Change Management for Open Data in Government: A New Model
April 15, 2012
Governments are starting to change the way they catch and release data. The giant file cabinets are still there, of course, but when the head of government starts pushing open data the wheels start to turn. The shift away from file cabinets towards open data driving government is essentially a change management issue. But most open government conversations don’t approach the problem as an institutional development or change management problem. Instead, we hear about “apps” and “transparency” and “participation”, all of which have definitional baggage.
Fortunately, lots of smart people have studied how organizations change, which means open government data proponents have a wealth of change management research to build a new change model on. I’m taking a crack at it here.
In this post, I’m proposing a change model based on the Dunphy Sustainability Scale, a tool for understanding how organizations adopt sustainability values. The environmental and social sustainability movement is a particularly good starting point for us because it has many parallels to open government:
- Most organizations class both sustainability and open data practices as “nice to have,” not “core to the business.”
- Both sustainability and open data can be transformational; they can create an entirely new frame to consider what an organization can achieve and how it operates.
- There aren’t many organizations that have managed to transform themselves yet, although there are plenty that are working on it.
It also helps that I’ve spent a few years working on sustainability focused change management projects, so I have a working understanding of the different stages, which I’ve drawn out here:
Let’s dig in, starting from the bottom:
- Rejection: Pretty self explanatory, really. This is a government that actively refuses to take steps towards opening data.
- No Response: This is a government that isn’t actively refusing to take action but isn’t making any positive effort either.
- Compliance: If regulations require opening data, these governments will do the bare minimum.
- Efficiency: At this stage someone is making strategic decisions about what data to open in order to save the government time or money.
- City as platform: Providing clean, structured data is the default; withholding data is the exception.
Of course, naming the stages is the easy part. The real question is: how do you move a government up the scale?
It’s easy to see how to move a government from rejection to compliance – just pass a law! While we’re waiting for the policy people to stop laughing, let’s take a closer look at the second half of the scale.
Apps contests as change agents
In an upcoming O’Reilly manual I’m writing with Virginia Carlson, I’m going to explore how civic apps competitions can move governments from compliance to efficiency and from efficiency to city as platform.
A common critique of civic apps competitions is that the apps don’t last. This is usually true, but there are other good outcomes of a apps competition that may be more important. Apps contests are a way to push government along the progression from rejection to city as platform. While apps for finding pickup basketball or cheap parking are nice, the long term transformation of government is a more permanent and wider reaching outcome.
Change management studies tell us there are four outcomes that make change stick:
- Examples (I see it): Show what success looks like.
- Assessment (I need it): Show how the change will make my work life better.
- Practice (I do it): Get started.
- Support (I live it): Build a community of people who support the change.
- Community building: Competitions engage the coding community with government data, which creates a community that supports the change to city as platform.
- Proof of Concept apps: Competition apps are examples that demonstrate the usefulness of making government data public to businesses and NGOs – even if they don’t stand alone after the competition ends.
- Test drive data practices: Competitions frequently speed the development of clean and structured data, which provides practice.
Compared to a nice, solid app these outcomes might seem pretty intangible, but that’s because the learning process is a nebulous thing. Institutional development is hard to see, but has long lasting impact.
— Kate Eyler-Werve
— Image by David Starkopf ( CC by/nc )