Luton Councils’ data-led approach to tackling homelessness
Lord Bird, founder of the Big Issue, recently hosted a Leading Lights Network event for Policy in Practice at the House of Lords to discuss the role public sector data has in identifying financial vulnerability and tackling homelessness.
One of the speakers was Nikki Middleton, Head of Customer Services at Luton Borough Council, a homelessness trailblazer local authority. Policy in Practice has been working closely with Luton, in collaboration with service design agency UsCreates (now part of FutureGov), to build a proactive and data-led approach to tackling homelessness. In this case study we share 7 lessons learned so far.
Clive Jones, Head of Revenue and Benefits, Luton Council shares the impact COVID-19 has had on the financial resilience of residents and the role that data and LIFT will play as they look to recovery.
Data and the homelessness reduction act: an opportunity for prevention
The introduction of the Homelessness Reduction Act (HRA) in 2018 placed new requirements on how local authorities deal with homelessness. Many saw this as an opportunity to rethink their homelessness services altogether, with some pioneering authorities exploring the predictive potential of the data they hold.
Predictive data modelling is not new. It‘s widely used in various sectors from weather forecasting to policing, to identifying young people most at risk of becoming Not in Education, Employment or Training (NEET). Indeed, the original Policy Lab and Ministry of Housing, Communities and Local Government (MHCLG) project that informed the Trailblazer set out predictive data modelling as one of the referral routes into redesigned services.
As part of the HRA legislation, MHCLG introduced a new statutory data collection system called H-CLIC to track the prevention work that councils undertake. It systematically records preventative action for people identified as at risk of becoming homeless within 56 days. However, the system doesn’t capture outcomes of successful interventions taken before this 56 day threshold. Like Luton, local authorities want to take an early intervention approach because it’s easier and a more cost effective way to prevent homelessness. Policy in Practice helps councils use their data to identify who these households might be and how to track the outcomes of early interventions 6 or 12 months down the line.
Councils could explore the £7.5 million Digital Innovation Fund from the MHCLG. This is a fund for councils to bid
for support in developing new digital solutions for their challenges.
Drawing on the expertise we have working with administrative data on low-income households, we’ve built a model that can be identify households at financial risk early and then track their progress against the support they receive. This offers huge opportunities for local authorities who want to create targeted awareness campaign, measure impact and make the case for further investment.
We partnered with UsCreates, now FutureGov, to design, develop and trial a data-led preventative service for Luton that works on the front-line, and whose impact can be measured.
After six weeks of analysing data and mapping Luton’s current homelessness service, front-line staff trialled a number of service changes with an initial cohort of customers we identified as being at financial risk. At eighteen weeks, we reviewed Luton’s feedback and crunched their data again, to present a more refined and localised view. Here we present some of the lessons learnt so far.
7 key lessons for Luton
Administrative data already collected by Luton contains a wealth of information on low-income households, which can be joined up to get a very in-depth understanding of someone’s financial situation.
By working directly with front-line staff to understand the characteristics of homelessness in Luton, Policy in Practice was able to design an indicator of homelessness risk which is based on homelessness patterns seen locally. Specifically, this indicator uses a measure of household financial resilience, which uses administrative data on household incomes to identify those likeliest to be facing high income shortfalls. It also takes into account how each individual resident is expected to fare under Universal Credit.
Full-service Universal Credit rolls out to Luton residents next month and front-line staff expect the reform will have a particular impact on the number of residents presenting as homeless.
Early tests suggest that this indicator captures a significant number of households currently in Luton’s homelessness service, so that it can be considered an accurate proxy for risk of homelessness. In the next few weeks, front-line staff will be using an online dashboard populated with data on Luton residents to identify households nearest to a homelessness crisis according to this measure, but who have not yet entered the service. These households will be checked by staff and contacted early if deemed appropriate.
Households identified early by front-line staff can be tracked over time. This is essential to verifying whether the service designed for an early intervention is working. Luton can select a group of households that they engaged with and track their income, employment and housing circumstances many months later.
In the context of the Homelessness Reduction Act, tracking can also help local authorities to evidence effective preventions, which it is required to record under the new legislation.
One of the key insights to emerge from our work so far, specifically from the interviews conducted by UsCreates with service users, is that the Council reaching out earlier (or in a different way) could have helped avoid a crisis. For example, service users who were affected by the Benefit Cap prior to becoming homeless, for example, told us that had they been contacted specifically about the impact the cap could have had on their housing situation would have helped them take action sooner.
Many people reported being confused by welfare reforms and complex policy, including their redefined role within the HRA. This was an obstacle to people understanding their situation and making decisions.
As a result, Policy in Practice and UsCreates are exploring how policy is communicated to service users, both by front-line staff and online. As part of this, we will be trialling how the Benefit and Budgeting Calculator can make complex information more relevant, engaging and personalised for service users.
One key insight from Luton is that service users can have very different needs. Some are particularly complex cases where support needs to be more holistic whilst, in other cases, a household could be diverted from crisis through ‘light-touch’ self-help, such as support with budgeting. We’ll be investigating the extent to which online tools or specific, themed workshops targeted to such cases can be effective in preventing certain people from becoming homeless.
Front-line staff in Luton are knowledgeable, personable and able to find tailored solutions for people during appointments. Both staff and clients reported this as a particular strength of the current system. An effective prevention service must therefore recognise and maximise time staff have for these in-person conversations. With Luton we’re exploring how a data-led approach can improve efficiency, for example in completing the Personal Housing Plan which must be completed to ensure compliance with the HRA. It also includes the ability to load up a case from the dashboard directly into the calculator, saving advisers time and meaning that people at risk of homelessness don’t need to repeat their story for the umpteenth time. We hope that making this quick and, where possible, automated, could gradually free up staff to deliver an excellent preventative service.
The factors behind homelessness in Luton are varied and complex, and often overlap over a range of services, responsibilities or departments. This has been recognised by Luton Council, where different departments are keen to collaborate, share their perspectives and highlight specific issues. Building and refining an indicator of financial risk to guide preventative action is a collaborative task that requires pooling data across departmental silos. Taking a council-wide approach to tackling homelessness can help drive future collaboration and data-sharing around strategic council issues.