Demand driven research: who serves whom?

In today’s fast-moving innovation landscape, one phrase echoes in boardrooms and funding agencies alike: research should be demand-driven. The reasoning is sound: research must align with industrial needs, tackle real-world problems, and generate outcomes that matter.

After all, translating scientific excellence into usable value is key. This holds true whether public funding is involved: where taxpayers rightly expect return on investment or when businesses themselves foot the bill. In both cases, outcomes count. Curiosity is vital, but results drive relevance.

This logic underpins the classic model of how innovation is supposed to unfold: a neat, sequential path from lab to market. And tools like the Technology Readiness Levels (TRLs) are built to support this. Starting from TRL 1 (early-stage research), a concept moves through development phases, reaching TRL 5 when it's validated in a relevant environment, and finally TRL 9, where it’s market-ready. TRLs are helpful for aligning industry expectations, managing risk, and mapping investments.

However, there's a catch: TRLs also reinforce the myth that innovation is linear. And real innovation? Rarely follows a straight line.

In practice, innovation journeys involve loops which include returning to early assumptions, discovering new use cases, or encountering unforeseen roadblocks. Research and development are iterative, responsive, and frequently non-linear. And this dynamic reality applies equally to research-industry collaboration.

Learning from Self-Driving Cars

Let’s take a closer look through a real-world example: the DARPA Grand Challenge, as recounted by Sebastian Thrun in his TEDx Brussels talk in 2010. In 2003, the U.S. government offered a challenge: build a self-driving vehicle capable of crossing 140 miles of desert terrain without human intervention. GPS coordinates were even supplied to make it “easier.” Thrun, an accomplished roboticist, initially was not interested and dismissed the task as being too straightforward.

He was wrong. Most vehicles didn’t even clear the first mile. Even top teams failed to reach 10 miles. Humbled, Thrun dedicated the next year to solving this deceptively complex challenge, ultimately leading to one of the first successful autonomous vehicles. It required research, resilience, and deep cross-disciplinary collaboration.

The lesson? What seems like a simple industry request can demand years of scientific inquiry. Conversely, research-originated questions can sometimes be resolved with elegant, simple solutions.

Why Boundaries Spark Innovation

Interestingly, the best innovation doesn’t come from unlimited freedom — it often stems from clear boundaries. Constraints around technical feasibility, user needs, thematic focus, or funding goals can unlock sharper thinking. Like an artist who thrives within the edges of a canvas, innovators gain clarity from structure.

The Power of a Collaborative Mindset

The real power lies in the interaction between both worlds. Innovation thrives not in silos, but in shared ambition. When academia and industry co-design solutions, build alignment, and co-own the path forward, something powerful happens: the results are more creative, more relevant, and more impactful.

True innovation isn’t just about novel ideas, it’s about delivering real value: whether through smarter systems, new products, or better user experiences.

Open Minds Alone Aren’t Enough

But let’s be clear: having an open mind isn’t enough. Building successful research-industry collaboration is complex. These are two fundamentally different worlds: with different cultures, timelines, and expectations. Without a clear framework, even well-intended partnerships can falter.

Consider how many innovation project proposals fail to deliver. Too often, it’s due to misalignment, hidden agendas, or lack of clarity about roles and outcomes.

The Win-Winnovation Methodology: Collaboration That Works

The good news? These pitfalls are avoidable. Enter the win-winnovation methodology, a structured approach designed to bridge the gap between research and industry. Built on decades of experience, this proven framework helps partners align their goals, define shared outcomes, and work together more effectively.

Best of all, it’s accessible. Anyone can learn how to use it. With practical tools and clear steps, win-winnovation transforms complex partnerships into productive, value-driven innovation ecosystems.

So, Who Serves Whom?

That’s the wrong question. The real win happens when research and industry stop pulling in opposite directions and start innovating side-by-side. The win-winnovation approach is your blueprint for doing just that.