Countries across the globe are using data to support their citizens. This blog highlights some good examples of where data analysis is focused on addressing vulnerability.

Using data in the USA, New Zealand and in the UK to improve outcomes for vulnerable children

Data analytics can be used to drive real change in children’s lives. An article published by KPMG brings out some of the best examples. These include:

  • Work in California using data on over 2 million children to predict how factors at birth can forecast risks of abuse by the age of five
  • An open data collaboration in the same state to track the effectiveness of children’s welfare services
  • A scheme in New Zealand that allows parents to choose and track their child’s journey through the state support system. 
  • Work for the Children’s Commissioner to model the effect of welfare reform here in the UK.
  • New York using the demographic characteristics of children to forecast demand for welfare services

1. California: Berkeley University Center for Social Services Research links household characteristics at birth to risks of abuse by the age of five

“Researchers at the Center for Social Services Research at the University of California at Berkeley released a study that tracked over 2 million children in 2011. They were able to identify specific factors at birth that were linked to higher rates of reported or substantiated abuse by the time a child reached age five”

2. California: The Child Welfare Indicators Project identifies children most at risk of being harmed in real time

“The California Child Welfare Indicators Project provides an open source database of customisable information on the state’s entire child welfare system. Data can be filtered by year, country, age, ethnicity, gender and placement type, among other categories. Child welfare agencies are thus increasingly able to identify in real time the children most at risk from being harmed and to target their interventions accordingly”

3. New Zealand: Smart Start tailors information about early childhood services and establishes a newborn’s future digital relationship with government

“New Zealand has launched a predictive tool focused on those who need services, rather than those who provide them. SmartStart gives parents a customized timeline based on their personal profile. It provides tailored information about early childhood services, and establishes a newborn’s future digital relationship with government. The service can be used by professionals working with expectant mothers or new parents, but it’s the parents who control which agencies have access to their information”

4. UK: Policy in Practice uses data from 120,000 families to analyse the impact of welfare reform on children in low-income households

Here in the UK,  we have recently completed a project with the Children’s Commissioner using data from over 120,000 families to evidence and analyse the impact of welfare reform on children. We found that the number of low-income families with children who will struggle to make ends meet will jump from 13% to 25% as a result of recent welfare reforms. Our Low Income Family Tracker (LIFT) Dashboard allows local authorities to spot these children at risk, create and implement tailored interventions and track the effectiveness of those interventions.

5. New York City:  Administration for Children’s Services and KPMG use children’s demographic characteristics to determine the probability of a child requiring support

Another example of how data can be used to model demand for support and flex resources to match that demand is in New York;

“The modelling approach not only accounted for events while an individual was within the child welfare program but also developed child demographic characteristics, and then evaluate the extent to which these events demographics could determine the probability of a child staying within or leaving the program. 

“The model can be re-run with updated data to refresh forecasts for the number and types of services and facility places that are needed over any given period. That means the ACS is better able to plan and budget, therefore to negotiate with vendors and facilities. In other words, improved service planning leads to improved service responsiveness and efficiency”

How data is being used to prevent homelessness

Citizens’ interaction with the state creates data that can help authorities identify risks of homelessness early, and take action. Here in the UK a great deal of this information can be gathered from data associated with the provision of welfare, as we highlight below with an example from Luton. In New York, CAMBA, a non-profit agency, has partnered with the city authorities to use data to identify those at risk of homelessness and to take informed action to help families proactively avoid crisis and receive the right support. Data includes tenure types, age and marital status.

6. New York City: CAMBA Collaboration creates a heatmap of greatest risks of homelessness in New York

“Proprietary software is used to map these factors and related data on Google maps, producing colour-coded dots to show the concentrations of people of the greatest risk for homelessness. Different colours represent factors such as a prior visit to a housing court or to a shelter. Field workers can click on a dot to see family composition and other details, and then organise their caseload accordingly”

Map of New York highlighting clusters of families who avoided homelessness through CAMBA’s homelessness prevention services.

7. UK: Luton Council proactively tackles homelessness using data analytics

Policy in Practice partners with local authorities, using data from the benefit system to model and map risks of homelessness within a borough.  Luton Council has used this data led approach to build and implement a completely new approach to homelessness prevention based on early identification of risks and tailored responses.  Through the recent integration of our Benefit and Budgeting calculator users can also click into a household and create an individual, tailored plan for the household at risk.

Policy in Practice helps local authorities to identify vulnerable people who need support by analysing and modelling their anonymised household-level data.

Read more about Luton Council’s work with data here

8. UK: Croydon Council uses its data to tackle household poverty early

Croydon Council has adopted an early intervention and prevention approach to helping families affected by welfare reforms. Called Gateway, the award-winning programme uses tools, including a LIFT Dashboard developed by Policy in Practice, to help it identify households at risk and target tailored support to people before they reach crisis point. The approach sees the council using its own data to proactively tackle poverty and prevent homelessness.

To date, the programme has helped over 2,000 families avoid homelessness through support with budgeting, benefits and employability advice.

Read more about Croydon Council’s work with data here

Policy in Practice helps local authorities to identify vulnerable people who need support by analysing and modelling their anonymised household-level data. Visual for illustration only.

Positive use of data can help society’s most vulnerable people

We are proud that so many of our clients are part of a global movement, using data as a force for good.  We also know that there is a lot more we can do to harness the power of data to improve outcomes for citizens. Data exists right across central and local government that can be used to help people to avoid crisis. These datasets, such as health care data, adult and children’s services data and of course the data generated from the provision of benefits.

Next steps

Croydon Council’s Gateway service has won the prestigious Delivering Better Outcomes award at The MJ Awards 2019. Ahead of the awards ceremony Julia Pitt, Director of Gateway Services, joined us talk about the programme, the results it’s achieved so far and the impact it’s having on Croydon’s residents. Listen back here.

Register for an upcoming webinar

TitleDateStart TimeDurationRegister
How data can help you target your Household Support Fund and other discretionary funding Covid-19 has hit low-income households in the UK hard. Universal Credit claimants more than doubled during the past two years, reaching an all-time high of 5.8 million people. As many as 8.9 million jobs were put on furlough and the poorest fifth of households in the UK saw an average fall in earnings of 15%.

To help councils navigate the aftermath of the pandemic the government has introduced a £500 million Household Support Fund, helping vulnerable households to cover their fuel, food and utility bills.

It will be vital for local authorities to use data to identify residents who are struggling or in crisis for targeted support from the Household Support Fund and other discretionary funding.

Sutton Council, like many councils, are using their administrative data creatively to ensure their residents are getting the right support at the right time. They have used insights from their own administrative data to identify and target support to over 500 households, supporting residents with a range of discretionary funding, including DHP and crisis payments, to boost income and sustain tenancies.

Join this webinar to hear:

- How councils can use their data to target their discretionary funding to support vulnerable households before crisis hits
- Sutton Council’s innovative approach to tackling their resident’s Covid-19 income shocks
- How Sutton Council use automated data refreshes to respond to struggling residents more effectively

We will be joined by guest speaker, Julian Clift, Welfare Benefits Advice and Support Manager, Sutton Council.
17/11/202110:30 GMT1.5 hours
Register
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