Rules are not enough: knowledge transfer needs people who can make them work
By Mariana Hanková · 4 min read
Czechia is rewriting the rules for turning research into practice. But whether research results reach the market, public services and policymaking - or end up in another report - depends on people inside institutions who understand the evidence and have the authority to act on it.
Key takeaways • New legislation removes barriers, but it does not create the capacity to use the new opportunities. • Analysis informs decisions; it does not replace them. Even AI cannot supply the institutional context that lives in people. • External expertise works best when it feeds a specific decision with a clear internal owner. • Support tools are multiplying, but access still depends on institution, region, field and open calls. |
A year of big changes – and quiet cuts
Czech research and innovation policy is changing faster than it has in years. In January, a new Act on Research, Development, Innovation and Knowledge Transfer takes effect. A Startup Act is going through the legislative process, the updated national R&D evaluation methodology (Metodika 2025+) is being applied, and the government is introducing its Economic Strategy 2.0. The state wants to make it easier to found spin-offs, commercialise results and use research evidence in public policy.
At the same time, ministries are reorganising and cutting staff, and the project funding that built part of the state's analytical capacity is coming to an end – at the Ministry of Finance or the Ministry of the Environment, for example.
Analysis does not replace politics – it sharpens it
Working at the Office of the Government, I saw decisions grounded in thorough research and decisions driven mainly by politics. Both are legitimate. Elected representatives set the goals and priorities. The job of analysis is not to replace politics but to show what each option costs, what it is likely to achieve and how uncertain that is. A political decision loses nothing by this – it becomes better informed and easier to defend.
Even with AI, people are not disappearing from this work – at least not yet. AI can dramatically speed up research, data processing and the comparison of options. But without institutional context, it does not know why a programme was set up the way it was five years ago, what has already been tried, what is feasible in practice or what works differently than on paper. Much of that knowledge is not written down anywhere. It lives in people and their shared experience.
The same problem from the other side of the table
Today I see the same problem from the other side. When a research institute has to decide whether to keep developing a technology, license it or build a spin-off around it, it needs to understand the market, competing solutions, intellectual-property risks and whether there will be real demand.
Research organisations often lack the in-house capacity for this kind of analysis, so they bring in external experts. That is a sensible choice: an external team brings specialisation, benchmarks from other institutions and markets, an independent view and capacity the institution does not need to keep permanently. It works best when the analysis is not a mandatory deliverable but input for a specific decision.
But external analysis cannot replace an informed decision owner inside the institution. If nobody on the side of the state or the research organisation understands the question, can judge the quality of the evidence and will take responsibility for what happens next, the institution is not buying better decisions. It is just buying another document.
Data without analysis is just entries in a system. A strategy without follow-up decisions is just a box ticked. And external analysis without an internal owner often ends up as a PDF nobody opens again.
More tools, but not yet a system
The good news is that the system is full of people and teams who want to change things, and the toolbox is growing. Alongside technology transfer offices and regional innovation centres, new initiatives are emerging: widerAdvance Facility helps teams from European Widening projects make better use of their results, the NTK Knowledge Transfer Academy teaches researchers to test whether and how their results can be applied in practice, and the Policy Engagement Toolkit shows scientists how to present findings in a form policymakers can use.
Each, however, covers a different part of the need for a different group. Whether a research team can access support still depends on its institution, region and field – and on whether a call happens to be open.
What would help • Stable shared capacity giving smaller research organisations access to specialists in intellectual property, markets, regulation and licensing. • Fast funding to validate commercial potential before deciding whether to develop, license or spin off a technology. |
The Czech Academy of Sciences' PRAK programme already follows this logic: it combines a smaller grant with expert support for IP protection, partner search or spin-off preparation, and decides on funding quickly. But it is open only to Academy institutes.
You can buy expertise – not ownership
Not every institution needs to employ all of these specialists. Nor do technology transfer centres have to carry them – their capacity is often limited and, like the civil service, dependent on project funding. Specialised work can be shared or bought in. What cannot be bought as a one-off is the person who knows when to use it, can judge the result and has the mandate to act on it.
New rules can remove barriers. Whether they bring research into practice – or just into another document – will be decided inside institutions.
Deciding what to do with a technology? At UNICO, we help research organisations and companies assess markets, competition and IP risks, so the people who own the decision have solid ground to stand on. |
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