Report highlights need for proactive approach to encourage data-led innovation in local government
The Government Digital Service (GDS) and the Department for Communities and Local Government have been urged to embed data analysts alongside local government workers around the country.
Innovation charity Nesta has made the call in its new report on the use of data in local government, Wise Council, saying the two bodies should set up a dedicated scheme to encourage more data-led innovation in the sector.
It says there are existing programmes for bringing data scientists into social sector organisations – citing examples from Chicago University’s Data Science for Social Good programme and the operations of the DataKind organisation – and that they could provide a template for connecting data scientists with staff in councils.
They could work together with the objective of creating actionable insights and data driven tools to couple with needs they have identified. In addition, they could take a lead in the cultural change needed to spread awareness of the potential of data and develop in-house capacity.
But the scheme would need funds of about £3.7 million a year from central government and other sources.
GDS is already committed to spreading the use of data science around central government, and such a scheme would be in line with the moves it has taken this year to work more closely with local government. But the call for funding would no doubt have to compete with those to meet other objectives.
The report says the programme would also need data scientists and analysts committed to dealing with social issues and a commitment from local authority leaders. In addition, any tools, apps or analytic methods they develop would have to be scaled up quickly; and everything would have to be subject to a rigorous analysis.
A second recommendation is for the Local Government Association to get behind efforts to replicate best practice in the field with a knowledge transfer scheme. This would involve secondments ore visiting support from people involved in leading best practice, and would make it easier for councils to share intangible skills and knowledge.
“Once underway, the programme should aim for each site which receives a secondee to then become the expert secondee in the next round,” the report says. “This would multiply the rate at which innovations could scale, and reduce the burden on the first wave of local authorities.”
Other recommendations are that city regions that win devolution settlements should be required to set up an Office of Data Analytics, and councils should build systematic evaluation into data-led innovation.
Report author Tom Symons (pictured) said: “This is really just the beginning. Most councils are only just starting to get to grips with all the data they have, and all the ways they could use it to make improvements.
“The data held by the local government sector is a potential goldmine of insights into how to improve people’s lives and make our communities better.”
The report is the second in Nesta’s Local Datavores series, looking at how councils can use data to achieve their strategic objectives. It draws on case study research and nearly 40 interviews with data analysts, project managers and senior leaders, and comes up with 11 areas in which data is producing benefits for local government:
- Optimising management of place and infrastructure.
- Testing what works.
- Intelligent case management.
- Outcomes based performance management.
- Early identification of adverse events and future service pressures.
- Understanding and responding to citizen needs.
- Informing public service transformation.
- Streamlining operational council processes.
- Opening government.
- Supporting the local economy, businesses and innovation.
- Identifying fraud and error.
Councils face some stiff challenges in realising these benefits, such as pulling together data from legacy IT systems and ensuring that they comply with information governance rules that are not always clear. But the report says they can make progress by following 10 steps that include: starting with a clear problem to be solved; being clear about the ultimate objectives; doing the work through a series of short, repeatable cycles; and testing the product with end users and taking in their feedback.