Abstract
Master data is a main component of most information systems. In distributed and heterogeneous organizations, problems of data quality may arise if several Enterprise Resource Planning (ERP) systems, customized with respect to local business needs and objectives, use subsets of common master data. In this paper we describe data management issues in a large organization, running 10 instances of the SAP R/3 system. For coordinating purposes, com mon elements of materials master data are entered via a centralized application and subsequently distributed to the affected instances. However, this master data management approach did not avoid massive data quality problems, which are, for instance, hampering the computation of informative key performance values and the effective realization of inventory reduction programs. The paper discusses possible approaches for improving data quality in this situation and in other cases of distributed ERP systems.
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References
Angeli, A., Streit, U., Gonfalonieri, R.: The SAP R/3 Guide to EDI and Interfaces, 2nd edn. Vieweg, Braunschweig/Wiesbaden (2001)
Ballou, D.P., Pazer, H.L.: Modeling Data and Process Quality in Multi-Input, Multi-Output Information Systems. Management Science 31(2), 150–162 (1985)
Brackett, M.H.: Data Resource Quality. In: Turning Bad Habits into Good Practices. Addison-Wesley, Boston (2000)
Brodie, M.L.: Data Quality in Information Systems. Information and Management 3(6), 245–258 (1980)
Broeckelmann, R.G.: Inventory Classification Innovation. St. Lucie Press/APICS, Boca Raton/Falls Church (1999)
CFO Research Services/Deloitte Consulting: IQ Matters: Senior Finance and IT Executives Seek to Boost Information Quality. CFO Publishing, Boston (2005), http://www.deloitte.com/dtt/cda/doc/content/Final%20Deliverable_IQ%20Matters.pdf
Davenport, T.H.: Putting the Enterprise into the Enterprise System. Harvard Business Review 76(4), 21–131 (1998)
Druker, D., Rich, R.: Master Data Management. DB2 Magazine 10(3), 33–36 (2005)
English, L.P.: Improving Data Warehouse and Business Information Quality. Wiley, New York (1999)
Galway, L.A., Hanks, C.H.: Data Quality Problems in Army Logistics: Classification, Examples, and Solutions. RAND, Santa Monica (1996)
Gattiker, T.F., Goodhue, D.L.: Understanding the local-level costs and benefits of ERP through organizational information processing theory. Information & Management 41(4), 431–443 (2004)
Griffin, J.: Overcoming Challenges to Master Data Management Implementation. DM Review Magazine (April 2006), http://www.dmreview.com/portals/portalarticle.cfm?articleId=1051113&topicId=1031394
Hayler, A.: Are You Master of Your Data or Its Slave? DM Direct Newsletter, March 4 (2005), http://www.dmreview.com/article_sub.cfm?articleID=1020858
Khanduja, D.: Master Data Management: Three Approaches to Consolidating Master Data. DM Direct Newsletter (October 14, 2005), http://www.dmreview.com/portals/portalarticle.cfm?articleId=1038907&topicId=1031394
Kirsche, T., Baumann, G., Schanzenberger, A.: Alignment of Product Master Data. In: Cremers, et al. (eds.) INFORMATIK 2005: Informatik LIVE! Proceedings of the 35th Annual Conference of the Gesellschaft für Informatik, Bonn, vol. 2, pp. 449–453 (2005)
Klaus, H., Rosemann, M., Gable, G.G.: What is ERP? Information Systems Frontiers 2(2), 141–162 (2000)
Kremers, M., van Dissel, H.: ERP System Migrations. Comm. ACM 43(4), 53–56 (2000)
Loshin, D.: Enterprise Knowledge Management – The Data Quality Approach. Morgan Kaufmann, San Diego (2001)
McKnight, W.: Justifying and Implementing Master Data Management. DM Review Magazine (April 2006), http://www.dmreview.com/article_sub.cfm?articleID=1051165
Olson, J.E.: Data Quality – The Accuracy Dimension. Elsevier, Amsterdam (2003)
Piasecki, D.J.: Inventory Accuracy: People, Processes, & Technology. OPS Publishing, Kenosha (2003)
Redman, T.C.: Data Quality for the Information Age. Artech House, Norwood (1996)
Röthlin, M.: An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context. In: Dadam, P., Reichert, M. (eds.) INFORMATIK 2004, Proceedings of the 34th Annual Conference of the Gesellschaft für Informatik, Bonn, vol. 1, pp. 254–258 (2004)
Sherman, R.: Seven misconceptions about data quality. Software World 35(6), 13–14 (2004)
Walsh, T.: Master Data Management: Cross-System Assessment. DM Review Magazine (January 2004), http://www.dmreview.com/article_sub.cfm?articleID=7911
Wand, Y., Wang, R.Y.: Anchoring data quality dimensions in ontological foundations. Comm. ACM 39(11), 86–95 (1996)
Wittebrock, T.: Master data – Everyone Needs it, but No-one Wants to Maintain it. SAP INFO international, September 15 (2003), http://www.sap.info/goto/en/go/21299/
Xu, H., Nord, J.H., Brown, N., Nord, G.D.: Data quality issues in implementing an ERP. Industrial Management & Data Systems 102(1), 47–58 (2002)
Zornes, A.: Dispelling Master Data Management Myths. DM Direct Special Report, October 20 (2005), http://www.dmreview.com/article_sub.cfm?articleId=1039495
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Knolmayer, G.F., Röthlin, M. (2006). Quality of Material Master Data and Its Effect on the Usefulness of Distributed ERP Systems. In: Roddick, J.F., et al. Advances in Conceptual Modeling - Theory and Practice. ER 2006. Lecture Notes in Computer Science, vol 4231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908883_43
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DOI: https://doi.org/10.1007/11908883_43
Publisher Name: Springer, Berlin, Heidelberg
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