Building Distributed Capacity

By Kent Aitken

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Last week Nick laid out a model that blends public sentiment, data analytics, design thinking, and behavioural economics as the future of evidence-based policy (see: basically, that was the title). The opportunity cost of inaction, here, is far greater than the immediate financial investments required. The only disagreement I can muster is that I'd actually call it the future of governance, writ large.

But, we're in an era of intense scrutiny. Governments are no longer entirely opaque entities, and spending can be held not just to account but to undue pressure. And that pressure is greatest when spending doesn't lead to immediate and obvious public benefits, which is the case for pursuing the future as described above.

However, there are examples of governments spending money on complex investments - those that are long-term, hard-to-measure, and with widely distributed benefits. It's largely because there are strong communities that envision the long term that are bellowing for these investments, creating crucial pressure and accountability.


And these investments line up with the model Nick proposed. For public sentiment, the U.K. is building capacity through organizations like Sciencewise, dedicated to helping government consult with citizens on science and technology policy. For design thinking, there are a handful of examples, established to help policy makers apply techniques in their work. In the Behavioural Economics field, the U.K. are again the leaders with the Behavioural Insights Unit, and the U.S. appointed Cass Sunstein to a key role to make progress there. For Data Analytics? I welcome examples. But there is good news in the technology space, however, as on Monday a bill was proposed in the U.S. that would codify the national Chief Technology Officer role and establish a Digital Government Office.


These are all wise investments, the success of which can only be measured in the long-term and at the macro scale. None of those investments solve an easily definable problem; rather, they create a distributed capacity, a system for more reliable problem-solving.



So where do we go from here?

At the highest level, it's a question of ensuring that we can make important investments in complex solutions. Where the counterfactual is the key question, and the opportunity cost of inaction far outweighs immediate financial costs. And with closely watching stakeholders than can be hard to convince.


More concretely? There's a group of brilliant and dedicated public servants pursuing capacity-building for design thinking close to home. This is both a discrete capacity and a way to improve virtually every decision-making process, so I think this will go a long way towards better results. Design thinking is properly merciless in testing and discarding sub-optimal solutions.


But data analytics, behavioural economics, and understanding public sentiment require their own skillsets. And I think (and have for some time) that the opportunity cost of not exploring capacity-building in these areas is too great to be ignored.