 721 companies at the end of 2022. We asked a series of questions regarding speed and innovation and the technologies (for example, APIs and automation) and management mechanisms (such as management-style dashboards and data access) that companies used. We adjusted for industry differences and ran a series of regressions and other statistical analyses to create a management framework illustrating how top performers operate.

The management framework divides companies into two dimensions: innovation and time to market. We measured innovation based on the percentage of companies’ revenues from new products and services introduced in the last three years; respondents self-assessed speed, based on time to market, relative to competitors. We found that companies in our survey fell into four quadrants, which we named somewhat provocatively: Slow and Steady (32% of companies), Innovative but Slower (17%), Fast but Incremental (24%), and Fast and Innovative (27%). The Fast and Innovative companies performed much better with 9.8 and 11.6 percentage points higher on net profit margin and revenue growth respectively, compared to industry averages. The worst-performing companies were the Slow and Steady group, with 4.8 and 8.2 percentage points of growth and margin respectively, below their industry averages.

Surprisingly, the Fast but Incremental companies performed only marginally better than their Slow and Steady counterparts. And the Innovative but Slower companies performed significantly better than the Slow and Steady companies, with performance around the industry average on both growth and margin suggesting not only that speed is not enough but that innovation is typically more important.

The Drivers of Being Fast and Innovative

To better understand what enables a company’s pursuit of both innovation and speed, we looked at the enabling technologies and management mechanisms used most effectively by the companies in each quadrant in our framework. Statistically, we found four drivers of top performance:

In a digital world, no company can thrive on its own. Companies that are above average on innovation and speed collaborate more effectively, contributing to growth; and they are very effective at creating value from ecosystems and getting above-average revenues from channel partners. To keep innovation flowing, they provide suppliers with access to real-time data. They perceive a greater threat from digitisation, which drives them to innovate faster and focused on creating more value with digital for and from their customers.

Additionally, these companies have simplified work and organisation to succeed, shifting their management orientation from the more traditional command and control to coach and communicate. They understand there is no longer time to pass decisions up and down the hierarchy and instead empower local teams to make decisions within guard rails, with accountability supported by shared dashboards. The dashboards articulate value creation goals, identify the current levels of capabilities to achieve them, and measure if they are achieving them – for all to see so that when needed, people can make course corrections.

High Performance at Mercedes-Benz

Mercedes-Benz is a premier luxury car brand with a heritage of employing leading-edge technology. Mercedes-Benz’s strategy is focused on building dedicated electric vehicles, developing leading in-car software, and adhering to the highest standards of operational excellence. Following this approach, in 2022, Mercedes-Benz Group AG increased its earnings before interest and taxes by twenty-eight percent year-over-year and showcased the technical feasibility of a 745-mile-range electric vehicle with the company’s Vision EQXX car that relied on a less than 100kwh battery. Mercedes-Benz aims to be the leader in luxury mobility and to achieve this along with some of the most ambitious sustainability goals in the industry. The top management team is focused on the four drivers identified in this research—but with a Mercedes-Benz flavour.

Leadership while Simplifying Work

Leadership around technology at Mercedes-Benz is focused on creating digital mastery and entrepreneurial accountability to deliver on both speed and innovation. For all of its digital roles, Mercedes-Benz has established specific training paths to help people excel and continuously improve on their way to achieving expert status. As becoming a digital company requires more than employing experts, Mercedes-Benz has built communities of practice throughout the entire company, including for the production teams, to ensure digital fitness. The company accomplished this by moving to a coach-and-communicate leadership approach, which was especially necessary as the communities of practice are not reflected in the formal organisational structures.

Providing clear direction on what should be done is good—but explaining the why of doing things that way is better because it creates entrepreneurial accountability. At Mercedes-Benz, people are encouraged to think beyond the boundaries of their own responsibilities to care about and contribute to the overall result. Mercedes-Benz is in the process of introducing a product orientation for everything in the digital space. Going forward, work will be focused not only on project input parameters such as timelines and resources but also on the outcomes of the digital products, with the product owner fully accountable and empowered. This new orientation has thus far enabled Mercedes-Benz to implement a full-fledged online commerce suite for more than forty markets in less than one year—an innovation that is driving revenue. The company set the ambition for its online commerce suite of “five clicks to buy, three clicks to finance,” which requires that the suite is backed by a significantly streamlined business model.

Leading-Edge Technology

Everyone talks about cloud technologies, and yet they are often referring to a narrow application of cloud focused on hyper-scale infrastructure. Mercedes-Benz, by comparison, employs cloud native as a technical ecosystem to develop and run software.

To achieve advanced software capabilities, Mercedes-Benz relies on modular applications rather than monolithic, inflexible systems to allow for more flexibility and maintainability. The company also uses highly automated tools for the delivery of new code to facilitate continuous deployment. To additionally enable speed and innovation via enhanced software capabilities requires on-demand infrastructure, which provides computing power that can scale as required; and reliability, by leveraging scaling to create redundancy so that faulty components do not become a single point of failure.

In a cloud-native environment, one team is in charge of development and operations (DevOps), producing an end-to-end understanding and accountability. This is the driver for simplifying and automating business processes—which in turn drives speed and innovation. Mercedes-Benz’s cloud-native approach to digital shop floor management enables a high level of resilience in production, even with an increasing number of disruptions in global supply chains. Every impact is displayed in real-time dashboards, supporting a zero-delay production programme. During the worldwide bottlenecks of certain semiconductors, these capabilities enabled Mercedes-Benz to optimise its production within a very short time, focusing on high-margin vehicles and thus protecting profits.

