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B5: Maximising the value of your
Customer information
Speakers: Jason Wilkes Customer Information Manager WM Housing Group
Tony Sanderson
Corporate Planning and Performance Manager First Wessex
Jason Wilkes
WM Housing Group
Maximising the Value of
Customer Information
• Based in the West Midlands
• 4 Associations make up the Group
• 27,000+ Properties
• Covering Hereford, Worcester,
Birmingham, Coventry & surrounding areas
Good Customer Knowledge
Good businesses know their customers.
Information helps
identify trends amongst different
groups of people and helps us to develop
services that respond to specific needs.
Good Customer Knowledge
We also have legal duties to make sure
that all of our services are accessible to
everybody. Without information we can’t demonstrate if this is
the case or not.
Customer Information
• The journey so far &
the challenges
• Making information
COUNT
• GIS is not just for
properties
Customer Information
• Customer information and
welfare reform
• Collecting customer data in
a digital world
• The role of #datanerds
in housing
The Journey So Far
The Sectors Journey So Far
• Housing Associations have
been late to the party to
collect customer information
• Many providers have
collected only 1st Person
Information historically
• Early focus on Audit
Commission
six strands (Age Gender Ethnicity
Sexuality Faith Disability)
Challenges of collecting
• We see 10% of our
Customers 90% of
the time
• Data Protection
nervousness from
customers and staff
• The WHY do you
want to know that?
Stonewall Publication
The Challenge
Turning Customer Information
into useful Customer Insight
The Tesco Comparison
WM’s Customer Insight
We recognise that a key element in improving services for our customers is information
that tells us :
– The demographic profile of our customers
– Which services customers use
– How and when they access them
– How frequently they use them
– Why they use them
– How satisfied customers are with the services they use
– How much our services cost to provide
How to
Make Information
COUNT
COUNT
Collect
Once
Use
Numerous
Times
Making it COUNT
Information comes in to our organisations
from numerous sources
• Much of it is used only once.
• Individual surveys tell us at a point in time
information
• Not always recorded against a particular
customer or with a UPRN (Property Reference)
This information has extra value if we record who responds and how often they respond.
• Establish who is more likely to respond
• Predict how best to get a response from other customers using a variety of communication
methods.
We can then target the best method to the most appropriate groups of customers to get the best feedback in the most efficient time
and at least cost.
Making it COUNT
Collection
Collect relevant and reliable data by :
• Collecting full demographic profile information
for all customers, our aim is to achieve at
least 95% of all information.
• Carrying out regular audits of new customers
to ensure that profile information is being
collected at sign up
Collection
We collect information from :
• Customer Profile Forms
• Customer histories (Rent, ASB, Repairs)
• Compliments, comments & complaints
• Customer journey mapping
• Customer involvement
• STAR surveys (Survey of Tenants & Residents)
• Satisfaction surveys
Collecting Once
Make profile information available to
customers to check and validate by :
• Pre-populating customer surveys where possible
with demographic information
• Making information available on line, through a
secure customer portal and steering people
towards checking and maintaining information
themselves
Using the Information
Our customer insight is drawn from our
own records and databases but we also
supplement this with external information.
• Use segmentation from external sources
(Mosaic from Experian)
• Utilise freely available “opendata” from
government departments such as The Indices of
Multiple Deprivation
A – Isolated rural
B – Small & mid-sized towns
C – Wealthy people
D – Successful professionals
E – Middle income families
F – Couples with young children
G – Young city dwellers
H – Couples and young singles
I – Lower income workers
J – Ex-industrial estates
K – Sufficient incomes
L – Active elderly people
M – Elderly on state support
N – Young people in flats
O – Families in low rise
WMHG properties All households
nationally
Mosaic Profiles
Using the Information
Routinely publish anonymous summary
information and provide trend analysis to
Boards, SMT & service teams
• Annual Report to our boards on Equality and
Diversity Information
• Information packs & reports are available to all
staff on our intranet.
Using the Information
• Provide training and support to staff so
that they understand the information that is
presented to them
• Develop GIS (Graphic Information
Systems) to provide mapped analysis of
information and to identify hotspots.
Using the Information
The Challenge is to change the
culture of your organisation.
Ensure that the information is used and
moves from being interesting to useful.
