Deven Ghelani discussed how data analysis can identify children who are vulnerable at a recent symposium on Tackling Child Poverty. View his presentation and Twitter thread from the event below. 

Early intervention is vital to keep children out of poverty. This means that children’s services need to be able to identify those children who are most at risk, yet these vulnerable children are only recorded in children’s services datasets after they have been referred for critical support.

Even once referred, service records only hold information on the child themselves which means that service directors have no access to data on families’ social and economic context. This is exactly the kind of data that could be used to target early interventions at vulnerable children before the need for referral.

However, a detailed, ongoing record of low-income families’ social and economic data already exists and is routinely collected by every local council in the UK, albeit to administer Housing Benefit and council tax reduction schemes for low-income households.

Local authorities can analyse their household benefits datasets and visualise the resulting insights using a LIFT Dashboard developed by Policy in Practice. Using smart technology to securely process, store and analyse data, it is possible to link household benefits data with children’s service records to give local authorities a more comprehensive picture of child vulnerability. Councils can quickly and easily identify vulnerable children, target early interventions, and predict care demand.

Tackling Child Poverty: Building a Positive Future for Britain’s Youth from Policy in Practice

The challenge: children out of context

A child’s social and economic context plays a major part in determining their future welfare. The Department for Education currently only collects data on vulnerable children after they have been referred to a care service. These records focus exclusively on the child, without capturing any information on their family background.

The Office of the Children’s Commissioner (CCO) estimates that there are around 1.6 million children from low-income or materially deprived households in the UK who are at risk, a figure far larger than the 390,000 children recorded through referral to care services in 2018. Without access to data on those at risk of needing care, service providers are severely limited in their ability to intervene early and prevent children from reaching a point of crisis.

The solution: link children’s data with benefits data at the household level

Much of the information needed to measure the risk factors facing a child and their family is already routinely collected by local authorities as part of the Single Household Benefit Extract (SHBE). This is a local authority-owned, standardised monthly record of every household in a local authority area receiving either Housing Benefit or Council Tax Reduction (CTR). The extract contains all the household-level information needed to calculate Housing Benefit and CTR awards, including data on individual households’ incomes, family circumstances and disability status.

Policy in Practice currently processes anonymised SHBE datasets for more than 90 local authorities across the UK, giving them the ability to filter and track households at a click using a wide range of social and economic indicators. We do this via a bespoke Low Income Family Tracker (LIFT) Dashboard.

In its raw form SHBE datasets can be used to identify the following groups of at-risk children, as defined by the CCO’s vulnerability framework:

In addition, when processed through Policy in Practice’s policy engine we can also calculate three indicators of risk:

  1. Children living in relative poverty
  2. Children at risk of food poverty
  3. Children at future risk of poverty, for example as a result of policy changes or inflation

Local authorities can visualise and explore their data at borough, ward and household level using the LIFT Dashboard, a tool developed by Policy in Practice to help councils make more of the data they already hold. We have recently added a new Child Poverty screen, based on the CCO’s vulnerability framework, shown below. This animation shows how SHBE data can already be used to identify at-risk children, estimate potential service demand, and explore the impact of broader welfare policy changes such as the rollout of Universal Credit on child vulnerability.

Household level data can identify children at risk, target support and track changes over time.

By merging SHBE data with existing children’s service data, local authorities can gain a far more powerful information resource than either dataset offers in isolation.

With this linked data, it would be possible to:

  • Identify household characteristics, such as rent levels, or changes in circumstances, such as parents becoming unemployed, that increase the risk of need for children’s services
  • Estimate how much of an effect each factor has on overall risk, to identify which traits or events pose the greatest danger to vulnerable children
  • Calculate the risk of service referral for each individual child in the SHBE dataset, allowing support to be targeted at those most at risk
  • Estimate cost savings from early interventions targeted at family risk factors, such as costs avoided for each at-risk household whose status can be changed to ‘not at risk’
  • Rigorously evaluate the effectiveness of early intervention programmes by comparing ‘recipient’ and ‘control’ households

The impacts: children in context

As a general principle, merging datasets from different areas of public service helps to create a culture of collaboration across local government. By sharing and linking data, we can build a more complete picture of the complex, interconnected systems of care and welfare.

