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Andrew Mulholland Public Sector Marketing Manager QAS

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?.

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Andrew Mulholland Public Sector Marketing Manager QAS

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

  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? • 350 respondents from across the UK Contributors by sector

  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? 10 20 40 50 30

  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 * 31st 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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