B5: Maximising the value of your Customer...

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 &

Twitter

• 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