Harnessing the power of data analytics to drive better services from local government is well-established, and a recent survey of council chief executives revealed a third are already using data analytics to inform decision-making and strategy.
However, the current financial situation for the sector remains challenging and was high on the agenda at July’s Local Government Association’s annual conference. With the funding gap estimated to reach £5.8bn by 2020, data needs to go further and it needs to be smarter if data analytics infrastructure is to deliver better and more tailored services.
Ultimately, smart policy implementation relies on evidence-based decision-making. Data is growing exponentially and its role in guiding decisions, by providing a firm idea of the impact or effects of particular decisions on services, is really only limited by the data that is available.
Be it consumer segmentation, information describing demographic, lifestyle and behavioural characteristics, or disposable income data – which is becoming increasingly sophisticated – data helps to gain a much better understanding of the facts on the ground.
The more detailed the data, the clearer the picture of the impact of particular policies or investments. As a result, consumer segmentation can shape our knowledge of who will be interested in particular services, while disposable income data can explain whether residents can supplement these services financially.
One example of effectively using data can be seen at Basingstoke and Deane BC, as Sally Kenyon, policy officer, data, explains: ‘The policy team at the council applies analytical techniques, insights and tools so that work and programmes are data driven and evidence based, and iteratively improves policy to meet complex and changing needs.
‘The council is a joint land owner for the Manydown housing development site, one of the largest residential-led developments in the South East on land in public ownership. This significant development includes initial plans for 3,200 homes within the council’s current local plan period which runs to 2029. Ownership of the Manydown site gives the council a unique opportunity to ensure the development provides high quality, well-planned, well-designed and well-built new communities that meet local needs.
‘CACI data is used for assessing the affordability of local housing for local people. This helps the council keep track of the proportion of households by lifestage that can afford market housing within the borough and to assist those that cannot.
‘The Manydown development allows the council to look at innovative ways of providing affordable housing through a range of new products in the Government’s housing white paper. The data helps the team explore variations in affordability for these products based on indicative market prices and then determine the suitability of their use locally.’
While councils are routinely solving varied challenges through data analytics, we know that the better the available data, the more tools analytics teams have to work with. In the case of differential services, for example, far greater detail and depth of understanding of consumer demographics, behaviours and disposable incomes are required.
A trend linked to differential services is the need for authorities to ‘condense’ services. Coventry City Council’s work in this area required analytics teams to understand how different services can be configured together to, for example, reduce risks in child health or protection services – using consumer segmentation and disposable income data.
Andy Baker, insight manager, intelligence at Coventry City Council, expands on this: ‘The most important way to think about data is that it doesn’t answer questions for you, but it does help you to ask questions more intelligently. When reviewing service provision, we have worked hard to use data to support decision-making by understanding what is possible, then using data to adapt our approach as we implement and refine the service.
‘Last year we launched our customer portal, to allow users to access information on items such as housing benefit, council tax and waste disposal. This shift to digital speeds up access for those who prefer to manage their accounts online, while allowing us to divert resources to those who need more assistance in managing their accounts.
‘Data on consumer segmentation allowed us to understand the potential level of take-up of this portal, which meant once it was launched we could understand our performance.
‘Looking ahead, we are working on a consultation on children’s services in the area. Using consumer segmentation data and our own case management information, we can create a comprehensive view of wider trends in the population and the needs of individuals. And where necessary, we are supplementing our understanding of households using disposable income in post codes. All this data is then being used to assess the potential impact of different scenarios in changing children’s services. This evidence-based approach will allow us to give the community the right information to make informed decisions on how they want services to look in the future.’
Neil Wholey, chair of the Local Area Research and Intelligence Association (LARIA) and head of evaluation and performance at Westminster City Council, highlights the challenges still to be done in bringing together data:
‘There are three common characteristics of useful data. The first is it has to help meet the organisation’s financial and social challenges. Next, it should be as comprehensive as possible and be able to link with other data. Finally, we should know its provenance and that it has been ethically collected and used.
‘Financial and social challenges can be met by demand-side and supply-side data in different ways. Demand-side identifies current or potential heavy users of services, whereas supply-side can show community capacity to positively contribute to challenges.
‘Making sure data is comprehensive and linked to other data is equally useful. In a recent Westminster City Council-supported hackathon with Kings College, students looked at the data around the night-time economy, successfully creating links and connections with other relevant data from the organisation.’