The Mercedes-Benz Operating System (MB.OS) allows for frequent updates to the in-car software, both for control units and entertainment features. All updates go through one cloud-native vehicle backend, which not only verifies the technical viability and release conformity of the update but also ensures compliance with different certification requirements in different countries. In addition, the cloud-native vehicle backend gathers data from vehicles in the field, allowing for feature or quality improvements. Under GDPR governance and provided that the customer has given consent, vehicle data can also be used to directly enrich the customer experience through additional digital services.

Data as the Guide

Mercedes-Benz uses data in various ways, including to make better decisions based on comprehensive data—targeting the development of predictive action (for instance, predicting maintenance needs for capital-intensive shop floor equipment) and the creation of improved customer services through knowing customers better—while observing all relevant data protection principles. For example, having customer data available at every touchpoint, whether physical or digital, allows Mercedes-Benz to make a “next best offer”—an action identified using predictive analytics—which contributes to revenue growth. Mercedes-Benz can use data from a customer’s interactions with the company and the telemetry of their vehicle to predict and notify about the car’s maintenance needs. For example, if you are a sporty driver, they can contact you at a less-than-standard interval to visit a Mercedes-Benz repair shop to change your tyres or brake pads. Mercedes-Benz’s customers decide for themselves which services they want to use and which data to pass on to the company and not.

Also, Mercedes-Benz is establishing a comprehensive digital representation (a digital twin) of vehicles throughout their entire life cycle, starting with the order of the vehicle and extending from production through recycling of the used vehicle. The target is to radically speed up the time to market, reduce costs in development and operations, and further enhance the customer experience. For example, when developing a quick or even predictive reaction to potential issues on the road, the digital twin can help Mercedes-Benz go faster and innovate. Mercedes-Benz’s ambition is that the first physical vehicle built will be the one used for certification.

An Innovation Ecosystem

Mercedes-Benz has created an ecosystem around its customers. The company combines the data from sources such as online and offline touchpoints and car usage to not only make the next best offer but also to interact with customers more often, in particular through the Mercedes me connect app or other digital services based on MB.OS. These interactions create even more data that help in many ways including a first-class charging-and-driving experience. By aggregating all available vehicle data like state of charge and energy consumption, including environmental information such as wind speed, a whole new level of individual range prediction can be achieved. Additionally, Mercedes-Benz has partnered with a number of other companies, such as hotels, to create special offers for Mercedes-Benz customers. Customers can rely on the fact that data protection is of great importance to Mercedes-Benz and that the company ensures a responsible and transparent handling of data.

What It Takes to Succeed

We found that in today’s digital world, top performers are both faster to market and innovating to generate new revenue. We suggest you have a conversation about where your company is today and where you’d like to be on our 2×2 framework. Being excellent at both enabling technologies like APIs and management mechanisms like value-tracking dashboards was common in the top-performing companies in our research. Digital enablement of both speed and innovation is a great opportunity for you to reinvent how your company does business—to become the company you have always wanted it to be.

This article is based on “Going Faster Is Not Enough; Add Innovation To Outperform,” MIT CISR Research Briefing, April 2023 by Peter Weill, Jan Brecht and Stephanie L. Woerner.

About the Authors

Peter Weill, PhD, is an MIT Senior Research Scientist and Chairman of the Center for Information Systems Research (CISR) at the MIT Sloan School of Management, which studies and works with companies on how to transform for success in the digital era. MIT CISR has approximately 75 company members globally who use, debate, support and participate in the research. Peter’s work centres on the role, value, and governance of digitisation in enterprises and their ecosystems and has coauthored 10 books. Ziff Davis recognised Peter as #24 of “The Top 100 Most Influential People in IT” and the highest-ranked academic.

Jan Brecht presently serves as the CIO of Mercedes-Benz Group AG and Mercedes-Benz AG, overseeing global IT operations across divisions, brands, and markets. Prior, he held roles at Adidas Group, culminating in CIO and Head of Global Supply Chain. Beginning at Daimler-Benz AG in 1997, he’s led various IT roles, including management positions in automotive sales, financial services, production, and engineering. Brecht holds a Master’s in Communications Technology and is associated with the German National Scholarship Foundation. Outside work, he’s a family man who enjoys hiking, skiing, and 20th-century novels.

Stephanie L. Woerner, PhD, is a Principal Research Scientist at the MIT Sloan School of Management and Director of MIT CISR. She is a renowned researcher and speaker, and coauthor of Future Ready: The Four Pathways to Capturing Digital Value and What’s Your Digital Business Model? Six Questions to Help You Build the Next-Generation Enterprise, both published by Harvard Business Review Press. Stephanie studies how companies use technology and data to create more effective business models as well as how they manage the associated organisational change and governance and strategy implications. Stephanie’s research has appeared in MIT Sloan Management Review, Harvard Business Review, CNBC, Forbes, Chief Executive, and CIO.

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By learning to proactively manage supplier risks through digital strategies, companies can mitigate the adverse effects of disruptions, enhance supply chain resilience, and stabilise cash flows in the face of uncertainties.

“A strategy is necessary because the future is unpredictable.” — Robert Waterman

Reducing cash flow volatility has always been a strategic goal for companies across various industries. A key aspect of achieving this goal is implementing proactive risk management strategies that anticipate and address potential supply chain disruptions.

Supply chain disruptions can have a significant impact on a company’s cash flow. When a disruption occurs, it can lead to delays in the supply of raw materials, components, or finished products. These disruptions can result from various factors such as natural disasters, geopolitical events, logistics issues, supplier bankruptcies or labour disputes, and lead to production stoppage and revenue losses.¹ The consequences of these disruptions can affect a company’s financial performance and cash flow stability.