In the case of children’s services, linked data puts each child into a meaningful context. This allows vulnerable children to be identified early and to receive support before they reach the point of crisis. Information on family context can help service directors better estimate future demand, allowing resources to be targeted more efficiently.

Linking data on the child and their context also helps policy makers to better understand the processes behind child poverty. By improving our understanding of the problem, we become better able to solve it.

Benefits data can enable policymakers to understand which children are ‘at risk’ of being ‘at risk’

Tackling child poverty: building a positive future for Britain’s youth

Deven Ghelani, founder and director of Policy in Practice, joined an expert panel of speakers at Public Policy Exchange‘s Tackling Child Poverty: Building a Positive Future for Britain’s Youth symposium on Tuesday 5 March 2019.

Deven talked about how data analysis can be used to identify children who are vulnerable now and who are likely to be so in the future. He also showed how organisations can use their data to target support and track change. View his slides here and Twitter thread from the day, below.

Join our webinar: Using data analytics to understand child vulnerability

Our next webinar is titled Using data to understand child vulnerability and we’ll be discussing data analysis we’re doing for the Children’s Commissioner on children at risk. Please join us on Wednesday 17 April at 10:30 and share this invitation with your Children’s services colleagues.

We’ll share the impact of early analysis on specific policy reforms, including Universal Credit, the benefit cap and the two child limit, will have on levels of child vulnerability.

Join this webinar to hear:

  • Findings of analysis on that policy changes have had on child vulnerability
  • How data analysis can identify children at risk of being at risk
  • Practical actions local authorities can take to act preventatively

Register here

To learn more about Policy in Practice’s capacity for data linkage, or the benefits of this approach, please sign up to our newsletter, email or call 0330 088 9242.

Read a short summary of other talks from the symposium in the Twitter thread below.


Leave a Reply

Your email address will not be published. Required fields are marked *

Fill out this field
Fill out this field
Please enter a valid email address.

Register for an upcoming webinar

TitleDateStart TimeDurationRegister
Reducing barriers to work using data led campaigns In September 2023 the UK experienced an economic inactivity rate of 21.3% and an estimated unemployment rate of 4.3%, both of which have increased compared to previous data. Economic inactivity has surpassed pre-pandemic levels, prompting government efforts to integrate this group into the workforce.

Historically, policies under Universal Credit and legacy benefits emphasised pushing people into employment through conditionality and short term measures. Today, both major political parties are exploring ways to facilitate return to work and eliminate barriers to employment. However, the government is also extending conditionality and adopting a tougher stance on sanctions for a broader range of people.

Haringey is home to a young, ethnically diverse population. In June 2023, almost one fifth of those between 16 to 65 were on Universal Credit. Nearly 7% of residents over 16 were claiming unemployment related benefits, a figure above the London average of 4.7% and the 3rd highest rate of all UK councils

Haringey Council wanted to find ways to overcome barriers to employment for young people and families with children and has used data to achieve success with its employment support programmes.

Join this webinar to learn:

- The new carrot and stick policy changes designed to break down barriers to work and reduce economic inactivity
- What Haringey Council did to increase take up of free childcare for two year olds to 70%
- How Haringey Council successfully helped 95 NEETs on their employment journey

With guest speakers from Haringey Council
29/11/202310:30 GMT1.3 hours
Policy review of 2023 and what 2024 may hold Join our last webinar of 2023 to hear our policy analysts review 2023's policy changes and big issues, from the ongoing cost of living and energy crises to the funding of local government and the Autumn Statement.

We will highlight our policy findings from the year including our work that revealed that millions of households across the UK are missing out on £19 billion of support each year.

We'll look at the role that data is playing in helping leading organisations to tackle these issues.

Through case studies of different types of households we'll look at what the changes mean for families now, and what 2024 has in store.

Along the way we'll share the positive impact that organisations we work with ​are having, and give practical solutions that others can adopt.
6/12/202310:30 GMT1.3 hours
How the debt sector is connecting people to support31/1/202410:30 GMT1.3 hours
Skip to content
%d bloggers like this: