NAWRA conference: Using data to inform work on poverty
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The document outlines the Living Standards Index for London, developed by Policy in Practice to analyze poverty and inform policy decisions. It details how data analytics assist local authorities and other organizations in understanding living conditions, supporting low-income households, and facilitating operational strategies to mitigate poverty impacts. The initiative, backed by the Trust for London, aims to provide evidence-based insights and resources for effective interventions in response to welfare changes.
NAWRA conference: Using data to inform work on poverty
- 1. Zoe Charlesworth Policy in Practice The Living Standards Index for London Using data to inform work on poverty
- 2. Content ā¢ A brief background to Policy in Practice and how data analytics informs policy ā¢ The Living Standards Index for London ā¢ How this translates to frontline operations 2
- 3. Policy in Practice A social policy organisation that uses data analytics to: ā¢ Inform an understanding of the depth and breadth of poverty ā¢ Provide evidence-based research on the impact of policy ā¢ Formulate evidence-based policy solutions that feed into national conversations ā¢ Provision of operational tools: - to allow those on low income make informed choices - to support those working with households on low income: Local authorities, Housing Associations, Charities, Welfare advice organisations 3
- 4. Housing Benefit / Council Tax data Benefits Modelling Engine Rich, detailed impact assessment Analytical Engine + Household datasets 4
- 5. Policy in Practice āData is already used to detect fraud and chase arrears, so why not use it to help citizens?ā Sue Nelson, Social Interest Group, formerly at Luton Borough Council 5
- 6. The Living Standards Index for London Living Standards Index for London Supported by Trust for London Policy in Practice is tracking changes in living standards for almost one million Londoners on a monthly basis. Using benefit administration data from 18 London councils to track: ā¢ Income ā¢ employment ā¢ Poverty Currently being updated to show: ā¢ Impacts relating to homelessness risk ā¢ Differing poverty/need measures (including Social Metrics Commission, Minimum Income Standard) 6
- 7. The Living Standards Index for London Living Standards Index for London Supported by Trust for London Some headline figures ā¢ 15% of Londonās low income households canāt pay the bills week to week ā¢ Biggest growth in cash-strapped families since 2016 was in Sutton (79%), Camden (40%), Southwark (43%) ā¢ The number of London families who canāt pay the bills is expected to triple to 238,000 by 2021 if nothing changes 7
- 8. The Living Standards Index for London 8
- 9. The Living Standards Index for London 9
- 10. The Living Standards Index 10
- 11. The Living Standards Index 11
- 12. How is this used? A detailed analysis of poverty now, and in the future, provides evidence to: ā¢ Feed into national conversations on the implications of welfare reform ā¢ Inform pan-London Economic strategies ā¢ Inform pan-London anti-poverty and support resources ā¢ Provide an understanding of the implications at the borough level ā¢ Feed into borough economic and strategic planning ā¢ Provision of informed anti-poverty and support strategies at borough level This is a free resource, visit: http://policyinpractice.co.uk/lsi-london/12
- 13. Using data at an operational level The ability to be pro-active to changes in welfare support Crisis Prevention through intervention ā¢ Identification ā¢ Targeting ā¢ Engagement ā¢ Support - Advice and information (preparation for change) - Employment support - Income maximisation 13
- 14. Pro-actively using data to prevent crisis Example: targeting low-income self-employed households PIP analysis shows that the self-employed will be on average Ā£50/week worse off under Universal Credit due to the Minimum Income Floor ā this is a significant drop in income and could cause crisis. Our longitudinal analysis shows that of those affected by the minimum income floor 74% move to unemployment, 25% to employment and less than 1% stay self-employed. The Budget 2018 extended a 12 month grace period from the minimum income floor to all self-employed moving to Universal Credit under managed migration This gives support agencies 12 months to contact these households and provide the information they require in order to make decisions to protect themselves from crisis. 14
- 15. Identify households likely to be affected 15
- 16. Target those that will need support E.g. Households with children and those with low financial resilience. This reduces the 1,272 self-employed households to 317 16
- 17. Pro-actively engage with these households Inform (and illustrate) income under Universal Credit initially and after 12 months In this case, a reduction of Ā£316/month in household income 17
- 18. Consider options Show the impact of remaining self-employed or leaving self-employment to both unemployment and the equivalent hours worked in employment: 18
- 19. Outcome-focused If relevant, provide employment support 19
- 20. Knowing expected income ā and why 20
- 22. Using data at an operational level London Borough of Greenwich Provides the Welfare support team with the ability to offer pro-active and holistic Support Council-wide outcomes ā¢ Targeted help reduces the number of evictions and ultimately reduce homelessness across the borough. ā¢ Strategic decisions based on evidence-based trends and forecasts ā¢ Support for additional funding (e.g. Flexible Support Fund) ā¢ Better use of expert resources such as Welfare Advisors 22
- 23. Using data at an operational level London Borough of Greenwich Provides the Welfare support team with the ability to offer pro-active and holistic Support Outcome for residents ā¢ Support through change and at times of crisis ā¢ Targeted communications to inform and engage with those affected by change ā¢ Assistance with income maximisation and budgeting (Identified up to Ā£20 million per year of unclaimed benefits) ā¢ Provision of an understanding of probable income and how this is calculated ā¢ Provision of employment support (if relevant) 23
- 24. Using data to support work on low-income and poverty 24
- 25. Next steps: Living Standards Index This is a free resource, visit: http://policyinpractice.co.uk/lsi-london/ Start conversations with your local authority about using data Case studies: www.policyinpractice.co.uk Feed frontline knowledge into our calculator development: zoe@policyinpractice.co.uk 25
Editor's Notes
- #5: BRADFORD Governments may know how one policy affects many people. We can show how all policies combined affect one person. We work with household level data from over 40 different local authorities to Welfare reforms we model, and how accurate we are.
- #9: Not enough income to meet outgoings. How we define outgoings Differences regionally ā Barnet 25% Greenwich 10% Can choose a particular group to look at eg by household composition: those most likely to not be able to manage outgoings are couples with children 16% do not have enough income to cover costs
- #10: Can see the change by 2021 Takes account of expected welfare benefit changes ā in this case particularly UC ā wages, rents and outgoings Increases from 15% currently to 61% of those on benefits. Regional differences with the biggest changes in Ealing with an 89% rise and the lowest in Hammersmith & Fulham with a 23% increase Again, we can look at a particular cohort, in this cse by tenure and see that private tenants are most affected with a 118% increase in those that cannot meet their outgoings
- #11: There is a particular focus on Universal Credit. This shows that 42% will be worse off under UC and 36% better off We can see the results regionally and that Islington Croydon and Sutton have the highest proportion of households worse off Again we can choose cohort. And we can see that tenants are more likely to be worse off than owner occupiers or those in supported accommodation
- #12: The Index also provides a poverty measure. We developed this prior to the SMC measure to take account of outgoings. This shows the proportion of households who have a cash shortfall, those struggling and those coping. Aggain by tenure and cohort ā this shows that if you are a private tenant or in Barnet, Enfield and Camden you are more likely to have a cash shortfaull
- #13: To Ward level Changes: poverty measure: Minimum Income Standard Social Metrics Commission ā Total Resources Avaailable Trigger Figures ONS deciles Housing affordability Change in LHA - Change in market share of tenure Initial findings - In London, average private tenant has rental costs 57% of their income 97% have rental costs higher than the LHA
- #16: Imagine the Living Standards Income and being able to identify the households? LIFT Dashboard has a much larger range of options for targeting those affected by welfare reform ā will show this
- #17: With children and low financial resilience. So unlikely to be able to cope with an income shock