However, with the advancements in digital tools and technologies, businesses can now leverage these resources to assess supplier risks and enhance supplier relationship management. The ability to proactively manage supplier risks through digital strategies can help mitigate the adverse effects of disruptions, enhance supply chain resilience, and stabilise cash flows in the face of uncertainties.

In this article, we explore how digital strategies can play a crucial role in proactive supplier risk management, enabling companies to mitigate risks and optimise their supply chains in anticipation of potential supply chain disruptions.

Leveraging Digital Tools for Risk Assessment

With the increased availability of digital tools, firms can now assess supplier risks more effectively. By leveraging data analytics and intelligence platforms, companies can gain deeper insights into their supplier base, identifying potential risks and vulnerabilities. These tools provide a comprehensive overview of supplier performance, financial stability, and compliance with regulatory changes, allowing businesses to make informed decisions and implement proactive risk mitigation measures. The landscape of supplier intelligence platforms keeps evolving, and at the time of writing this article, the major players are listed in Figure 1.

Integration of Supplier Relationship and Risk Management

Leading companies are recognising the value of integrating supplier relationship management with risk management capabilities through the utilisation of digital tools. By combining these functions, businesses can enhance supplier visibility and establish stronger partnerships with their suppliers. Digital platforms enable the seamless sharing of information, fostering collaboration across functional areas and facilitating the proactive identification and mitigation of supplier risks. This integration ensures that risk management becomes an integral part of the supplier relationship management process.

Actionable Insights and Targeted Sourcing Strategies

The adoption of data analytics tools such as Craft further enhances supplier visibility and enables the transition from raw data to actionable insights. By analysing large datasets, companies can identify patterns and trends, allowing for more targeted sourcing strategies. These strategies can consider global regulatory changes, ensuring compliance and minimising supply chain disruptions. Digital tools empower businesses to optimise their supplier base, select the most reliable partners, and proactively manage risks associated with sourcing and procurement.

Using Generative AI to Manage Supplier Risk

With the increasing availability of generative AI tools like ChatGPT, a new source of supplier risk intelligence has become available at the organisations’ fingertips. AI offers valuable capabilities for managing supplier risk by analysing unstructured data sources, web crawling, enhancing supplier evaluation, and improving supply chain forecasting accuracy. However, while AI is still in its infancy, human expertise and judgment remain crucial for validating insights and making strategic decisions based on the generated information.

Supply Chain Finance and Risk Mitigation

Supply chain finance offers opportunities to reduce the risk of bankruptcies by optimising payment terms for both small suppliers and large buyers. For example, PrimeRevenue is a service provider which enables businesses to improve cash flow, provide working capital to suppliers, and foster financial stability within the supply chain. However, caution must be exercised when implementing supply chain finance programmes, as there are instances where it has led to risky situations (think of Carillion or Greensill). It is essential to establish robust risk management frameworks and evaluate the potential impact of supply chain finance on overall supplier risk exposure using digital tools and information available through RapidRatings, Moody’s or S&P Capital IQ.

Establishing Risk Appetite and Allocating Risk Capital

Finally, the implementation of economic supply chain risk capital allows companies to define their risk appetite, allocate risk capital to business units, and evaluate performance on a risk-adjusted basis.² By quantifying risk exposure and assessing potential losses, businesses can make informed decisions regarding risk management strategies. Digital tools can assist in measuring and monitoring risk metrics, providing real-time insights into the effectiveness of risk mitigation efforts. An example of a platform providing this emerging capability is the RAAD360’s partnership with Microsoft.

Putting Strategy into Action

In an era of increasing supply chain complexities and uncertainties, digital strategies play a vital role in proactive supplier risk management. By leveraging digital tools, companies can assess supplier risks more effectively, integrate risk management with supplier relationship management, gain actionable insights for targeted sourcing strategies, and optimise supply chain finance practices. Furthermore, the implementation of economic supply chain risk capital empowers businesses to establish risk appetite, allocate resources efficiently, and evaluate performance in a risk-adjusted manner. By adopting these digital strategies, organisations can enhance their ability to mitigate supplier risks, reduce cash flow volatility, and achieve long-term success in today’s dynamic business environment.

The execution of digital strategies needs to be accompanied by finding internal stakeholder buy-in, which can only be achieved if the digital tools in question are recognised by the business leaders. This necessitates close coordination among various functions beyond procurement, supply chain and technology and requires skilled resources who understand the data and the consequences of data-driven decision making.

About the Author

Dr. Kamil J. Mizgier is the former Global Supplier Relationship and Risk Management Leader at Dow with 15 years of experience in implementing risk management strategies across industry sectors. Before this role, he led enterprise risk modelling projects and teams, among others, at BNY Mellon and UBS. He has published more than twenty academic and practitioner journal articles on risk management and is a frequent public speaker. He obtained his master’s degree in applied physics at the Warsaw University of Technology and a PhD in supply chain management at ETH Zurich.

References

1 Schlegel, G.L., & Trent, R.J. (2014). Supply Chain Risk Management: An Emerging Discipline (1st ed.). CRC Press.
2 Mizgier, Kamil J. (2022): The Path Forward to a Unified Risk Framework. The European Business Review, January-February 2022, pages 8-11.

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After helping kickstart digital transformation across the MENA region, Cedar Rose is now a mature company ready to thrive in a post-Covid business world. Founder Christina Massaad reflects on her 20 years at the helm, shares how to inspire future leaders and offers key lessons for managing a remote working team.

