Exploring the role of data in post-Covid recovery

Blog by Eddie Copeland: “…how might we think about exploring the Amplify box in the diagram above? I’d suggest three approaches are likely to emerge:

Image outlines three headings: Specific fixes, new opportunities, generic capabilities

Let’s discuss these in the context of data.

Specific Fixes — A number of urgent data requests have arisen during Covid where it’s been apparent that councils simply don’t have the data they need. One example is how local authorities have needed to distribute business support grants. Many have discovered that while they have good records of local companies on their business rates database, they lack email or bank details for the majority. That makes it incredibly difficult to get payments out promptly. We can and should fix specific issues like this and ensure councils have those details in future.

New Opportunities — A crisis also prompts us to think about how things could be done differently and better. Perhaps the single greatest new opportunity we could aim to realise on a data front would be shifting from static to dynamic (if not real-time) data on a greater range of issues. As public sector staff, from CEOs to front line workers, have sought to respond to the crisis, the limitations of relying on static weekly, monthly or annual figures have been laid bare. As factors such as transport usage, high street activity and use of public spaces become deeply important in understanding the nature of recovery, more dynamic data could make a real difference.

Generic Capabilities — While the first two categories of activity are worth pursuing, I’d argue the single most positive legacy that could come out of a crisis is that we put in place generic capabilities — core foundation stones — that make us better able to respond to whatever comes next. Some of those capabilities will be about what individual councils need to have in place to use data well. However, given that few crises respect local authority boundaries, arguably the most important set of capabilities concern how different organisations can collaborate with data.

Putting in place the foundation stones for data collaboration

For years there has been discussion about the factors that make data collaboration between different public sector bodies hard.

Five stand out.

  1. Technology — some technologies make it hard to get the data out (e.g. lack of APIs); worse, some suppliers charge councils to access their own data.
  2. Data standards — the use of different standards, formats and conventions for recording data, and the lack of common identifiers like Unique Property Reference Numbers (UPRNs) makes it hard to compare, link or match records.
  3. Information Governance (IG) — Ensuring that London’s public sector organisations can use data in a way that’s legal, ethical and secure — in short, worthy of citizens’ trust and confidence — is key. Yet councils’ different approaches to IG can make the process take a long time — sometimes months.
  4. Ways of working — councils’ different processes require and produce different data.
  5. Lack of skills — when data skills are at a premium, councils understandably need staff with data competencies to work predominantly on internal projects, with little time available for collaboration.

There’s a host of reasons why progress to resolve these barriers has been slow. But perhaps the greatest is the perception that the effort required to address them is greater than the reward of doing so…(More)” –

See also Call For Action here