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Customer Insight Seminar Chartered Institute of Housing 3 September 2013 at 3.30 pm De Montfort University, Leicester Claire Higgins Director of Operations Cross Keys Homes, Peterborough

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Customer Insight Seminar

Chartered Institute of Housing 3 September 2013 at 3.30 pm

De Montfort University, Leicester

Claire Higgins Director of Operations

Cross Keys Homes, Peterborough

Cross Keys Homes took over the management of the housing stock

from Peterborough City Council on October 4, 2004 and are Peterborough’s largest housing association

We manage over 10,500 properties providing homes for tenants, older people, shared owners and leaseholders and lease over 70 shop units, rent out garages and manage temporary accommodation.

Turnover of £40m pa 250 employees Area with high levels of deprivation – several SOA’s with top 10% in

the country Life expectancy 10 years less in some areas Highest unemployment in East Anglia (5%) 25% under 24s out of work Low educational attainment historically 66% on benefits (full and partial)

Cross Keys Homes – Who are we?

The practicalities How we did it What data we are collecting and how we are using it

WHO – demographic data WHAT – behavioural data WHY – attitudinal data Listening and learning

Discussion

Cross Keys Homes resident census project

"The danger is that if housing providers don't get to know who their tenants are, then they may not meet

everyone's needs“ David Pipe, CIH, July 2011

How we did it

Formic provide the software “Fusion “ to create,

complete and upload the census to QLx which is our housing management system.

Invu allows the viewing of the completed census as

was done on the day, this is a blueprint as such

Alto Digital are the re-seller and all licenses are

through them. They also completed the initial set-up and configuration.

QlikView software used to analyse the data that has

been collected via the census, e.g. user friendly dashboards

Began census project in 2011 Visited 100% of customers using remote laptop technology to

capture data, looking at: Employment status State benefit claimants Bank account availability Literacy / Numeracy Mobile phone usage / Broadband connectivity Health matters Skills gaps

Insight driven service offer: Identified 275 tenants affected by under-occupation measures

to target down-sizing options Targeted support to help tenants set up bank accounts Introduced a laptop loan scheme to support digital inclusion Introduced payment of rent via phone apps

Background

What data should be gathered? Tenant circumstances – household size, number and age of children Geographical trends – neighbourhood effects of welfare reform Are specific groups likely to be disproportionately affected e.g. large

families, people with disabilities, BME groups Overlapping impacts – some households will be affected by more

than one welfare reform measure Up-to-date stock information (including size) How many tenants are under-occupying and by how much Who will be affected by the benefits cap Households in work and out of work Digital inclusion or exclusion Preferred rent payment options Preferred methods of communication Protecting tenants from loan sharks

Background

An evolutionary step from the tenant verification visit. Focus shift to customer insight from data collection. Investment in technology and software to underpin efficient

working practice and to maximise data capture and utilisation.

Data to inform service development and planning. Data to be mainstreamed to become a day to day tool for

managers and front line staff.

Journey map

“One of the first things we learned from the demonstration project was that

landlords did not know as much as they might have thought about their tenants.” Lord David Freud, Inside Housing, 21 June 2013

Everything nearly! Under occupation Overcrowding Aspirations Income levels and sources Disabilities Economic status Household composition

What is covered?

Satisfaction with: Landlord Home Neighbourhood Neighbours Facilities

Emerging themes: Internet access/PC ownership Mobile phone ownership Mythbusting - employment Benefit dependency levels Occupation levels Support needs, adaptations, etc

Household composition

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

One adult under 60 23%

One adult aged 60 or over 12%

One parent family with child/ren at least one

under 16 22%

Two Adults under 60 9%

Two Adults at least one 60 or over

7%

Two parent family with child/ren at least one

under 16 15%

Three or more adults 16 or over

6% Other

6%

Economic status

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

Full Time Work 14.39%

Part Time Work 11.30%

Part-time Student 1.27%

Gov training/New Deal 0.19%

Job Seeker 16.60%

Not in Emp, Edu or Training 0.84%

Long Term Sick\Disabled

16.88%

Not Seeking Work 17.39%

Retired 15.52%

Other 5.63%

Economic status contd.