What key qualities set Cedar Rose apart and will help guide the company through this uncertain future?

I’m proud to say that Cedar Rose is a proactive, dynamic, innovative and agile business. For the past 20 years, my team has gathered and transformed data while building quality, reliable credit and compliance solutions for our customers. We love being provocative market disruptors by merging hard-to-reach data with artificial intelligence and machine learning to create new markets and services. We will keep investing in top-end translation technology and data standardisation to give us a unique multilingual, multifunctional database covering the Middle East, Africa and Asia. All this means we offer accurate global coverage for automated credit and compliance assessments.

This combination of innovation, future thinking and agility along with years of experience – including coping through several regional disasters – gives Cedar Rose the edge it needs to survive and thrive after this unprecedented global crisis.

Has the Covid-19 pandemic made it more difficult for Cedar Rose to collect data and identify trends?

Like most companies, we had to adapt. Cedar Rose has offices and people working remotely around the world. A large percentage of the team were based in Lebanon, which was suffering from street protests long before the pandemic started. So, they were accustomed to working from home already. Our Business Continuity Committee was regularly discussing crisis plans and preparing for disaster recovery. Robust forward planning and preparation has protected us through many crises including the 2006 war in Lebanon, lengthy power outages in Cyprus in 2011 and the economic crisis in 2013 – to name a few. We were prepared for the worst and had a committee to oversee the smooth switch to home working. Initially, working from home complicated our research and outreach since companies and government offices were often closed too. But within a few weeks most organisations had caught up. It also helped that much of our revenue now comes from online automated solutions which remained unaffected by the Covid crisis.

As for identifying trends, unprecedented events will always improve the predictive analysis since now there is historical data to build on. Sadly, according to several sources, climate change may help create more pandemics in the future, but each of us – governments, businesses and individuals – now have a better idea how to react next time.

Very generally, how did the pandemic impact your operations in the MENA region (Middle East, North Africa)? What lessons do you have for business leaders there?

It really depends on the country. For example, the pandemic exacerbated one of Lebanon’s worst economic crises. On the other hand, the United Arab Emirates handled the pandemic well. Even back in March 2020 when I last visited Dubai, there was already hand sanitizer near every lift or reception desk and visitors from high-risk countries were tested at airports.

Many MENA countries have rapidly advanced their digitalisation, e-commerce and compliance over the past year, but of course this also led to an increase in fraudulent behaviour. One lesson is that stricter compliance measures must be introduced alongside the introduction of any e-commerce, neo-banking and mobile payments technology. Thankfully, most MENA governments are now enforcing their anti-money laundering and counter-terrorism financing laws. That means business leaders must know to whom they are extending credit or making payments. It also pays to check if the ultimate beneficial owners or companies are located in high-risk countries or perhaps even sanctioned, red-flagged or politically exposed. A few years ago, automated checks weren’t available in the MENA region, but today KYC/KYB and credit and compliance checks are fast and cheap. 

Has the Covid-19 pandemic made the MENA area more or less attractive for business? What sectors were most affected?

The worst affected sectors in MENA are the same as those affected everywhere – the travel and tourism, hospitality, leisure, health, fashion, beauty, manufacturing, real estate, construction, oil and gas, sports, automotive, transport and retail industries are all hurting. But some sectors are expanding unusually fast, such as insurance, e-commerce, digital advertising and data. Europeans might scratch their head about this, but consider that online grocery shopping is only about a year old in this region. Online services have quickly become a necessity for many, as have restaurant deliveries and takeaways. Smartphone app delivery and couriers are a big part of this boost.

What did the pandemic teach you about the future of business?

So many lessons! Any business owner or manager who has come through this experience will have learned a lot, and that will make them a better leader in whatever they do. We can never be over-prepared. We must always plan for the worst and strive for the best. That means planning ahead at least two or three years for your cash-flow, growth strategies and future project plans. In my opinion, a current cash-flow forecast is the most important business tool and can be done with a fairly simple Excel spreadsheet. It must always be based on a worst case scenario. You should have enough cash for a few months in case things are worse than imagined while you work to swiftly cut costs. On the plus side, a forecast lets you know when things are going well so you can afford to expand.

Another lesson is to stay within sensible credit limits and be firm with credit control. There is always a fine balance in keeping a good supplier-customer relationship and actually getting paid for supplies. Remember that a great customer relationship is worthless if you aren’t getting paid. Make sure the terms of agreement are clear from the start, enact a strict credit policy and tell your sales and finance teams about the customer terms. In most cases, accounts payable teams will prioritise paying any businesses that applies a late payment interest fee, or they will get on the phone to chase down an outstanding invoice. Don’t be afraid to be one of those businesses! Setting sensible credit limits is the main purpose of credit reports. They also reveal the risky customers and those with the greatest potential.

Do you worry that businesses may be focusing too much on Covid-19 and missing other factors?

Yes. Covid-19 will have a dramatic economic effect for at least another year. That means supplies might not arrive, companies may not get paid and some might even go into liquidation. All of these things cause a domino effect. Business leaders must take precautionary measures like getting good data about their customers and suppliers and keeping a close eye on their cash-flow. European businesses with a large exposure to the UK (and vice-versa) should be prepared for Brexit. This break-up of the economic union could not have come at a worse time for businesses on both sides of the Channel. Don’t let coping with Covid mean you are less prepared for other challenges like this.

Most people wisely treat Covid-19 as a threat. But do you see any opportunities arising out of this pandemic?

