This summer Lord Bird, founder of the Big Issue, 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, to build a proactive and data-led approach to tackling homelessness. In this blog post we share 7 lessons learned so far.

“When we don’t avoid [homelessness], not only is it expensive [for local authoritIes] but the cost to individuals is considerable. That means that the interventions become less effective and engagement is much harder. It makes no sense at all for us to wait until someone is at a point of crisis.”

Nikki Middleton, Customer Services Manager, Luton Borough Council

Data and the Homelessness Reduction Act: an opportunity for a truly preventative service

The introduction of the Homelessness Reduction Act (HRA) in May of this year placed new requirements on how local authorities deal with homelessness. Many are seeing 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 is widely applied in a variety of sectors from weather forecasting to policing, to identifying young people at the biggest risk of becoming a person Not in Education, Employment or Training (‘NEET’). In fact, the original Policy Lab and 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 have introduced a new statutory data collection system called H-CLIC to track the prevention work that councils undertake. It systematically records preventative action for those identified as at risk of becoming homeless within 56 days. However, it does not capture the outcomes of any successful interventions taken before this 56-day threshold. Local authorities are increasingly interested in taking an early intervention approach, under the view that acting early is an often easier and cheaper way to prevent homelessness. Policy in Practice is helping councils use their data to identify who these households might be, and showing how to track the outcomes of early interventions 6 or 12 months down the line.

Councils interested in Digital Government and predictive analytics may want to explore the Digital Innovation Fund from the Ministry of Housing, Communities and Local Government (MHCLG). This is a £7.5 million fund for councils to bid for support in developing new digital solutions for their challenges.

The fundamentals of predictive modelling, which can be applied to range of sectors.

By drawing on our expertise working with administrative data on low-income households, Policy in Practice have built a model that can be used to identify households at financial risk early, and track their progress against the support they receive. This offers huge opportunities around creating targeted awareness channels, measuring impact and making the case for further investment.

UsCreates, who have extensive experience helping local authorities to re-imagine the services they provide, are supporting Policy in Practice to design, develop and trial a data-led preventative service that works on the front-line, and whose impact can be measured. To read more about UsCreates’ approach, read their blog about Luton’s work here.

After six weeks of analysing data and mapping out Luton’s current homelessness service, front-line staff have been trialling a number of service changes with an initial cohort of customers identified as being at financial risk by Policy in Practice’s predictive tools. At eighteen weeks, we took on board Luton’s feedback and crunched their data again, to present a more refined and localised view. Here we present what some of the lessons gathered so far by Policy in Practice and UsCreates are.

1. Data already held by Luton can effectively highlight risk

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.

Policy in Practice and Uscreates worked with Luton’s frontline staff to tackle homelessness using data and service design

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 will become available 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.

2. Tracking individual households is key to demonstrating a preventative service

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.

Luton Council uses a LIFT Dashboard to track the effect of interventions on households

In the context of the HRA, tracking can also help local authorities to evidence effective preventions, which it is required to record under the new legislation.

3. Acting early can prevent a crisis

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.

4. Clear communication of welfare reforms and policy changes is key

Many service users reported being confused by welfare reforms and complex policy, including their redefined role within the HRA. This was in many cases an obstacle to people understanding their situation and making the decisions that are right for them.

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.

5. Targeted self-help could go a long way

One key insight from Luton is that service users can be very different. While some are particularly complex cases where support may need to take a more holistic form, in other cases a household could be helped away 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. You can access a limited version of the Benefit and Budgeting Calculator used by Luton here.

6. The best service is tailored to the individual

Front-line staff in Luton are incredibly knowledgeable, personable and able to find tailored solutions to users during appointments. During interviews, both staff and service users reported this as a particular strength of the system in place today. An effective prevention service must therefore recognise and maximise the time that staff have available for these in-person interactions.

In the case of Luton, we are exploring how a data-led approach can make currently tedious parts of staff’s jobs more slick. This includes aspects such as the Personal Housing Plan, which staff are newly required to fill out in order 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.

7. There are opportunities to join up departmental silos

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 the Council in Luton, with different departments 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, which crucially requires pooling data across departmental silos. Taking a council-wide approach to understanding homelessness, therefore, can set the precedent for future collaboration and data-sharing around strategic council issues.

Next steps: trial, refine, repeat

Over the next few months, Policy in Practice and UsCreates will be trialling and evaluating different service changes with the homelessness team at Luton Council.

The LIFT dashboard will enable staff to determine the impact that these changes are having a few months down the line. For example, it will be possible to see whether households in rent arrears and with other debts who are offered budgeting support have been able to lower their arrears (and therefore their risk of becoming homeless), after 6 months. This is key to highlighting the potential benefits of investing in a data-led, preventative approach to tackle homelessness.

To find out more about how councils like Newcastle City Council and Luton Borough Council use their data intelligently to build a proactive and preventative homelessness service listen back to our Use your data effectively to identify and prevent vulnerability webinar here. Contact us for more information on our work with Luton via hello@policyinpractice.co.uk or 0330 088 9242.

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