Embedding Customer Insight into the        Corporate Culture             Cheryl Coppell            Chief Executive       L...
Where is Havering?•   Situated in Outer North East    London, Havering is the third    largest London borough by    area a...
Havering’s Population• Total population of 236,100• 5.38% above 80 (compared to 3.39% for London)
Population Projections                  • Population +11.5% by 2021, faster                    than London average        ...
Deprivation             Ward        No. of LSOAs   IMD Average   RankGooshays                      9            34.14     ...
Havering’s HealthAreas for Improvement • Early help for vulnerable people in   the community • Dementia – improved   ident...
Challenges facing the Council• Significant budget savings: £40m by 2014• Very low grant base = high council tax• Already v...
The Havering 2014 programme             • Transformation programme               will enable us to meet new               ...
Our Transformation Objectives• 3 ‘change’ principles   – To be efficient, focussed and fair• The sort of council we want t...
Using Customer Insight to target services• We have been developing a tool to target residents based on  their characterist...
The Over 65s Volunteer Consultation Project
Aims of the Project• Aims and purpose of the project evolved as the project  progressed!• Consult with vulnerable older pe...
Targeting Specific Older People• We used our customer segmentation tool to target  older people based on the following ind...
Using Customer Insight to Target             Consultation• This identified 5000 residents over 65• Identified a sample of ...
Project DeliverablesOriginal Targets:     • 500 older people contacted or visited     • 150 referred to Council and Partne...
Outcomes• Early Intervention Successes:     • CAB advised a resident living in hardship who is now       £120pw better off...
Other outcomes• Increased skills of the volunteers• Face to face service highly effective and well  received by customers ...
A corporate programme of using   customer insight to target services• Targeting Energy efficiency grants – 25% more take- ...
Any Questions
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Embedding customer insight into the corporate culture Cheryl Coppell, London Borough of Havering

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  • 0-15 = 19%, working age 60%, 21% older population Highest proportion of older people of retirement age in London 5% of our population are over 80, compared to London average of 3% over 80 Low ethnic diversity (89% white, 11% BME) although this is predicted to grow over time
  • An extra 27,000 people by 2021 Population growth means more births and less people dying – pressure on services eg. schools Net migration means more people moving into the borough than leaving – pressure on services esp. housing
  • Overall Havering ranks 177 th out of 354 local authorities for deprivation = not very deprived 2 areas in Havering fall within the 10% most deprived in the country (Briar Road and former Mardyke estate)
  • Generally, the quality of life in Havering is very good. We have higher than average life expectancy. We are developing a Health and Wellbeing strategy with our CCG and Shadow Health and Wellbeing Board that will look at the following areas that are a priority for Havering. I want to ensure that we are targeting the right support at the people who need it the most.
  • The first Mosaic tool we purchased was too generic and not specific enough to Havering. We wanted something that would factor in all the information we currently had on our customers and which services they use – and what other services, such as payment by direct debit, we could be targeting specifically at them.
  • The project started out as a consultation and information sharing engagement project. Whilst the volunteers were carrying out household visits, by spending half an hour with older people in their homes, they were able to identify ‘early warning’ signs, such as evidence the older person was having difficulty carrying out daily chores or had work that needed doing to their homes to prevent slips and trips – they were able to make referrals to the relevant agency. The project became an early prototype for a volunteer-led early intervention programme we are setting up in Havering, based on this success.
  • If it wasn’t for the customer segmentation tool, we would never have been able to target precisely the older people we wanted to make contact with, who met our target group We really wanted to contact those older people not currently known to social services, so this tool helped us to do that by eliminating all the households that were on that register. Without targeting this engagement activity, we would probably still be knocking on doors now!
  • Actual Performance 1235 residents includes those visited at home using customer insight, as well as other older people we contacted through open days and other events at the hospital and other locations
  • Our 40 volunteers came from all walks of life: retired city workers, single mums, students, unemployed people looking to gain extra skills. Many of the volunteers went on to volunteer for our partner agencies such as Age Concern and CAB after the project finished, and we are still in touch with those who have said they would like to volunteer for the council again.
  • Even though we’ve achieved a lot so far, we are really at the beginning of our customer insight journey, and have a whole programme of work underway around targeting services more efficiently: Energy Efficiency grants such as Warm Zones – after targeting 500 households who met the criteria, instead of universal advertising of the grants in the Council’s Living magazine, which also resulted in a lot of disappointed people when they responded to the advert only to find out they were not eligible, in one month we managed to get an extra 25% more people taking up the offer of energy repairs than last year by targeting only those homes who our segmentation tool told us were eligible. This equated to 70 new boilers (amongst other energy efficiency measures) – at a cost of £3000 per boiler, this amounted to £210,000 savings for people at risk of fuel poverty in Havering Top 100 families – currently profiling the top 500 families identified to help build a profile of the average complex family, which will then inform our strategy for earlier identification of families before they reach crisis stage DD campaigns planned, to shift residents who are able to pay by DD, away from high cost payment methods such as face-to-face Increasing the number of foster carers – we are currently profiling our current foster carers to help us target our next marketing campaigns to recruit more foster carers We currently have very ambitious targets to increase telecare and telehealth take-up to help people with long-term conditions live in their homes independently and safety, for longer. We are using customer insight to target people who may benefit form this service, as part of our overall prevention strategy to keep people out of hospital. Embedding into CRM system – so that every customer record is linked to a segment. When they contact the council, customer service advisors will see prompts on their screen, generated by the segment the customer is in, to ask them about related services or ways they would like to be contacted by the council. We think that this is where the big savings could potentially be released, as well as going a long way to improve customer satisfaction with the council.
  • Any Questions
  • Embedding customer insight into the corporate culture Cheryl Coppell, London Borough of Havering