I do indeed. Positives are everywhere – if you know how to look for them. For example, prior to the pandemic, online grocery shopping was almost unheard of here in Cyprus and most restaurants lacked a delivery service. Many companies have since developed electronic ID, web development and marketing skills. They have also hired vehicles, delivery services, warehousing and logistics. Businesses like ours moved to 100% remote working and created fresh opportunities in IT, online training, project management, virtual offices and cloud servers. We ordered more deliveries from florists, couriers and gift hamper companies. I believe remote working will continue for many people in the long term which will bring a host of other profitable opportunities for both B2C and B2B businesses.

How has the pandemic changed the qualities it takes to be a good leader?

I think a leader needs to be firm, organised, consistent and proactive with a good degree of emotional intelligence. You won’t always get it right the first time, so a leader must admit mistakes and be prepared to quickly change tack. The pandemic has exposed indecisive and disorganised leaders and those who can act quickly and firmly. The numbers of virus cases and deaths in each country speak for themselves.

Emotional intelligence is now a critical leadership quality due to rise of remote work. Leaders must keep remote teams engaged and be careful to notice when staff are struggling with loneliness and depression or may be losing motivation. Employee engagement is tougher today, so it is much more important to get it right.

Are women well represented at the top echelons of your industry and among business leaders in general?

Women are fairly well represented across the business information industry, although most of the top managers are still men. That seems to be the case in most sectors. But over the last ten years, times are changing across the MENA region which tends to be way behind Europe in this issue. Yet if a woman does reach a high position, her pay may be lower than a man’s for the same role. This is something every company must address.   

Do you think it is important for young women to have aspirational female role models like yourself who prove it’s possible to reach the top levels of business?

I believe women can be inspired by male role models just as much as by other women. But yes, there seems to be fewer female role models in business. Most business leaders I look up to are male, but I never saw that as a problem. What really matters is the example set by a role model. Having said that, the highest level of praise a member of my team can give me is that I inspire them. Inspiration goes both ways, though. I am often inspired by colleagues pushing themselves beyond expectations. We have many such people in our company, both male and female. Our company motto “Strive for Excellence” motivates us to become the best version of ourselves by hitting targets and developing new skills. Once you have that business culture, everyone can inspire each other.

Do you have any advice for women starting their careers?

Don’t be intimidated by anyone. If you think you are weaker because you are a woman, or for any other reason, then you are already disadvantaged. Be confident in your abilities – and if you are not confident then improve your skills or change jobs. Your managers and colleagues will respond positively to genuine and humble confidence. And if you believe in yourself, then it’s more likely your boss will trust you with greater responsibility over time. Confidence coupled with great performance can overpower discrimination and turn it into respect. I’ve seen it happen many times.

Is the MENA region being digitally transformed at the same rate as other parts of the world?

Digital transformation in the MENA region is happening at an even faster rate than in Europe or the US because the region was a long way behind. MENA countries are able to skip a lot of the early steps because the regulations, technology and data were already tested in developed countries over decades. The region has rapidly advanced its healthtech, agrotech, fintech and the entire tech family while embracing green energy to power them.

It’s a thrilling time to be based here. I’m proud that Cedar Rose several years ago helped to enable this digital transformation by developing expertise in gathering, translating, cleaning and structuring data for the region and making it available in real time to our clients around the world.

Many organisations are finding clear advantages to working remotely. What implications will this have for employee well-being if this trend continues beyond the pandemic?

While we should monitor employees’ mental health since they can’t socialise in person with colleagues, working from home has positive advantages as well. For instance, there is less peer pressure so the need to keep up to date with fashionable clothing, hair, shoes or even body weight is somewhat negated. This may seem trivial, but these issues can put a lot of mental pressure on young people especially. Remote working also creates less space for gossip and the formation of cliques. Employees are also happy about not spending hours in traffic or squeezed into public transport each day. This should give people less stress, less exposure to pollution, more money and more rest time.

Even without the pandemic, most people would still prefer the freedom of working from home because they can still socialise, go shopping, go to the gym or the soccer match in their free time. But since we can’t do most of those things now, it’s crucial for employers to regularly communicate with their staff to notice any mental health issues due to isolation. The “It’s okay not to be okay” message must be loud and clear so staff can reach out for help if they need it. Staff should also be encouraged to take enough rest time. Lockdowns and 12-hour workdays without regular breaks is a recipe for disaster in the long term. People must know it’s acceptable to switch on and off at the usual times, take days off and speak up when feeling overloaded.

Now that you are “taking a back seat” as non-executive director at Cedar Rose, what achievements are you most proud of and what are some of your biggest lessons so far?

I’m extremely proud to lead a socially responsible, diverse and reputable company. After 24 years in business, Cedar Rose is trusted by Fortune 500 businesses and the “Big Four” auditing firms. Considering that until recently we’ve covered one of the hardest regions for data – MENA – that’s a great accomplishment. Now that we have global coverage, the potential is so much greater and I’m very positive about the future of Cedar Rose.

It’s tough to choose the most important lessons. I’ve learned so much about perspective, marketing, business strategy and working among different cultures. But the most important lessons are to always be prepared for the unexpected, be aware and in control of your finances and never put too much trust in any one person. Some harsh lessons, sure. But with experience comes the wisdom to calmly deal with extreme situations, stay focussed and let go of issues that will only bring you down. 

What future goals are you the most excited about reaching?

I’m currently writing a book about the adventures my husband and I have been through. We’ve had quite a few both in business and in our personal lives. I hope the story of a working-class girl from the London suburbs and a refugee from Lebanon who built a successful business to improve global security will help inspire others.

