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
2. About Policy in Practice
Jade Alsop
Commercial Director
Louise Murphy
Policy and Data Analyst
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
9. 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
10. 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
12. 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
13. 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
15. EngageIdentify Track
people who need your
support the most
the impact of policy and
effectiveness of
interventions
your residents with
targeted support
24. 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
25. 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
So before we get into how we have done that – it would be good to get a show of hands on whether you are currently using a data led approach and whether you are looking for ways to improve that.
No hands- OK so
So I walk you through our data led approach and what data we use to do this
Louise has mentioned what we do and how we do it
but whats important here today is how this has supported organisations to address current homelessness
and prevent future homelessness