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How predictive analytics can help identify people at risk of homelessness

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Jade Alsop, Commercial Director and Louise Murphy, Senior Policy Analyst with Policy in Practice, were invited to speak at the Homelessness Conference in Leeds on the topic of How predictive analytics can help identify people at risk of homelessness.

For further information visit www.policyinpractice.co.uk, call 0330 088 9242 or email hello@policyinpractice.co.uk

Published in: Government & Nonprofit
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How predictive analytics can help identify people at risk of homelessness

  1. 1. Jade Alsop Louise Murphy Policy in Practice How predictive analytics can help identify people at risk of homelessness
  2. 2. About Policy in Practice Jade Alsop Commercial Director Louise Murphy Policy and Data Analyst
  3. 3. A team of professionals with extensive knowledge of the welfare system who are passionate about making social policy work We help local authorities use their household level data to identify vulnerable households, target support and track their interventions We develop software that engages people. We identify the actions people can take to increase their income, lower their costs and build their financial resilience
  4. 4. 444 Homelessness - what do we know?
  5. 5. Our policy work
  6. 6. Universal Credit roadmap
  7. 7. The drivers of homelessness
  8. 8. Around 5,000 rough sleepers in England and 8,000 in the UK A 15% increase on a year ago, and the 7th year numbers have risen Rough sleeping
  9. 9. The NAO concluded that government efforts to tackle homelessness could not demonstrate value for money The government needs to: • Evaluate effectiveness • Help local authorities share best practice • Help ensure housing supply meets housing need • Monitor the impacts of policies and interventions on homelessness NAO: A change in approach
  10. 10. 111111 Ask the audience: Do you use data to inform your homelessness strategy?
  11. 11. We work with household-level data Housing Benefit / Council Tax data, household level arrears / debt data from local authorities Data is processed by our Benefit and Budgeting Calculator Detailed view of household-level financial circumstances now and in the future Councils identify and engage households at risk before a crisis occurs
  12. 12. Our analytics We analyse the living standards of households now, and model their predicted living standards in 2023 This allows us to identify households who are coping now, but will be struggling in the future
  13. 13. 151515 How Croydon Council are using their data to uncover vulnerability
  14. 14. EngageIdentify Track people who need your support the most the impact of policy and effectiveness of interventions your residents with targeted support
  15. 15. Step 1. 34,186 low-income households in Croydon www.policyinpractice.co.uk
  16. 16. Step 2. 6,108 are unemployed with children www.policyinpractice.co.uk
  17. 17. Step 3. 316 live in the Thornton Heath ward www.policyinpractice.co.uk
  18. 18. Step 4. 93 are on Universal Credit, 15 will be worse off www.policyinpractice.co.uk
  19. 19. Step 5. Focus on one household
  20. 20. Step 6. Engage through tailored support
  21. 21. Step 7. Track the impact of your intervention 778 households (10.5% of 7,413) moved into work
  22. 22. 242424 Some other examples
  23. 23. Growing financial resilience Activity Analysed Housing Benefit and Council Tax Reduction data Identified £20 million in unclaimed benefits Outreach programme to encourage benefit take up Data insights Return on investment Food bank usage +1% in Greenwich vs +20% benchmark. Better use of limited support Measurable increase in living standards Services designed around prevention “LIFT has given us the opportunity to do targeted take-up work to increase the income of our residents.” Learn more
  24. 24. Prevention and reducing homelessness Activity HRA puts new responsibilities on councils… but 56 days is too late. Luton use their data to identify those e.g. in arrears, in shortfall, worse off on UC. Pooled with other data to enhance predictive capability “It makes no sense at all to wait until someone is in crisis. Interventions become less effective & engagement harder.” Data insights Return on investment 78 households identified initially Proactive outreach engaged 52 people in the first wave of calls. 42% of people took up the offer of support to increase their income. Fewer homelessness applications (£7.5k) and 10% fall in TA. Learn more
  25. 25. Target support: DHPs
  26. 26. 282828 Thank you Questions?
  27. 27. www.policyinpractice.co.uk Thank you Jade Alsop jade@policyinpractice.co.uk 07551 165172 Louise Murphy louise@policyinpractice.co.uk 0330 088 9242 hello@policyinpractice.co.uk

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