Business Model Innovation
Speakers who challenge how organisations create, deliver, and capture value in shifting markets
Boards want the upside of founder-led growth without the chaos that usually comes with it. Most corporates cannot tell the difference between a genuine scaling business and one that simply spends fast. The gap between how operators build and how incumbents invest is where value is lost.
Purpose-driven business is now a crowded marketing category, and most of it rings hollow. Customers and employees can tell when a giving programme is bolted onto an unchanged commercial model. The harder question is whether giving can be the engine itself, and what happens to the founder when the model is tested at scale.
Most marketing organisations collect more data than they act on and run more campaigns than they can defend. The gap between dashboards and decisions has widened with generative AI, not closed. Senior leaders need a way to connect customer intent, measurement and commercial outcomes without handing the argument to the loudest vendor in the room.
Generative AI is trained on what people have already created, then competes with them using it. Boards now face a question with no settled answer: who owns the human capability a machine has absorbed, and what does the company owe the workforce it displaces? Most AI strategy stops at deployment and ignores the legal and economic claims forming underneath it.
Corporate innovation budgets keep rising, yet most large organisations still struggle to convert startup engagement into commercial outcomes. The tension is structural. Procurement cycles, risk committees and quarterly targets collide with the speed and failure tolerance that make startups useful in the first place, and leaders need a clear map of which engagement model actually fits which strategic problem.
Incumbent financial institutions know their customers would leave if a credible alternative appeared. The problem is building that alternative inside a regulated industry, with legacy systems, risk-averse culture, and distribution models that were never designed around the customer. Most attempts to modernise from within stall long before they reach the market.
Most organisations have now invested significantly in digital infrastructure. Most are still not performing like digital organisations. The companies consistently outcompeting established players are not winning on technology budget – they are winning on operating model, decision-making speed, and cultural norms that established businesses have not yet diagnosed, let alone changed. Leaders are under pressure to demonstrate digital transformation outcomes without a clear account of what actually separates digital investment from digital performance.
Leaders now have access to more knowledge than at any point in history – and less clarity about what to do with it. Most strategic frameworks for navigating AI and exponential technology were designed for a world that no longer exists. The gap is not information; it is understanding: the capacity to anticipate what comes next, make decisions with philosophical coherence, and preserve human agency in organisations that are accelerating faster than their leadership thinking can follow.
Most organisations commit to products, propositions, and growth strategies before testing the assumptions those decisions rest on. The result is predictable: offerings that miss the market, business models that erode under competitive pressure, and strategy conversations that consume resource without resolution. The problem is not ambition. It is the absence of a shared, practical framework for designing and testing what the business is actually trying to deliver.
Recurring-revenue businesses do not fail because their product is weak. They fail because acquisition, onboarding, retention and expansion are run by separate teams using different data, different vocabulary and different incentives. Scaling growth without redesigning that operating system produces compounding friction instead of compounding revenue.
Every major food business generates surplus. Most treat it as a disposal problem and price it accordingly. The result is a supply chain designed to waste, measured by metrics that make the waste invisible – until ESG reporting, procurement scrutiny, and reputational risk make it expensive.
Retail and consumer brands are being asked to behave like logistics companies without losing what made the brand worth choosing in the first place. The marketing team owns customer experience that now depends on a delivery driver, an app, and a supply chain. Most organisations have not redesigned how brand, commerce and operations work together to make that handoff feel like one company.