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Andrew Mulholland Public Sector Marketing Manager QAS Managing a fluid nation: Better quality data in the public sector.

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Presentation on theme: "Andrew Mulholland Public Sector Marketing Manager QAS Managing a fluid nation: Better quality data in the public sector."— Presentation transcript:

1 Andrew Mulholland Public Sector Marketing Manager QAS Managing a fluid nation: Better quality data in the public sector

2 Data decay in the ‘fluid nation’ Every day there are: 18,000 movers 1,600 deaths 820 marriages 410 divorces

3 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

4 Background Commitment to data quality NOP World research QAS / Kable public sector research

5 Who participated? Contributors by sector 350 respondents from across the UK

6 Aspiration and reality: a critical gap How is data quality perceived?

7 Aspiration and reality: a critical gap Do you have a data quality strategy in place?

8 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

9 Data strategy ownership by function Who owns data strategy? ‘Business’ not technology issue Strategy must come from the top

10 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 * 31 st May, 2005

11 Confidence in data quality How accurate is your data? Don’t know 90% 70-89% 50-69% <50%

12 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’

13 The benefits of accurate data

14 The principal barriers to data accuracy Key data accuracy challenges Considerations for data migration

15 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%)

16 The most important data

17 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


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