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The data quality improvement plan: deciding on choice and sequence of data quality improvements

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  • Dominikus Kleindienst

    (Universitätsstraße 12)

Abstract

With the rapid growth in the amount of data generated worldwide, ensuring adequate data quality (DQ) is increasingly becoming a challenge for companies: data are, among others, required to be timely, complete, consistent, valid, and accessible. Given this multidimensionality, DQ improvements (DQIs) need to be purposefully chosen and –as there can be path dependencies– arranged in an optimal sequence. Thus, this research contributes to performing the complex multidimensional task of ensuring adequate DQ in an economically reasonable manner by providing a formal decision model for identifying an optimal data quality improvement plan (DQIP). This DQIP comprises both an economically reasonable selection and execution sequence of DQIs based on existing interrelationships between different DQ dimensions. Furthermore, a comprehensive Monte Carlo simulation provides insights in implications to put the decision model into operation. For practitioners, the decision model enables efficient allocation of resources to DQIs. The model also gives advice on how to sequence DQIs and attracts attention to the complex problem context of DQ in order to support valid managerial decisions.

Suggested Citation

  • Dominikus Kleindienst, 2017. "The data quality improvement plan: deciding on choice and sequence of data quality improvements," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(4), pages 387-398, November.
    • Handle: RePEc:spr:elmark:v:27:y:2017:i:4:d:10.1007_s12525-017-0245-6
    DOI: 10.1007/s12525-017-0245-6
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    References listed on IDEAS

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    1. Olaf Radant & Ricardo Colomo-Palacios & Vladimir Stantchev, 2014. "Analysis of Reasons, Implications and Consequences of Demographic Change for IT Departments in Times of Scarcity of Talent: A Systematic Review," International Journal of Knowledge Management (IJKM), IGI Global, vol. 10(4), pages 1-15, October.
    2. Kai M. Hüner & Andreas Schierning & Boris Otto & Hubert Österle, 2011. "Product data quality in supply chains: the case of Beiersdorf," Electronic Markets, Springer;IIM University of St. Gallen, vol. 21(2), pages 141-154, June.
    3. Zhengrui Jiang & Sumit Sarkar & Prabuddha De & Debabrata Dey, 2007. "A Framework for Reconciling Attribute Values from Multiple Data Sources," Management Science, INFORMS, vol. 53(12), pages 1946-1963, December.
    4. Craig W. Fisher & InduShobha Chengalur-Smith & Donald P. Ballou, 2003. "The Impact of Experience and Time on the Use of Data Quality Information in Decision Making," Information Systems Research, INFORMS, vol. 14(2), pages 170-188, June.
    5. Donald Ballou & Richard Wang & Harold Pazer & Giri Kumar Tayi, 1998. "Modeling Information Manufacturing Systems to Determine Information Product Quality," Management Science, INFORMS, vol. 44(4), pages 462-484, April.
    6. Amir Parssian & Sumit Sarkar & Varghese S. Jacob, 2004. "Assessing Data Quality for Information Products: Impact of Selection, Projection, and Cartesian Product," Management Science, INFORMS, vol. 50(7), pages 967-982, July.
    7. Olaf Radant, 2014. "Demographic Change: The Reasons, Implications and Consequences for IT Departments," International Journal of Human Capital and Information Technology Professionals (IJHCITP), IGI Global, vol. 5(1), pages 41-54, January.
    8. Donald P. Ballou & Harold L. Pazer, 1995. "Designing Information Systems to Optimize the Accuracy-Timeliness Tradeoff," Information Systems Research, INFORMS, vol. 6(1), pages 51-72, March.
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    Cited by:

    1. Rainer Alt, 2021. "Electronic Markets on digital platforms and AI," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 233-241, June.
    2. Rainer Alt, 2017. "Electronic markets on transaction costs," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(4), pages 297-301, November.

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