Managing a fluid nation:
Better quality data in the public sector
Andrew Mulholland
Public Sector Marketing Manager
QAS
Data decay in the ‘fluid nation’
Every day there are:
18,000 movers
1,600 deaths
820 marriages
410 divorces
Who is affected by poor data quality?
Data quality problems pervasive
The consequences of inaccurate data
Customer interactions
Front-line morale
Wasted money
Sensitive information going astray
Fraud
Negative publicity
IT project risk
Background
Commitment to data quality
NOP World research
QAS / Kable public sector research
Who participated?
350 respondents from across the UK
Contributors by sector
Aspiration and reality: a critical gap
How is data quality perceived?
Aspiration and reality: a critical gap
Do you have a data quality strategy in place?
10
20
30
40
50
The data quality strategy
So why is a data strategy so important?
It’s a strategic issue
It can impact new IT initiatives
Data’s all about people
Data strategy ownership by function
Who owns data strategy?
‘Business’ not technology issue
Strategy must come from the top
A case in point…
“Clean data – that is my biggest, biggest, biggest, biggest
challenge. If I could get the data clean in our
organisations so that many millions of people have not got
multiple entries, we can do much less reworking.
Reworking is a real killer.”*
Steve Lamey, CIO, HMRCs
*
31st May, 2005
Confidence in data quality
How accurate is your data?
Don’t know
90%
70-89%
50-69%
<50%
How often is your data cleaned?
Over 50% rarely clean their data, or don’t know how often,
if at all, it is cleaned.
What is an effective data quality strategy?
Data sharing can be problematic
Avoid ‘boom and bust’
The benefits of accurate data
The principal barriers to data accuracy
Key data accuracy challenges
Considerations for data migration
How to improve citizen data?
Implementation of data quality solution (30%)
Improved IT infrastructure (18%)
Introduction of a data quality strategy (17%)
Dedicated staff (14%)
New CRM system (10%)
Greater investment (8%)
The most important data
Summary and Conclusions
Progress is being made!
Data deteriorates rapidly through time
Data strategy has to come from the top
Must be owned by the organisation
Regular data cleansing
Significant cost savings
Address data improves service delivery