Geographic Information Systems
(GIS) is not just for properties
GIS
• Its not just for Asset Management
• Available to all staff through our intranet
• We have used it to : -
– help target training to residents
– Show where pay points are for customers
– Measure the impact of Welfare Reform
WM Housing Local View
Proximity to Pay Points
GIS
• Links to external data resources
– Multiple Indices of Deprivation
– Open Data from Government
– Guardian Data Blog
• It will be one of the tools we use to
measure our impact in communities
• Lower Super Output Areas are the key
Indices Of Multiple Deprivation
Customer Information
and
Welfare Reform
• We have worked with Local Authorities to
identify those potential affected by Welfare
Reform
• We visited all of our customers affected by
under occupation
• We asked them if they wanted to move or
to stay and pay
Welfare Reform
% of each age group under-occupying
• 16 to 24 2.99%
• 25 to 34 14.45%
• 35 to 44 20.98%
• 45 to 54 36.92%
• 55 to 59 15.45%
Welfare Reform Age Groups % of those in arrears Arrears %
16 to 24 8.81% 7.12%
25 to 34 21.34% 6.96%
35 to 44 21.82% 6.39%
45 to 54 19.74% 5.72%
55 to 59 6.66% 4.62%
60 to 64 5.42% 3.36%
65 to 74 7.68% 2.56%
75 plus 4.90% 1.91%
Date of birth unrecorded 3.63% 4.04%
Group Average 5.25%
WM Housing Group average arrears
by Mosaic group
A – Isolated rural
B – Small & mid-sized towns
C – Wealthy people
D – Successful professionals
E – Middle income families
F – Couples with young children
G – Young city dwellers
H – Couples and young singles
I – Lower income workers
J – Ex-industrial estates
K – Sufficient incomes
L – Active elderly people
M – Elderly on state support
N – Young people in flats
O – Families in low rise
WM Housing Group arrears by
ethnicity
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
BME Non BME Refused Unknown
Welfare Reform
Welfare Reform
• All customers subject to the benefit cap have
been treated as vulnerable but broken down to
see if we needed to target any particular group
• We have updated our profile collection
information due directly to welfare reform to
include access to banking & digital inclusion
information
Welfare Reform
• Rent arrears – all demographic information
taken into account when deciding on the
progress of arrears actions
• All new customers have a ‘risk assessment’
which assess their level of need and allows us to
target the specific support that they need
Welfare Reform
• We have branded our communications around
Welfare Reform
• We have targeted information to customers in a
variety of formats
Welfare Reform
Welfare Reform
Information on WM Housing YouTube Channel
@wmjasonw #J2ex
Our Journey to Excellence Project
• We have been reengineering our business
processes and we are changing the way
we deliver our services for the future
• CRM will help us to achieve it easier
• Our systems aren’t necessarily geared up
to enable easy collection of information
Our Vision is
• 24/7 self service
• Single contact number
• Perfect customer knowledge
• 80%resoulution at point of contact
• Consistency of service with greater mobility
• More efficient services
• High % right first time
• Excellence in our customers areas of priority
Collecting customer data in a
digital world
• We are making use of online secure portal
• We email a newsletter to customers
• We make use of Facebook pages &
• We have a WM Housing App for
customers to report repairs, ASB and to
contact us
Collecting customer data in a
digital world We will monitor all those services to see who is
using them.
– The demographic profile of our customers
– Which services customers use
– How and when they access them
– How frequently they use them
– Why they use them
– How satisfied customers are with the services they
use
– How much our services cost to provide
What to do next ?
• There isn’t a one size fits all solution
• Identify why you are doing it
• Find what works for you
• The challenge is to stay one step ahead of
the technology curve and the business
The role of #datanerds
in housing
“With great power comes great
responsibility”
http://prezi.com/9r-klclkf9fi/?utm_campaign=share&utm_medium=copy&rc=ex0share
http://www.theguardian.com/housing-network/2013/mar/08/housing-management-tenants
Housing Data Analysis Best Practice Group
NHF IT HOUSING
CONFERENCE 19 November 2013
Maximising the value of
customer information
Presented by:
Tony Sanderson Corporate Planning &
Performance Manager
Agenda
• Background & ethos
• Data & value for money
• Geographic Information Systems (GIS)
• Challenges for customer information & welfare
reform
• Background & ethos
• Data & value for money
• Geographic Information Systems (GIS)
• Challenges for customer information & welfare
reform
About First Wessex
Concentrated in 11 core local
authority areas in the counties
of Hampshire and Surrey
March 2013
First Wessex ‘Ethos’
Keep
Promise
s
Reduce
custome
r effort
Attentive
service
Simple
processe
s
• Background & ethos
• Data & value for money
• Geographic Information Systems (GIS)
• Challenges for customer information & welfare
reform
• Public spending restricted
• Private finance –
expensive, short term,
uncertain
• Welfare Reforms
impacting on revenue
streams
• Increased demand for
sub-market priced housing
Drivers of Value for
Money
Q: How does
information
management
contribute?
=
Data
Vision & Strategy
Delivering the Strategy: ‘Removing Data Silos’
Datawarehouse
Performance Management System (AspireView)
GIS - Geographical Information System (ESRI
& GeoSamba)
Simple to access, easy to view
Inputs: Performance Indicators, Property, Person, Tenancy, Benchmarks, Risks, Complaints, Customer Satisfaction, External Data Sources e.g. Indices of
Deprivation
Extracting value from
data
Performance Systems (Top Down – Aggregated Data)
Key corporate
dashboards
• Background & ethos
• Data & value for money
• Geographic Information Systems (GIS)
• Challenges for customer information & welfare
reform
Mapping
First
Wessex
• Maps at any level of
geographic detail
• Benefits:
• Any dataset linked to
tenancy or property
• Efficiency of resource
allocation
• In depth analysis
Estates, Property Points
and Land Ownership
Procurement: Mapping
Suppliers
• Background & ethos
• Data & value for money
• Geographic Information Systems (GIS)
• Challenges for customer information &
welfare reform
Census Data Mapping: Indices of Deprivation
First Wessex:
Internal Census
Mapping Satisfaction
Arrears and Welfare
Cases
Arrears and Welfare
Cases Welfare Benefit
activities
reducing arrears
Arrears and Welfare
Cases - Mapping Positive Outcomes
GIS to Infographics
Turning the
‘complex’ into the
‘simple’
- Accessibility
- Immediate impact
- Story telling
GIS to
Infographics
Simple Data:
- Story telling
- Transparency
- Clarity of information
Business Intelligence
Challenges • Making Information COUNT
– Data controls
– Maintaining / updating customer data
• Flexible to meet changing demand
• The ‘right’ use of technology
• Resource skilling
– Availability of specialists
– Staff usage
• Key Principle:
• Keep it simple
• Delivered:
• Clear strategy
• Improved
intelligence &
analytics
• Self-service portal
• Work continues on:
• Data quality
(inputs / outputs)
• Information governance
Data Management: Summary
NHF IT Housing Conference 19 November 2013
Tony Sanderson Corporate Planning &
Performance Manager