Can PDIA become a regular part of how a government works?

Guest blog written by Peter Harrington

Recently I have been engaging with a government in a middle-income country which is using PDIA methods to tackle some of their thorniest public problems. As one would expect there have been successes and failures, and lots of learning. But in addition to this, leaders in the government want to ‘embed’ PDIA permanently into the way their government works. This raises some interesting questions for PDIA – can the methodology be institutionalised as part of the way a government works? If so, what does this look like? And what is required to make that successful and sustainable?

The government has decided that it wants to embrace more innovative methods of getting things done, and governments through the ages have had similar ambitions. There has been a recognition that existing ways of working leave some problems unsolved, and a good place to start is to understand why this might be.

Governments by their nature function in routines. These are established pathways which, to a greater or lesser degree depending on the government’s capability, serve a range of functions in maintaining the operations of the state. These functions are well established but can also change, adapting to new conditions and new social or economic needs through shifts in policy, legislation, new services and new ways of working. As such governments can be understood as complex adaptive eco-systems which are themselves embedded in and interacting with a larger complex adaptive system: wider society.

As functioning (or dysfunctioning) systems, governments get an awful lot of things done. To borrow an analogy used by Matt Andrews, the amount of coordination it takes to make a streetlight switch on at a specific time each day is actually quite extraordinary. But as systems whose configuration is a response to and reflection of their societal context, governments are by their nature unable to solve every problem through their regular operation. Some problems are complex, and/or emergent, and require different types of know-how to solve. Some of these problems may arise directly because the machine of the state is configured in such a way as to neglect, exacerbate or even cause that particular issue. Think of a robot vacuum cleaner: they are pretty smart these days, programmed to trundle around your house hoovering the floor space and capturing a lot of dirt. When it’s done the floor looks pretty clean, but anyone with a Roomba knows that it can’t catch dirt gathering in the hard to reach corners, and it may have even pushed extra dirt into some of those corners. Getting into those nooks and crannies requires something different – probably a human, using a different tool.

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