Apart from that I’m excited about the potential of this mature company which has such strong foundations. Cedar Rose is ready to start a new, much faster, more automated phase. Our investments in automated credit scoring and electronic ID are bearing fruit and the new CR Comply tool can complete research tasks in seconds rather than hours or weeks. It’s game-changing for our customers who can on-board clients at a fraction of the time and cost. 

Finally, do you have a motivating message for aspiring leaders?

The world is at a turning point and it’s an exciting time to be alive. We have survived a difficult period and gained unique wisdom, strength and experience to pass on to future generations.

Leaders don’t need to be in the front of the pack to show the way. You can push from behind, support from below and sometimes just walk side by side. So, strive to be the best version of yourself and others will be inspired to follow you.

This article was originally published on 14 March 2021.

Executive Profile

Christina Massaad is a Non-Executive Director at Cedar Rose, having co-founded the group of companies with her husband, Antoun Massaad in 1997. Until the end of 2020, Christina was Managing Director at Cedar Rose and co-managed the operations of the company in the UK, Lebanon, Cyprus and UAE.

The post Diamonds In The Rough: Spotting Opportunity During A Crisis appeared first on The European Business Review.

Finland is experiencing dynamic growth in the number of companies that are developing and / or using artificial intelligence (AI) in their business. This is illustrated by comparing the total of 947 such companies in 2019 with only 358 in 2017. Furthermore, AI-focused companies may be found across the country, but three out of every four companies in Finland that are developing or using AI are, nonetheless, located in Uusimaa region (ETLA 2019). The body of companies developing or employing AI is currently rather homogeneous and mainly composed of software development and programming companies. However, efforts are being made to grow the AI capabilities of Finnish companies across sectors, with a special focus on the SMEs that form 98 per cent of the country’s registered businesses.

KEY TAKEAWAYS

Corona has invigorated digitalisation and the demand for AI-based solutions

Finland’s strength in the rapidly developing field of AI is the agile business environment that enables and supports collaboration between companies, research and education organisations, and society at large (Ministry of Economic Affairs and Employment 2017). Finland’s roadmap for AI (Technology Industry of Finland 2020) brings forward four building blocks.

First, it calls for responsibility to be built in at all stages of development and highlights that AI is not a value in itself. In Finland, AI is there to solve challenges relevant to a socially and ecologically sustainable society, which fuels positive discussion and promotes the use of AI solutions. Furthermore, encouraging companies to develop digital web-based service solutions in addition to physical products helps to safeguard business in situations such as the COVID-19 pandemic and supports reaching the goals on carbon neutrality.

Second, creating and sharing relatable AI stories promotes understanding and acceptance of AI. As decision makers in companies and other organisations become familiar with the potential of artificial intelligence, readiness to invest in the new technology increases. These investments will further create new positive examples that will spread through public debate and networks and inspire other companies.

Third, the aim of Finland’s AI ecosystem is to be diverse and open. The functioning artificial intelligence ecosystem is characterised by close and mutually beneficial cooperation between research, industry, start-ups, and public administration. A vibrant ecosystem attracts motivated and diverse experts from diverse backgrounds, which in turn creates more inspiring activities, investments, and successes.

Fourth, AI enables and positively contributes to business renewal, with AI viewed as a part of continuous development. This is reinforced by enthusiastic people in organisations who, as a result of getting support to operate and experiment, are able to obtain credibility and resources. As the first AI successes are made visible within organisations, understanding of the technology spreads. Organisations learn to evaluate AI applications from a business-oriented perspective and invest in developing AI capabilities in a balanced way.

Five AI trends in Finland to keep an eye on

Historically, Finland has strong technical and IT skills to build upon and is, therefore, one of the AI pioneer countries in Europe. The work is being approached from multiple angles, five of which are introduced next.

1. Making AI available to SMEs. AI contributes to the adaptability to change associated with the digitalisation of SMEs. However, SMEs across Europe struggle to embrace AI, although it is they who have the greatest potential to benefit from AI. This is the challenge and the opportunity recognised at a European level. On a positive note, numerous AI initiatives, programmes, and accelerators are currently being developed and launched to tackle the issue (example: AI-TIE). There is also a greater interest on the part of SMEs part in AI in comparison to, for instance, a couple of years back. This is accompanied by a willingness to commit to learning about AI and embracing it as a part of business processes and new product and service development.
   
2. The “train the trainer” principle in equipping business advisors with AI understanding. Chambers of commerce, business development centres, and start-up hubs are homes for services that are offered to companies locally. This implies constant dialogue with the company networks on behalf of business advisors employed by these organisations. Increasing the business advisors’ understanding of AI helps to make it a part of their company interactions – spreading the knowledge about AI-related business opportunities.
3. Creating industry-specific knowledge and skills in AI. Taking the AI discussion from the general level towards industry-specific training, mentoring, and accelerator activities is one of the key current AI trends. This enables the creation and deepening of industry-specific AI expertise and thus supports companies operating in the industry. Recent examples of this include AI-TIE AI Accelerators in the cleantech sector, health and medtech.
4. The social and human-centric dimension is essential. There is an ongoing discussion and research stream dedicated to understanding how AI impacts work life at the level of individuals, teams, and organisations. The human-centric view is also taken in the development of AI-related legislation within the EU.
   
5. Cooperation and ecosystem focus. Current policies on the development of innovation ecosystems at the EU level emphasise the extension of the concept of innovation to include social, technological, and operational innovations as part of the ecosystem idea. This is considered in the current AI RDI projects and in building AI ecosystems, in which SMEs, large companies, educational institutes, and other key players work synergistically together and offer their products and services. Their aim in doing so is to increase business and knowledge transfer between smaller and larger, more-experienced and less-experienced organisations.