    1. 1. Embedding Customer Insight into the Corporate Culture Cheryl Coppell Chief Executive London Borough of Havering
    2. 2. Where is Havering?• Situated in Outer North East London, Havering is the third largest London borough by area at 112 square kilometres (43 square miles)• The Borough is well connected, with good rail and road links to central London, Stansted airport, the M25 and ports in Essex and Kent• Havering’s principal town centre is Romford, followed by the smaller town centres of Hornchurch, Upminster and Rainham
    3. 3. Havering’s Population• Total population of 236,100• 5.38% above 80 (compared to 3.39% for London)
    4. 4. Population Projections • Population +11.5% by 2021, faster than London average • This will be due to population growth and positive net migration • Increased numbers of health conditions affecting older people • Cancer • CVD • Respiratory illness • Dementia • Osteoporosis (& falls fractures) • Pressures on related services
    5. 5. Deprivation Ward No. of LSOAs IMD Average RankGooshays 9 34.14 1Heaton 8 31.91 2South Hornchurch 8 22.30 3Havering Park 8 21.85 4Brooklands 9 19.72 5Romford Town 9 18.15 6Harold Wood 8 17.36 7Rainham and Wennington 8 16.95 8Mawneys 8 16.57 9Elm Park 8 16.54 10St Andrews 9 12.94 11Hylands 8 11.29 12Pettits 9 11.10 13Squirrels Heath 8 10.84 14Hacton 8 10.32 15Emerson Park 8 9.89 16Cranham 8 7.08 17Upminster 8 5.97 18
    6. 6. Havering’s HealthAreas for Improvement • Early help for vulnerable people in the community • Dementia – improved identification and support • Early detection of cancer • Tackling obesity – 27% of Adults • More integrated care for ‘frail elderly’ • Focusing on our ‘Top 100 families’ • Reducing avoidable hospital admissions
    7. 7. Challenges facing the Council• Significant budget savings: £40m by 2014• Very low grant base = high council tax• Already very low unit costs of services• Ageing population – disproportionate strain on social care• Some bureaucratic processes• How do we deliver services more efficiently whilst protecting those that really matter to local people?
    8. 8. The Havering 2014 programme • Transformation programme will enable us to meet new financial and service challenges whilst supporting culture change • Need to bridge a funding gap of £40 million over four years • Comprises eight separate work programmes
    9. 9. Our Transformation Objectives• 3 ‘change’ principles – To be efficient, focussed and fair• The sort of council we want to be is – A council that works smarter – A council that works with others – A council that prioritises effectively• Moving away from universal, prescribed services towards personalised services targeted at people who really need them• Allowing customers to have more choice• Need to have the insight that allows us to target customers more effectively
    10. 10. Using Customer Insight to target services• We have been developing a tool to target residents based on their characteristics and preferences• We first purchased Mosaic from Experian in 2006 – a generic customer profiling tool based on “general” characteristics• It made Havering look like a tale of two cities – not precise enough• In 2011, a new bespoke segmentation tool was built using our own customer data sets form across the council and PCT as well as new Mosaic data• 12 different segments, specific to our population• Allows us to identify at a household level the communication preferences of our residents and which services they do and don’t use• This enables us to target the right services at the right people in the right way
    11. 11. The Over 65s Volunteer Consultation Project
    12. 12. Aims of the Project• Aims and purpose of the project evolved as the project progressed!• Consult with vulnerable older people on council services, to encourage take-up and take feedback on services, specifically: • Older residents that are most in need of support or direct services, and • Older residents who may be unaware of the full range of services they are eligible to use.• Using Customer Insight, target consultation more effectively• Increase customer satisfaction with Council• Developed into an early intervention model, using an army of local volunteers
    13. 13. Targeting Specific Older People• We used our customer segmentation tool to target older people based on the following indicators: – Low Income Pensioners – Reliance on State Pension – Not currently on social care register – Low Household Incomes (<£13,499) – Rented Homes AND home ownership (asset rich cash poor) – Low Savings• It showed us that these people prefer face to face contact → we designed a household visit engagement model
    14. 14. Using Customer Insight to Target Consultation• This identified 5000 residents over 65• Identified a sample of their addresses• Plotted them on a map• Contacted residents to arrange household visits• This meant we would be able to target specific households that were definitely within our target audience
    15. 15. Project DeliverablesOriginal Targets: • 500 older people contacted or visited • 150 referred to Council and Partner services • Increased satisfaction of older people with council services since last year • Reduced avoidable contact by older people contacting the councilActual Performance: • 1235 residents contacted and 564 visited in their own homes • 2824 requests for services or more information
    16. 16. Outcomes• Early Intervention Successes: • CAB advised a resident living in hardship who is now £120pw better off • Referrals to NHS Community services for dental implants • A number of older people were assessed for social care support through Havering Direct • Huge increase in aids and adaptations take-up • Garden clean-ups • Housing improvements identified • £64,806 in unclaimed benefits identified
    17. 17. Other outcomes• Increased skills of the volunteers• Face to face service highly effective and well received by customers - 98% satisfaction• Cost savings of using volunteers (1152 hours = approx £14,400)• Key issues: social isolation, lack of awareness of support• We are now developing a volunteering network based on this model ‘Activate Havering’ to tackle social exclusion and loneliness
    18. 18. A corporate programme of using customer insight to target services• Targeting Energy efficiency grants – 25% more take- up than universal advertising approach• Top 100 families profiling• Direct Debits and channel shift• Fostering campaigns• Increasing Telecare take-up• Embedding into CRM system to proactively refer people to services when people call the council• Free school meals• Encouraging recycling
    19. 19. Any Questions

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