Data Quality:

Success Generator or Failure Preventer?

Presented by: Jos Schijns (OUNL)

Co-author: Luc Schrover (Cendris)

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

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IntroductionThe circle of quality (Jim Harris)

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Source: http://www.ocdqblog.com/home/the-circle-of-quality.html

An organization’ssuccess is measured by the quality of itsresults…

…which are dependenton the quality of itsbusiness decisions ,,,

… which rely onthe quality of itsinformation …

…which is based onthe quality of its data!

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!

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Problem Statement

• Why are companies willing to invest in data quality and data maintenance of their customer data(base)?

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Literature Review5 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

address2. 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 rates3. Image and positioning

• If the data is wrong, reputation can be lost• E.g.: damage caused by letters to deceased persons or incorrectly written

addresses4. Preventing customer irritation and dissatisfaction

• E.g.: as a result of duplicates and incorrect courtesy titles5. Meeting regulation and legislation

• To avoid penalties and fines

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Research Questions

• Which of these are (most) important to firms?

• Do they change over time?– Historically: failure preventer– Now (also): success generator?

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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

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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)

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Findings (2)

• Companies do have more than one business driver to assure customer data quality in the firm

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82,464,4 59,2 54,3

7,85,86,34,20102030405060708090

100

Customerfocus

Failurepreventer

Successgenerator

Regulation

%

Low (1-3) High (5-7)

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

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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)

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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

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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

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For further information

Jos SchijnsOpen Universiteit in the NetherlandsSchool of ManagementNL-PO Box 29606401 DL HeerlenThe NetherlandsE: jos.schijns@ou.nl

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“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)

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