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

Full Time Work 14.07%

Part time work 6.54%

Full-time education at school , college or

university 1.51%

Part Time student 3.73%

Government training/new deal

0.33%

Job Seeker 9.16%

Not in Emp, Edu or Training 0.92%

Long Term Sick\Disabled 7.07%

Not Seeking Work 11.45%

Retired 8.51%

Child<16 29.32%

Other 7.40%

Sources of income (all from state benefits/pensions)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

No 34%

Yes 66%

Sources of income (Partly from state benefits/pension)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

No 86%

Yes 14%

Sources of income (Working)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

No 78%

Yes 22%

Sources of income (Occupational pension)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

No 97%

Yes 3%

Payment method (Rent)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

By post/cheque 1%

Cash 54%

Credit card/bill pay 9%

Direct debit 20%

Internet 10%

Pay zone 3%

Standing order 3%

Tenants with bank accounts

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

Yes 95%

No 5%

Homes with broadband

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

No 40%

Yes 60%

Nationality (tenant 1 & 2)

Data based on surveys

from 2200 households

“connect with us refresh”

2012/13

UK National Resident, 1779, 92.27%

Any other country, 23, 1.19%

Lithuania , 21, 1.09%

Poland, 20, 1.04%

Portugal, 20, 1.04%

Slovakia, 18, 0.93%

Afghanistan, 11, 0.57% Iraq, 8, 0.41%

Latvia, 7, 0.36% India, 6, 0.31%

Pakistan, 4, 0.21% Czech Republic, 3, 0.16%

Italy, 3, 0.16%

Hungary , 2, 0.10%

Other European, 2, 0.10%

UK National Resident Returning, 1, 0.05%

Dissatisfac

tion with

Neighbour

hoods

Dissatisfac

tion with

facilities

for younger

people

City wide breakdown

Dissatisfaction with

neighbours

Dissatisfaction with facilities for younger

people

Dissatisfaction with

Neighbourhoods

City wide breakdown

For example • Aids and adaptations • Involving residents – new approaches • ASB

Data analysis has been directly utilised • Local offers • Downsizing • Patch profiling for Neighbourhood Managers

Provided a valuable resource for impact analysis of government reform agenda

• Tenancy sustainability manager • CSR • Localism • Welfare reform

Service design and planning

Outputs have been mainstreamed throughout CKH

Informing baseline positions for projects

Planning - Herlington

• Drilling into demographics: age bands, children and young people, disabilities, economic status.

• Enabled direct link to delivery of projects to target relevant resources.

• Tap into anyone expressing interest in being involved.

• Able to establish successes of outcomes, by measuring satisfaction with area, neighbourhood, facilities, who became involved as a result.

Understanding our customers – Patch profiling

• Enabling NM’s to inform where to begin the next round of census

• Prioritising and targeting groups of specific tenants for any number of reasons:

• Working 4 u referrals/NEETS

• Troubled families

• Matching under and over occupation

• Mainstreaming focus groups and local offers

looking at satisfaction levels

Staff awareness

• NMs identified 20% of their patch for the refresh (2012/13)

• The refresh involved more office checks before

the visits, which will focus on mitigating the impact of welfare reform, tenancy and benefit fraud, fuel poverty, financial exclusion etc.

Census refresh

Early intervention • Financial capability support • Training/work programmes – tailored assistance • Literacy and numeracy • Proactive approach – tenancy sustainability

manager Downsizing – The statistics* • 202 Households moved • Released 604 bedrooms • 1208 bed spaces made available to households in

need • 140 of people who downsized were of working age

(69.3%) • Trends identify that people downsize within their

current area of residence (117 out of 202 – 58%) *as at July 2013

Welfare reform & Downsizing

• Over 1000 tenants have been contacted regarding Employment and Education advice with many referrals to the working 4 you scheme.

• Over 250 have been contacted regarding Improving Health advice to which some

tenants have been successful in reducing or stopping smoking. • Over 160 tenants have been contacted who have a need for Disabled Adaptation

with direct actions taking place eg the installation of grab rails. • Over 200 tenants have been contacted regarding a concern that they have with

anti-social behaviour which could have been unreported.

Outcomes

• Over 2100 tenants have expressed an interest in becoming

involved from attending an area panel, becoming a member of the scrutiny panel or a key virtual email contact.

Thank you for listening

Questions