Business drivers for data quality and data maintenance services

1. Data Quality:
Success Generator or Failure Preventer?
Presented by: Jos Schijns (OUNL)
Co-author: Luc Schrover (Cendris)

2. Introduction
• Marketing today has become data
(based) driven
– Data used for decision making
• So, you should be sure that your data is of
high quality
• However, data quality is not a ‘hot’ item
• Besides, data quality seems to suffer from
cost savings / budget restrictions in times
of recession
• Because (top) management often can’t
see the poor quality of their data
Pagina 2

3. Introduction
The circle of quality (Jim Harris)
Pagina 3
Source: http://www.ocdqblog.com/home/the-circle-of-quality.html
An organization’s
success is
measured by the
quality of its
results…
…which are dependent
on the quality of its
business decisions ,,,
… which rely on
the quality of its
information …
…which is based on
the quality of its data!

4. Introduction
• So, data quality matters because high
quality data serves as a solid foundation
for business success
– Circle of quality
• Data suppliers have to remind them!
Pagina 4

5. Problem Statement
• Why are companies willing to invest in
data quality and data maintenance of
their customer data(base)?
Pagina 5

6. Literature Review
5 categories of business drivers
1. Failure preventer
• Avoid inefficiencies in business processes and the very expensive rework efforts to
“fix” the failures made
• E.g.: costs/expenses caused by delivery failures and returns through changes of
address
2. Success generator
• Critical decisions based on poor-quality data can have serious consequences
• E.g.: determine sales potentials, develop new markets or products, improve
conversion rates
3. Image and positioning
• If the data is wrong, reputation can be lost
• E.g.: damage caused by letters to deceased persons or incorrectly written
addresses
4. Preventing customer irritation and dissatisfaction
• E.g.: as a result of duplicates and incorrect courtesy titles
5. Meeting regulation and legislation
• To avoid penalties and fines
Pagina 6

7. Research Questions
• Which of these are (most) important to
firms?
• Do they change over time?
– Historically: failure preventer
– Now (also): success generator?
Pagina 7

8. Research Method
• Webbased survey application (“CendrisMonitor”)
– Reached by a link within the e-mail invitation
• Pre-test with 132 executives in B2B industry in
the Netherlands
Pagina 8

9. Findings (1)
• From 5 theoretically based to 4 research based
categories
– Failure preventer
– Success generator
– Legislation and regulation
– Customer focus/related (image and positioning;
customer irritation and dissatisfaction)
Pagina 9

10. Findings (2)
• Companies do have more than one business
driver to assure customer data quality in the firm
Pagina 10
82,4
64,4 59,2 54,3
7,85,86,34,20
10
20
30
40
50
60
70
80
90
100
Customer
focus
Failure
preventer
Success
generator
Regulation
%
Low (1-3) High (5-7)

11. Findings (3)
• Relations suggested, that need further support
– (number of records X business drivers)
• (Large) companies, managing large databases are
more likely to invest in DQ from a success generator
point of view
– (type of industry X business driver)
• Utilities and telco’s are more likely to be advocates
of the success generator point of view
Pagina 11

12. What we didn’t find (suggestions for further research)
• Besides the two relations suggested before that
need further support
• Business driver X (unit/dept./person responsible
for DQ)
– Different people look at data differently
– E.g. a marketing manager versus an IT
manager
• Business driver X (#years of experience in
database marketing)
Pagina 12

13. Follow-up research
• Work in progress, a pre-test …
• … that needs follow-up research:
– Test hypothesis in a cross-section survey
– Explore changes in time
– Compare across countries
Pagina 13

14. Conclusions
• Businesses are only as good as their data
– Circle of quality
• More than one business driver for DQ
– But they are not equally important
• A number of relationships that have to be
investigated further
• Based on the research results, data suppliers
and data maintenance service suppliers can
help improve their customers’ performance
Pagina 14

15. For further information
Jos Schijns
Open Universiteit in the Netherlands
School of Management
NL-PO Box 2960
6401 DL Heerlen
The Netherlands
E: jos.schijns@ou.nl
Pagina 15

16. “When data is abundant, but data quality
remains scarce, then the thirst to acquire
knowledge and insight remains
unquenched, and data hangs like a heavy
albatross around the enterprise’s neck”
– Jim Harris (2010)
Pagina 16