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On the relevance of reports—Integrating an automated archiving component into a business intelligence system

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  • Schulz, Michael
  • Winter, Patrick
  • Choi, Sang-Kyu Thomas

Abstract

In the last years, the scope of business intelligence (BI) systems has been extended from strategic to operational decision support (operational BI). This has led to an increase in the number of information needs and, at the same time, to a decrease in the “efficiency” of reports in terms of how many information needs they address. As a consequence, the number of reports has exploded. This slows down knowledge workers’ manual or automated search for information, resulting in high search costs to companies. However, it can be observed that in many cases only a small subset of all reports is (still) relevant to knowledge workers. The remainder is an unnecessary burden that could be sorted out without obstructing the access to information that still is needed. In this paper, we develop a framework to identify such reports and archive them automatically. The relevance of reports is concluded from users’ information retrieval behavior as recorded in the log files of the BI system, particularly of its search component. We evaluate the proposed framework through a simulation study. The results indicate that the integration of an automated archiving component into a BI system can significantly reduce search effort and, hence, search costs.

Suggested Citation

  • Schulz, Michael & Winter, Patrick & Choi, Sang-Kyu Thomas, 2015. "On the relevance of reports—Integrating an automated archiving component into a business intelligence system," International Journal of Information Management, Elsevier, vol. 35(6), pages 662-671.
  • Handle: RePEc:eee:ininma:v:35:y:2015:i:6:p:662-671
    DOI: 10.1016/j.ijinfomgt.2015.07.005
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    References listed on IDEAS

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    1. Barbara Wixom & Hugh Watson, 2010. "The BI-Based Organization," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 1(1), pages 13-28, January.
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    Cited by:

    1. Jens Passlick & Lukas Grützner & Michael Schulz & Michael H. Breitner, 2023. "Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation," Information Systems and e-Business Management, Springer, vol. 21(1), pages 159-191, March.

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