When research commercialisation fails, the blame usually falls on one of two ends:

• “The research wasn’t market-ready.”

• “Investors weren’t willing to take the risk.”

In reality, most failures happen in between.

Not in the lab.
Not in the startup phase.
But in the missing middle — the poorly supported transition from research insight to commercial opportunity.

The real gap is not money — it’s coordination

This middle phase is often described as the Valley of Death.
But framing it as a funding gap is misleading.

Multiple international studies show that early-stage research ideas fail not because capital is unavailable, but because no one owns the process of turning knowledge into a coherent opportunity.

The OECD describes this as a systemic coordination failure: researchers, companies, investors, and technology transfer offices operate with different incentives, languages, and timelines.

As a result:

• researchers focus on scientific validity

• companies look for proven use cases

• investors seek scalable ventures

• TTOs manage risk and compliance

But no actor is responsible for sensemaking across these worlds.

From invention to opportunity is not a single step

Between a validated research result and a commercial venture lies a complex process:

• framing the problem in user and market terms

• identifying viable application contexts

• testing assumptions without full-scale commitment

• translating technical novelty into perceived value

This work is neither pure research nor entrepreneurship.
It is translational thinking — and it is systematically under-resourced.

The European Commission has repeatedly highlighted this gap in its knowledge valorisation reports, noting that many public systems “lack instruments for structured exploration before venture creation.”

Why linear innovation models fail here

Traditional innovation pipelines assume a linear flow:
Research → Development → Commercialisation → Growth

But this model breaks down in the middle.

At this stage:

• uncertainty is still high

• multiple futures are possible

• learning matters more than execution

Linear models demand commitment too early — to a market, a product, or a company — when flexibility is still essential.

This is why many promising ideas stall:
they are too early for scale, but too applied for research funding.

What effective systems do differently

Successful research commercialisation ecosystems invest deliberately in the missing middle by:

• funding structured exploration, not just projects

• supporting iterative opportunity framing

• enabling collaboration without premature company formation

• using portfolio logic instead of binary decisions

Institutions that do this well treat early commercialisation as a learning phase, not a proof phase.

The goal is not to eliminate uncertainty —
but to reduce the right uncertainties at the right time.

Until this middle layer is taken seriously, labs will keep producing knowledge — and markets will keep missing it.

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References

• OECD (2021). Reducing the Commercialisation Gap in Public Research

• European Commission (2022). Guiding Principles for Knowledge Valorisation

• MIT Innovation Initiative (2020). Translational Research and Innovation

• EIC Impact Report (2023). From TRL to Market

• Mazzucato, M. (2018). Mission-Oriented Innovation

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