According to the Local Government Association (LGA), local government provides 80 per cent of our local public services. These include environmental services such as waste management and the maintenance of parks and other green spaces. Yet its ability to provide these services effectively, both within and across local authorities, is hampered by a siloed and fragmentary approach to data and technology management.
Eddie Copeland, head of Policy Exchange’s Technology Policy Unit, recently released a new report arguing that each local authority’s IT infrastructure is virtually unique as a result of historical procurement and development decisions. This has important knock-on effects, including:
- Unnecessarily high technology costs: software development and procurement costs remain high since economies of scale are prevented, and local authorities are locked-in to both bespoke products and to specific vendors; and
- Inefficient working: fragmented technology and data recording methods reinforce organisational silos across and within local authorities and other public sector bodies.
Eddie argues that not only do we need the right technology and data management tools, but local government also needs to increase data sharing and collaboration. For that to happen, local government needs to change the way it operates; streamlining internal as well as external processes and involving all local authority staff. He makes a series of recommendations to help achieve this, including the establishment of an Office for Data Responsibility and supporting the proposed appointment of a Government Chief Data Officer.
This sounds wonderful in theory, but what could it mean in practice? This is where we could look to New York’s Office of Policy and Strategic Planning for inspiration. With a team of just five data scientists and the wealth of datasets that the public sector held (even the messy ones), enormous improvements in efficiency were made. Although these improvements were primarily in non-environment fields, there is potential for data sharing and collaboration to make a positive difference to the local environment.
Perhaps the most notable success was the combining of data from 19 agencies to determine where illegal housing conversions (contributing to fire hazards and rodent infestations) were most likely to have taken place. This allowed more targeted inspections, raising the proportion of vacate orders from 13 to 70 per cent. Combining public sector datasets also resulted in a list of restaurants that were statistically likely to be illegally disposing of cooking oil directly into local sewers. This led to a 95 per cent success rate in identifying the culprits. In addition, Hurricane Sandy inspired attempts to correlate public sector and utilities data to help local authorities determine when a building’s heat or lights were out in real time, allowing emergency services to respond more quickly.
How could this work in the UK? One of the most important areas of improvement would be in spatial planning across Local Authority boundaries. Imagine if neighbouring local authorities could quickly and easily share the locations of key infrastructure, amenities and processes, allowing cross-boundary co-ordination.
Suddenly, you would be able to spot cross-boundary gaps in provision, be able to link up existing facilities and processes at a much larger scale, and tailor amenities to provide the facilities that the local population needs most. Sectors that could benefit from this include, but are by no means limited to:
- Parks and other green spaces: our Park Land report explored current failures in cross-boundary spatial planning; and
- Waste collection and infrastructure: our A Wasted Opportunity report highlighted the complexity in the local governance of waste.
Another important area of improvement involves harnessing the predictive power of data. As was demonstrated in New York, analysing combined datasets can allow more rapid responses to (or even the prevention of) problems. Combining datasets from within and across local government, as well as from other public sector bodies such as the Environment Agency, would be particularly important in the areas of environmental health and emergency planning.
Even one minor example of the potential of predictive analysis illustrates the savings that can be made: what if you could predict (by combining data such as council complaints, mortgage refusals, building site locations, railway locations, and environmental records centre information, etc.) where the next infestation of Japanese knotweed would be most likely to occur and target treatment early? This could help cut some of Japanese knotweed’s £166m annual cost to the British economy.
The possibilities are endless, and in the long run digital reform will save local government money through both cheaper technology and improved efficiency. But in an age of austerity, it will require courage and foresight to take the first steps.