In conclusion, AI-related work in Finland takes a holistic view, starting with individuals and human impact and moving towards larger constructs, such as ecosystem-level thinking and action. The interest and the motivation towards AI have advanced in the recent years and are currently high among Finnish companies and SMEs especially. It is, therefore, the ongoing task and aim to create the conditions to match companies’ AI pursuits with the necessary education and support tools, expertise, and networks.

This article was originally published on March 20, 2023.

About the Authors

Dr. Anna Lahtinen, DBA, Senior Researcher, Entrepreneurship and Business Renewal, Haaga-Helia University of Applied Sciences, Helsinki, Finland. Anna specialises in the transformation of work life from various perspectives, including the impact of AI, robotics and new technologies, innovation management and entrepreneurship, evolution of psychological contract, gender roles and women’s careers. Anna has close to 20 years of professional, industry, entrepreneurial, start-up and academic experience in Finland, across Europe and globally. Anna is an internationally published scholar and a recipient of the “Academic Paper Most Relevant to Entrepreneurs Award” presented by the United States Association for Small Business and Entrepreneurship. She is a long-term affiliate and invited professor with top international Triple Crown accredited business schools. Her ongoing RDI projects include understanding the role of artificial intelligence, robotics and new technologies in work life, including individual, team dynamics and organisational levels. See, for example, AI-TIE – AI Technology Innovation Ecosystems for Competitiveness of SMEs. Anna’s other recent research and development contributions have focused on gender as a factor in financial compensation and career progress, entrepreneurial leadership as a key competence of knowledge workers, circular-economy digital marketplace creation, and cross-industry co-development and co-innovation work that enables business renewal.

Heikki Kallasvaara holds an MSc degree in Biophysics and currently serves as Senior Advisor at the Helsinki-Uusimaa Regional Council, which he joined in 2016. His tasks include policy development, EU-level funding and project support, especially in the field of industrial modernisation and innovative services. Helsinki-Uusimaa Regional Council has funded several projects addressing Digital and Green Transitions. Prior to this task, Heikki held the position of director at the University of Helsinki, Research and Innovation Services. His experience also includes a five-year stint at the Directorate General for Research at the European Commission, where his responsibilities covered both policy and programme development (RDI), especially on new and evolving technologies. Heikki started his career in the private sector, with management positions in the diagnostics industry. This early insight into a global, cross-cultural, and goal-oriented business environment served him well in his later public sector duties. He has served as a board member in two high-tech start-up companies and one consultancy.

References

1. ETLA (2019). “Digital Barometer 2019”. Facts and statistics credit: Finland Statistics Center, company register, Vainu.io; ETLA calculations: link, visited 8 September 2021.
2. Ministry of Economic Affairs and Employment (2017). “Finland’s Age of Artificial Intelligence”. Issue 47/2017: link, visited 8 September 2021.
3. Technology Industry of Finland (2020). “AI Finland in 2021”. Published 18 December 2020: link.

The post AI in Finland: From Relatable Stories Towards AI Ecosystems appeared first on The European Business Review.

While they may not be able to prevent pending economic crises such as those resulting from the COVID-19 pandemic, businesses can use them as launch pads to growth by becoming resilient and doubling down on growth instead of cutting costs.

Worried about a crisis? You might think it’s coming if you add in the Ukrainian war, inflation, a remnant COVID-19 pandemic, and burgeoning private debt. But in reality, there is also a bright picture to contrast with this bleak outlook in that the war may soon be over, China has reopened its economy, and inflation is levelling off slightly in some parts of the world.

Rather than spending too much time guessing at the next crisis, its size, nature, and timing, business leaders should instead teach their organisations to become resilient. In analysing the numbers from numerous crises, including research conducted in cooperation with Accenture Research at the time of the COVID-19 pandemic, we have discovered three important elements for leaders to take notice of.

The first is that resilience, or the ability to bounce back, is both a rare and long process. Brands like Hertz, JCPenney, and J.Crew went out of business in the first few months of the COVID-19 pandemic. In previous crises, 17% of publicly traded companies have gone public, either because they went bankrupt, went private again, or were bought out. And while most firms survived, it took between 1.5 and 3 years for firms and economies as a whole to recover the losses incurred during a major shock.

The second insight is that crises often redefine the status quo, with new winners emerging, and old winners becoming new losers. The falling angels are numerous, about 25% of total companies, but new rising stars are also visible. In fact, the idea is that resilience is a strategic complement to do better than before the crisis: what academics call bouncing “forward”. Resilient companies are those that use the crisis as an opportunity. Remember Andy Grove, then CEO of Intel, when he said that “crises make great companies better? At the time, Intel nearly collapsed because of a bug in the Intel Pentium processor. In fixing the bug, Intel also radically reinvented its partner ecosystem, while developing its Intel Inside Program that allowed the company to rebound and dominate the semiconductor market for years.

A final point concerns the ingredients for resilience and performance. Many studies, including consulting firms, will preach the virtue of agility, the ability to innovate or, the need to digitise. But the reality is more subtle than that. If a leader wants resilience to drive the new trajectory of his or her company, that same company will need to invest in the entire portfolio of capabilities (agility, innovation, digitisation, sustainability, and flexible work practices). And the best time to do so is during a crisis –precisely when rivals are scared, retreating, and overly focused on survival, instead of preparing for the next competitive battle. As Winston Churchill once said, “a good crisis should not be wasted.”

