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Supporting policy with scientific evidence

We mobilise people and resources to create, curate, make sense of and use knowledge to inform policymaking across Europe.

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Good Governance of Evidence-Informed Policymaking

In March 2022, the Joint Research Centre held an online workshop on the topic “Constructing assessment indicator dashboards for evidence-informed policymaking”. As part of the preparations to the workshop, I wrote one of the background reports on the challenges of evaluating, monitoring and ultimately governing evidence advisory ecosystems. Here are three important fundamentals when discussing the governance of evidence-informed policymaking.

The seemingly dry topic of “indicator dashboards” (see the full report) is connected to fundamental questions about the role and authority of science in democratic societies. Below, I state what I take to be three important fundamentals when discussing how and why to govern evidence-informed policymaking:

1. Science Doesn’t Speak Truth to Power

The good use of scientific knowledge in public decision-making is a keystone of modern societies. The scientific mindset is critical, self-critical and reflexive. Any good scientist knows that scientific knowledge is fallible, and that precision comes at the cost of scope. Yet, EU regulation occasionally describes science as “vital to establishing an accurate description of the problem, a real understanding of causality and therefore intervention logic”. 

This promise is too bold and it creates a risk that was mentioned already in President Eisenhower’s 1961 Farewell Address:

Yet, in holding scientific research and discovery in respect, as we should, we must also be alert to the equal and opposite danger that public policy could itself become the captive of a scientific-technological elite.

US President Eisenhower

To mitigate this risk, the use of scientific evidence in policymaking should be governed with an eye to the norms of:

  • transparency: Where does the knowledge come from?
  • reflexivity: What can we say about the known and unknown unknowns?
  • and contextuality: Is this knowledge input fit for purpose?

2. Control is a False Ideal

The language of “indicators”, “dashboards”, “bench-marking” and so on, is often associated with ideas of conventional intervention logic and the hope to command and control.

Such ideas and hopes may be well suited in prisons and in the army, but they are not useful to cultivate transparency, reflexivity and contextuality, which ultimately all depend on the presence of trust, truthfulness and the willingness to be convinced by the force of the better argument. Network approaches to governance are more relevant for evidence advisory ecosystems. Indicators and dashboards may still be useful, but not to command and control.

3. We should be smarter than SMART

A challenge that I really believe we can solve, is the presence of business jargon within European institutional discourse. “SMART” is an instance of such jargon. Its origin is a one-page paper written in 1981 by the management consultant George T. Doran.

Since then, it has lived its own life and penetrated public discourse in its various incarnations. The “A”, for instance, has variously stood in for Achievable, Attainable, Assignable, Agreed, Action-oriented and Ambitious. 

In many instances, there is nothing wrong with SMART. When developing good governance of something as dynamic and contingent as an evidence advisory ecosystem, however, the problem with SMART is that it encourages to decide beforehand, ex ante, what is the “specific and measurable” desired state of the system to be monitored. This is not how network governance works or even should work. We should stop using such jargon.