In many years of doing research in support of innovation policy, I realize there are two axis that determine the situation you are in:
- the level of political sensitivity of the issue
- the level of robustness of the evidence
These two axis determine four possible situations.
Low sensitivity/high evidence: this is the easiest situation, for well accepted statements like “research is good for a country’s competitiveness”. Your statements are easy to justify, and few will contradict you. You can use nice stories and histograms. But this is also the least valuable for policy-makers, and normally there are few studies about this topic as evidence is already available.
Low sensitivity / low evidence: this situation is not that very difficult either. You need creativity to bring up cool new ideas, and you don’t have to justify them thoroughly. For example, saying that government 2.0 is not a zero-sum game between public and private provision of services (the TAO government), is a nice attractive ideas which you can justify with anecdotes, as few stakeholders are disturbed by this concept
High sensitivity / high evidence: More difficult than the previous, but not too difficult either. You should make use of the best evidence available, in particular the “big numbers” that policy makers like, add buzzwords like “sensitivity analysis”, and quote from papers with high scientific standards and from authorities that your critics consider highly. You need to combine clear and bold conclusions with high evidence to back this up.
High sensitivity / low evidence. This is the dangerous place to be. You have little evidence and you will be watched by many. You need to avoid bold statement, be dry, refer continuously to the evidence and to authoritative scholars and politician. You should clearly define the limits of your conclusions. You should know and prevent the criticisms that will be drawn to you. You should thouroughly analyse evidence for and against. You can be creative, but mainly in looking for win-win situation. Most of all, you need to invest lots of time on this situations, and avoid being bold.
This might seem intuitive, but in my experience it is not. Too often researchers fail to take into account the political sensitivity of a situation, and only focus on the robustness of the results. They allow themselves to be bold on issues where they cannot be – and this is when the problems arise.
Robustness is a grey, not black and white concept. And you need to know when you can be bold and when you have to be dry. I recommend that at the beginning of each research, you draw such a map to anticipate areas which you need to “handle with care”.