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

2. Agenda Two views Why is research valuable? Global research Public Sector specific Common themes ValueOwnership InvestmentData 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 * 31 st 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 Sector Specific Research

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

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 “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” Customer interactions Front-line morale Wasted money Sensitive information astray Fraud

29. Thank you for listening Any Questions?