What’s Wrong with Public Policy Education? It has no understanding how to implement policies in the real world. (Francis Fukuyama)

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What is wrong with public policy education? Too much focus on econometrics and optimal policy choices. While learning how to implement the most optimal policies are theoretically sound, these policies are rarely implemented due to various actors and interest groups.

Instead, Frank Fukuyama suggests public policy education to focus more on stakeholders analysis using skills taught in anthropology.

The first set of skills would involve problem definition. A change-maker needs to query stakeholders about what they see as the policy problem, understand the local history, culture, and political system, and define a problem that is sufficiently narrow in scope that it can plausibly be solved.

The second set of skills concerns solutions development. This is where traditional policy analysis comes in: It is important to generate data, come up with a theory of change, and posit plausible options by which reformers can solve the problem they have set for themselves. This is where some ideas from product design, like rapid prototyping and testing, may be relevant.

The third and perhaps most important set of skills has to do with implementation. This begins necessarily with stakeholder analysis: that is, mapping of actors who are concerned with the particular policy problem, either as supporters of a solution, or opponents who want to maintain the status quo. From an analysis of the power and interests of the different stakeholders, one can begin to build coalitions of proponents, and think about strategies for expanding the coalition and neutralizing those who are opposed.  A reformer needs to think about where resources can be obtained, and, very critically, how to communicate one’s goals to the stakeholder audiences involved. Finally comes testing and evaluation—in the expectation that there will be a continuous and rapid iterative process by which solutions are tried, evaluated, and modified. Randomized experiments have become the gold standard for program evaluation in recent years, but their cost and length of time to completion are often the enemies of rapid iteration and experimentation.

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