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Homelessness Statistics User Engagement Andrew Presland, Joss Bass, Jeremy Hicks

DCLG Statistics User Engagement Day - Homelessness

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Page 1: DCLG Statistics User Engagement Day - Homelessness

Homelessness Statistics User Engagement

Andrew Presland, Joss Bass, Jeremy Hicks

Page 2: DCLG Statistics User Engagement Day - Homelessness

Statutory homelessness framework

• Housing Act 1977, Housing Act 1996, and the Homelessness Act 2002

• Applicants who apply for assistance who are eligible, unintentionally homeless and in priority need are owed a ‘main homelessness duty’

Page 3: DCLG Statistics User Engagement Day - Homelessness
Page 4: DCLG Statistics User Engagement Day - Homelessness
Page 5: DCLG Statistics User Engagement Day - Homelessness

User Engagement

• Consider the P1E from two perspectives– Data providers (local authorities)– Data users

Page 6: DCLG Statistics User Engagement Day - Homelessness

How can we improve our statistics without increasing local authorities’

workload?

• ‘Goldilocks’ problem

Page 7: DCLG Statistics User Engagement Day - Homelessness

How can we improve our statistics without increasing local authorities’

workload?

• We hope to answer this question by– Generating ideas– Constructive, honest critique– Audience participation– Feedback sheet

Page 8: DCLG Statistics User Engagement Day - Homelessness

Summary of session

1. Data user presentation – Homeless Link, Rachel Coffey Research Manager

2. Data provider presentation– Charnwood Borough Council, David Scruton

3. Group discussion & feedback – You!

Page 9: DCLG Statistics User Engagement Day - Homelessness

What’s behind the numbers?

DCLG stats user engagement day

Rachel Coffey

Research Manager

Page 10: DCLG Statistics User Engagement Day - Homelessness

Who are Homeless Link?

• National membership charity

• Over 500 members

• Work to make services better

• Campaign for policy change

• Homelessness Transition Fund

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How we use P1E data

Homeless Watch

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How many people are homeless?

Rough sleeping counts

SP data

Own research

Acceptances up by 1/3

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Page 14: DCLG Statistics User Engagement Day - Homelessness

Why are people homeless?

Tenancy problems

Page 15: DCLG Statistics User Engagement Day - Homelessness

Where are homeless people going?

The number of households in TA in another local authority has doubled in three years

Page 16: DCLG Statistics User Engagement Day - Homelessness

Affordability of renting

Share of affordable properties in London under the Shared Accommodation Rate

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Policy and research

• Welfare reform – sanctions, LWA

• Health of homeless people – dual

needs

• Improving evidence-base for the

sector

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Contact

• Rachel Coffey

• 020 7 840 4422

[email protected]

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DCLG User Engagement Day

Homelessness Session

David Scruton, Charnwood Borough Council

Page 20: DCLG Statistics User Engagement Day - Homelessness

What I’ve been asked to cover

• How easy is P1E to complete (obtaining and submitting figures)?– And how many people are involved each quarter– How much data is directly from systems and what

needs processing• How easy would system changes be?• Do we already hold additional useful information?• Are the statutory homeless publications useful to

LAs?• How might we improve the P1E?• (and a couple of words of caution of my own)

Page 21: DCLG Statistics User Engagement Day - Homelessness

My experience of the P1E

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How easy is the P1E to complete?

• Down to the quality and completeness of the data

• A lot of the information is routine, but…

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Collecting data• Ongoing cases give an opportunity to fill

the gaps

• But some clients you’ll only interview once, for a relatively short period of time in sometimes quite charged conditions

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Page 25: DCLG Statistics User Engagement Day - Homelessness

Data Issues• Significant difference between

period data and snapshot

• Easy to refine and rerun the period data

• Numbers in temp is snapshot of where people slept that night

Page 26: DCLG Statistics User Engagement Day - Homelessness

Snapshot Data• Often information isn’t updated until at

least following day

• Particular issue if quarter ends over weekend or holiday as may have been out of hours placements

• Difficult to rerun the snapshot as other cases will also have been updated

• Inevitable there will be some manual processing

• and the P1E form is very unforgiving

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Data ValidationYou appear to be losing the will to live, are you completing the P1E?

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Other issues

• Navigation is clunky making it difficult to work through errors- both within screens and between

• Problems printing• Guidance not particularly user friends and

entirely text based• People don’t understand the nuances- eg

hierarchy of priority need reasons• Mapping to the P1E categories – eg Couples• Not supporting recent browsers

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Who’s involved

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Prevention and Relief

• Involves a range of partners

• Takes time to collate at the end of the quarter

• Balance between data protection and double counting

• Advice and information vs assistance or intervention– Provided on a casework basis

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Changing the system• Depends on what, when and how• Depends on local set up• Need enough notice – IT and paper forms• Lots of different IT systems and suppliers

so likely to be cost and time delay• Need to ensure changes are

communicated to the right people• Who can suggest changes?• Where does it sit with the single data list

commitment?

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Do we hold related information that could be provided if requested?

• Inevitably

• But not necessarily the same information in the same format as other authorities

• Challenge will be developing a standard dataset everyone can easily provide

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How useful are the published statistics?

• Useful to a degree but quite limited global information published

• There’s a huge dataset going back 13 years but no obvious way of mining it

• LAs have some ability to interrogate the historic data but it’s time consuming and difficult

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Some caution around the data

• Are you comparing like with like (ie non-priority cases)?

• Are noticeable local changes real or changes to reporting methods?

• Can you cross validate? ie P1E against CORE against LAHS

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Suggestions for improvement

• Improve navigation

• Proper user friendly guidance notes

• Plain English error reporting

• Clear alert to the right people when system needs to change

• Improved printing options

• A reporting tool

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Page 37: DCLG Statistics User Engagement Day - Homelessness

Group discussion

1. How can we improve our statistics in a way that does not increase the burden on local authorities?

2. Is there anything else about the P1E homelessness statistics that you want to feedback to us?