In practice, however, the typical company has a narrow set of capabilities and tends to retrench during a crisis. Winners are already preparing for the next crisis, and are eager to invest in difficult times when rivals have morphed into victims of turbulence. Best companies are not necessarily good at predicting crises, rather they focus on excelling in rising, and not falling, when the crises hit. Are you that breed?

This article is originally published on May 16, 2023.

About the Author

Jacques Bughin is CEO of machaonadvisory, and a former professor of Management while retired from McKinsey as senior partner and director of the McKinsey Global Institute. He advises Antler and Fortino Capital, two major VC/PE firms, and serves on the board of multiple companies.

References

• Barnichon, R., Matthes, C., and A. Ziegenbein (2018). The Financial Crisis at 10: Will We Ever Recover? FRBSF Economic Letter, 19.
• Bughin, J., Berjoan, S., Hintermann, F. and Y. Wong, (2021), Is this Time Different? Corporate Resilience in the Age of COVID-19, In-cite, working paper, Solvay Business School, June.
• Gulati, R., N. Nohria, and F. Wohlgezogen (2010), Roaring Out of Recession, Harvard Business Review, March.
• Hirsch, S. (2018). Succeeding in the Long Run: A Meta-regression Analysis of Persistent Corporate Earnings. Journal of Economic Surveys, 32(1), 23-49.
• Mann, M., & Byun, S. E. (2017). Retrenchment or Investment? Recovery Strategies in a Recession. Journal of Business Research, 80, 24-34.
• Maury, B. (2018). Sustainable Competitive Advantage and Profitability Persistence: Sources versus Outcomes for Assessing Advantage. Journal of Business Research, 84, 100-113.
• Ollagnier, J.M, Berjoan, S., Bughin, J. and Xiong, Y. (2021) Why Fixing the Planet is Also About Seizing Business Opportunities, European Business Review, March.
• Romer, Ch. and D. Romer (2017), New Evidence on the Aftermath of Financial Crises in Advanced Countries. American Economic Review 107(10), pp. 3,072-3,118.
• Teece, D., Peteraf, M., and S. Leih, (2016). Dynamic Capabilities and Organizational Agility: Risk, Uncertainty, and Strategy in the Innovation Economy. California Management Review, 58(4), 13-35.

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In the fiercely competitive world of the post-pandemic travel industry, travel suppliers are looking to provide a leaner, more finely targeted service for their customers. Using state-of-the-art technology, DART enables suppliers to offer a one-stop shop for all their clients’ travel needs. Riversoft CEO Alex Kuo fills in the details.

Hello, Alex. Glad to have you with us again today. We have previously discussed the DART project. Can you tell us more about it? What does the acronym “DART” mean?

DART means “Dynamic Attention Recommendation Technology” for travel.

Since travellers’ needs change rapidly, Riversoft uses its in-house-developed Dynamic Attention technology to comprehend their needs, match them with the real-time inventory, and recommend travel products via the website, instant message channels, and emails.

Why did Riversoft develop this unique recommendation engine? What challenges facing the travel industry are you trying to overcome through DART?

After the epidemic, there are several pain points in the tourism industry.

1. The labour shortage is now a headache for the industry.
2. Travel suppliers have limited digitisation and experience difficulty providing travel products with the rapidly rebounding travel market demand.
3. Google says it intends to phase out third-party cookies in 2023. In the future, it will be hard to know the tendencies and profiles of individual travellers. It will also mean that the travel industry pays higher advertising costs to find the right customers.
4. Even online travel agencies do not allow travellers to purchase everything they need for travel in one stop.

Because of these difficulties, Riversoft developed its DART product to solve these pain points.

Tourism is a very fast-paced industry with many interconnecting variables in play. How does DART make accurate recommendations in a cookie-less environment?

First, we use the User Demand Profiling Engine to analyse the conversations of travellers in the chatbot and the behaviour on the website.

Second, we embed the concept of dynamic attention in the Travel Ontology Inference Engine, which trains customer behaviour data and needs via deep-learning models.

We can match the results to the travel products and services accordingly.

Lastly, we use Workflow Engine to present customised recommendation results to users and provide the most appropriate presentation of the results according to the user interface.

What are the major innovations behind the DART project? What is its critical success factor?

Riversoft has pioneered combining NLP technology, millions of items of real-time travel inventory, high-speed dynamic package technology, and CaaS (conversation as a service) in DART.

We think the key factors are listed below:

1. Riversoft builds its own ontology to develop its NLP kernel and make progress in the medical and CaaS fields.
2. Our team has more than ten years of domain knowledge in the travel industry.
3. We have a solid cloud-based inventory with a fast caching speed of auto-provision capability.

How can DART optimise the current booking experience for travellers? How can it increase the time visitors spend on the travel booking website?

To TAs and OTAs, embedding DART can significantly improve efficiency, upgrade their website function, and enhance the application of instant messaging channels. DART provides accurate business insight reports to TAs and OTAs and assists in finding market opportunities. More importantly, DART can assist TAs and OTAs in selling more products and increasing the lifetime value of each customer.

At the same time, travellers can chat with our AI bot, so DART can analyse the conversation and user behaviour on the website and provide travellers with precise recommendations to accelerate the process of finding everything they need and purchasing it all in one stop.

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• What’s Next for TravelTech? Insights from Riversoft CEO, Alex Kuo
• Riversoft Makes the Connection: From Travel Services to Medical Data Via NLP
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• Robot Travel Agency: A Warm and Technological Welcome

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