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Managing a Fluid Nation: Improving Public Sector Data Quality

Explore the impact of poor data quality in a dynamic society, with insights on strategy, ownership, barriers, and benefits of maintaining accurate data in the public sector. Learn how data quality initiatives can lead to better service delivery and cost savings.

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Managing a Fluid Nation: Improving Public Sector Data Quality

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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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