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Using data to make devolution a success

Janet Harkin

Janet Harkin Published on 25th April 2017

You would be forgiven for thinking there is only one election in the coming weeks, yet in the second of two blogs on devolution we look at how local organisations can ensure that devolved funds are properly invested in addressing their area’s unique issues. Local elections across the UK next month, in which 6 city-regions will for the first time elect metro mayors, herald a new wave of opportunities to do this.

Read part one, Are UK Cities overdue a dose of devolution?, for an overview of the journey to devolution of power to British cities to date. In it we highlight new opportunities for Local Authorities, Local Enterprise Partnerships and other organisations who are working to ensure strong economic growth and cohesive societies.

Devolution demands local knowledge to work

Given the new opportunities opened up by devolution – including the landmark mayoral elections next month – one thing is clear: it is now more important than ever for cities to understand the characteristics of their residents and the specific challenges they are facing.

Many city regions will potentially soon have more powers over their own affairs, and this should be matched by in-depth knowledge of the local area in order to make devolution a success. A better understanding of your residents and their challenges allows you to unlock support for things such as skills and progression through better targeting, higher levels of engagement and allows cities to evidence the value of devolved public services more broadly.

Using data to understand households and household behaviour

Many local authorities are exploring ways to make better use of their data by combining different datasets, and building internal capability.

Housing Benefit data collected by Local Authorities can for example be used to identify households that are vulnerable, in terms of welfare reform or risk of poverty, plus the specific demographic characteristics of the most highly impacted households. For example, an understanding of which households are highly impacted by Housing Benefit caps, combined with information on rental market statistics, can be used by cities to identify households ‘at risk’ today of being ‘in crisis’ tomorrow.

In addition, joining up data sets over time on an ongoing basis allows for longitudinal analysis, enabling cities and city-regions to track the changing circumstances of individual households over time. This can start to provide an insight into household behaviour, including how they respond to support such as Discretionary Housing Payments, or employment support and allows for more detailed predictive analysis. Through this, cities can gain a better understanding of the types of households that would benefit from specific types of support, and provide a basis to target employment and skills funding that could be won from City and Growth deals, and demonstrate the impact of their invest to save models.

Identify your area’s needs and challenges

Using administrative data, cities can analyse struggling households by the barriers to work they face. From this, cities can lay out specific areas of concern to be tackled with funding from City and Growth deals, the European Social Fund or, potentially, devolved funding of the Work and Health Programme. For example, if disability or a lack of local, affordable childcare is a particular barrier to work, cities can set up a tailored programme to address these barriers.

Homelessness prevention: a challenge for many cities

Council data can also be used as a tool to target and hone support for homeless households, a particularly severe issue in English cities. Using administrative Housing Benefit data, cities can start to identify households that are at a particularly high risk of losing their home, either because they’re already in high levels of arrears, for example, or they live in an area with rapidly rising rental prices. Cities can anticipate these situations by using household level data to segment residents into ‘risk groups’, Croydon Council are using this to trial different interventions to see what is most effective in preventing homelessness.

The recently launched homelessness trailblazer, where the government is funding several local pilots that address and prevent homelessness in novel ways, is a unique opportunity to demonstrate the value of data and place-based approaches to homelessness. Another of the trailblazers we are working with plans to use this joined up data to identify the characteristics of households most likely to need housing support in the coming months, allowing them to intervene early.

Turning data into solutions: Croydon Council

Once a city has gained an understanding of its residents’ characteristics and the specific challenges or barriers they face, this can be packaged into an intervention for laser-like precision.

Skills funding for households in-work

Analysis from Policy in Practice, based on Croydon’s SHBE cohort dataset, was instrumental in the Council’s bid for joint funding from DWP and the European Social Fund to boost skills and enable progression for low-income employed households. Using the analysis, Croydon Council was able to identify low-income households earning the minimum wage, their demographic characteristics and from this demonstrate how these households could see their incomes increase through specific training and support. In part because Croydon was able to demonstrate an in-depth understanding of their local area, they were ultimately awarded the funding and are now working together with 4 other South London boroughs to ensure that households receive the support they need to progress.

The benefit cap

Using household level data, Croydon Council identified the characteristics of households due to be affected by the lower benefit cap of £20,000 (£23,000 in London) and from this segment the cohort into six different target groups.

Among these were 168 households that could potentially qualify from exemptions, plus a further 160 households that could qualify for exemption by simply working slightly longer hours (thus considered ‘quick wins’). By approaching these households before the implementation of the benefit cap, the Croydon Gateway & Welfare team helped 57 households escape the cap and worked with 138 more to help them cope with the effects of the cap within just six weeks. Figure 3 shows the mapping tool used by Croydon to pinpoint the different target households.

Visual showing a bar chart and a graph to illustrate that using LA-owned household data to order households by impact and map geographical location is recommended

Figure 3: Using LA-owned household data to order households by impact and map geographical location

The approach taken by Croydon can and should be copied by cities looking to maximise impact of new devolved funding, including to prioritise support to the most heavily impacted households, target support and evidence the effectiveness of devolving powers and financing for social support.

Conclusions

Devolution to UK cities has picked up speed in the past 10 years, to the point where newly created Combined Authorities are increasingly being given substantial powers over transport, tax collection and social care and support. With these new opportunities, however, comes great responsibility. Local authorities and city regions should seek to ensure that devolved funds are properly invested and tackle the area’s unique issues to deliver better social outcomes, and better return to taxpayers and other funders. This is even truer in the context of an uncertain future, namely Brexit (and what this could mean for the European Structural Investment Fund currently handled by LEPs) and the significant cost pressures that local authorities are facing.

In the face of these challenges, it is crucial that cities make the most of funding that they control by understanding their residents, identifying needs and designing bespoke solutions through smart use of data that is already available to them.

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