Why government innovation goes beyond big data and tech.
Public sector agencies around the world are increasingly turning to data and technology-led solutions to help them tackle complex, knotty challenges. Governments wanting to show that they’re embracing innovation invest in flashy new apps, or chatbots, or data dashboards, which look impressive. However, it is important to remember that, working alone, these tools cannot address complex social challenges.
In order to drive the sustainable and systemic change that the public sector needs, a multidisciplinary approach is essential.
This is not to say that data and technology are not an important part of innovation — of course they are! Rather, it’s an appeal against the veneration of data and technology as the answer to public sector challenges. As Nesta’s Competency Framework for Experimenting and Public Problem Solving (see below) suggests, technology can only be an effective tool when we invest in understanding how well it works in real life, and whether it’s meeting people’s needs.
“We need big data, but we also need thick data. We need good AI tools, but we also need people who know how to use them well. We also need to be able to identify the limitations and flaws that exist in data and tech tools.”
1. Data analytics is being embraced by public sector agencies to help managers and frontline workers better predict risk, target resources and make more informed decisions. And it certainly can be a force for good. However, while data analytics can support agencies to optimise existing systems and services, analytics projects are not well placed to drive deeper, and more fundamental, systems change.
2. Building on this, there has been some great stuff written on the need to combine big data (quantitative) with thick data (qualitative) to generate truly meaningful insights. Andrea Siodmok wrote a great article on how a blend of big and thick data supports better policymaking.
3. Another challenge with data analytics projects arises from the fact that analytics teams tend to sit in central offices, miles away from the people actually making decisions. This can create a disconnect between the information generated by analysts and the information that decision-makers want and need. It doesn’t have to be this way! Manira Ahmad is working to embed data teams into communities to help them connect to the stories that sit behind the numbers.
4. It’s also important to remember that data is imperfect and should always be interrogated to identify potential gaps and biases. Great guides and toolkits exist to support this, many of which are included in this “Map the Gap” tool below, which Kelly Duggan and I created:
5. Focusing more squarely on technology now (although data and technology tend to operate hand-in-hand), many public sector agencies are beginning to use AI tools. While there has been a great focus on the importance of designing ethical AI tools, my recent report for Nesta argues that, for AI tools to be safe and effective, public sector agencies also need to support frontline practitioners to use these tools well.
6. Much has also been written about the fact that “digital government” is not all about using digital technologies; rather, digital is about changing the way we work. In their book ‘Are We There Yet?’, Martin Stewart Weeks and Simon Cooper argue that digital transformation is about rethinking “the assumptions we make about the context, mission and capabilities of the public sector.” Pia Andrews has also shared a great selection of resources on digital government.
7. To end, a quote from a most-excellent article on Innovating in Complexity:
“Technology-centric ‘innovation as usual’ will provide some of the building blocks of a more prosperous and just future. But what we must learn now is how to weave these technological advances into the fabric of society along with other cultural, institutional, social, and economic innovations.”
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