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Product data quality in supply chains: the case of Beiersdorf

Author

Listed:
  • Kai M. Hüner

    (Institute of Information Management)

  • Andreas Schierning

    (Beiersdorf AG, Supply Chain Data Process Management)

  • Boris Otto

    (Institute of Information Management)

  • Hubert Österle

    (Institute of Information Management)

Abstract
A number of business requirements (e.g. compliance with regulatory and legal provisions, diffusion of global standards, supply chain integration) are forcing consumer goods manufacturers to increase their efforts to provide product data (e.g. product identifiers, dimensions) at business-to-business interfaces timely and accurately. The quality of such data is a critical success factor for efficient and effective cross-company collaboration. If compliance relevant data (e.g. dangerous goods indicators) is missing or false, consumer goods manufacturers risk being fined and see their company’s image damaged. Or if logistics data (e.g. product dimensions, gross weight) is inaccurate or provided not in time, business with key account trading partners is endangered. To be able to manage the risk of business critical data defects, companies must be able to a) identify such data defects, and b) specify and use metrics that allow to monitor the data’s quality. As scientific research on both these issues has come up with only few results so far, this case study explores the process of identifying business critical product data defects at German consumer goods manufacturing company Beiersdorf AG. Despite advanced data quality management structures such defects still occur and can result in complaints, service level impairment and avoidable costs. The case study analyzes product data use and maintenance in Beiersdorf’s ecosystem, identifies typical product data defects, and proposes a set of data quality metrics for monitoring those defects.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:elmark:v:21:y:2011:i:2:d:10.1007_s12525-011-0059-x
    DOI: 10.1007/s12525-011-0059-x
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    References listed on IDEAS

    as
    1. Andreas I. Nicolaou & D. Harrison McKnight, 2006. "Perceived Information Quality in Data Exchanges: Effects on Risk, Trust, and Intention to Use," Information Systems Research, INFORMS, vol. 17(4), pages 332-351, December.
    2. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    3. Susan Cohen Kulp & Hau L. Lee & Elie Ofek, 2004. "Manufacturer Benefits from Information Integration with Retail Customers," Management Science, INFORMS, vol. 50(4), pages 431-444, April.
    4. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    5. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
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    Cited by:

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    3. 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.
    4. Duvier, Caroline & Neagu, Daniel & Oltean-Dumbrava, Crina & Dickens, Dave, 2018. "Data quality challenges in the UK social housing sector," International Journal of Information Management, Elsevier, vol. 38(1), pages 196-200.

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