Presented by: Charles King Date:15 th March 2006

1. QAS data quality research Presented by: Charles King Date:15th March 2006

2. Agenda • Two views • Why is research valuable? • Global research • Public Sector specific • Common themes Value Ownership Investment Data Strategy Responsibility

3. Two views “Lies, damn lies and statistics.” Mark Twain “98% of statistics are made up on the spot.” Anonymous

4. Why have we done the research? • Every day there are: • 18,000 movers • 1,600 deaths • 820 marriages • 410 divorces • 50,000 telephone number changes • Data is dynamic • Understanding and responsibilities • Marketplace • Education

5. Methodology In June 2005, 550 private and public organisations from across the globe were surveyed in order to establish the integrity of their customer data. The respondents were a mixture of CEO’s MD’s and senior managers.

6. Is it important? • All industry types rate enhanced customer satisfaction as one of their top 3 drivers to improve data accuracy • July 2005 white paper figure 3 *Dynamic Markets research 2005

7. Cost of poor data • 75% admit poor data quality leads to lost revenue through missed opportunities. • 73% believe inaccurate data costs them money on wasted resources, lost productivity, wasted marketing spend, reworking, etc. • On average 6% of revenue is perceived to be lost through incomplete or inaccurate data. • Impacts the efficiency and costs of your business. • Financial issue. *Dynamic Markets research 2005

8. 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

9. Barriers to maintaining accurate databases • Key data accuracy challenges • Figure 4 July 2005 white paper

10. Clear strategy • Only 34% have a Board member who takes ownership of the data • Only 19% say it has been discussed in the last 3 years • Communicate • 27% have an organisation wide documented strategy *Dynamic Markets research 2005

11. The data quality strategy • So why is a strategy so important? • “If you do not have a focussed data quality strategy in place, you have to assume that you have a data quality problem” • It’s a strategic issue • It can impact new IT initiatives • It’s all about people

12. Public SectorSpecific Research

13. Who participated? • 350 respondents from across the UK Contributors by sector

14. How is data perceived • 99% of respondents view it as a key organisational asset • 15% strongly agree, 43% agree

15. Data strategy ownership by function • Who owns data strategy? • IT responsible for but do not have ownership • Low strategic prioritisation • Strategy must come from the top

16. Confidence in data quality • How accurate is your data? • High degree of confidence Don’t know 90% 70-89% 50-69% <50%

17. How often is your data cleaned? • Over 50% rarely clean their data, or don’t know how often, if at all, it is cleaned. • Data decay • Data sharing can be problematic • Avoid ‘boom and bust’

18. The benefits of accurate data • Benefits clearly recognised

19. Legacy systems / Budget allocation • 51% of organisations are planning to invest in better data management practices in the next 12 months. *Dynamic Markets research 2005

20. Outdated Data Quality Systems • Only 62% of organisations have a database manager or alternative that looks after data quality. • 79% said 3 or more people have responsibility in the organisation. *Dynamic Markets research 2005

21. Lack of best practice/ Strategic prioritisation • Ownership of data • Head of IT / IT Managers 60% • Primary users • Are they best placed to maximise data? • Can they get the buy in to a data quality strategy? • Organisational asset • Visibility

22. The principal barriers to data accuracy • Key data accuracy challenges • Considerations for data migration

23. The most important data

24. What 3 things would you most like to improve? • Inaccuracies • Duplicates • Ability to share information

25. How is the Public Sector different? • More public sector organisations than any other industry sector (36%) said they have an organisation-wide data strategy in place. (Finance - 24%, Telecoms - 18%, Utilities - 21%, Retail –27%) • More public sector organisations (62%) have a dedicated database manager than any commercial sector (which averaged 42%)

26. How is the Public Sector different? • More Public Sector organisations (27%) have a single champion for data quality (compared to 18% in Finance and Telecoms,15% in Retail, and 21% in Utilities • Fewer Public Sector organisations (25%) are planning on investing in data management over the next 12 months compared to those in all other sectors – 59-64%

27. Research summary • Progress is being made! • Data deteriorates rapidly through time • The value of data is being recognised • A data quality strategy must be Owned Recognised Communicated Supported Continuous Consistent • Data quality directly impacts service delivery and the bottom line

28. Consequences… • Negative publicity • IT project risk • Customer interactions • Front-line morale • Wasted money • Sensitive information astray • Fraud “30 million tax letters a year go astray” “Between now and 2007, over half of all […] CRM implementations will fail due to a lack of attention to data quality issues”

29. Thank you for listening Any Questions?