Data Quality Issues When Quantifying Costs of Complexity

A. M. Staskiewicz*, L. Hvam, A. Haug

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Increased demand for product and service variety has meant that many manufacturing companies face problems of increasing product and process complexity. Literature on complexity management provides means for reducing product and process complexity based on quantifying product complexity costs, but when determining product complexity cost, little attention is paid to data quality challenges. The purpose of this paper is to expand the literature on quantifying product complexity costs by clarifying the role of data quality. This is done based on a case study at a world-leading healthcare product manufacturer, where reducing product complexity was investigated. The case study showed that poor data quality resulted in extra use of resources for finding the needed data and implied that the scope of the project had to be significantly reduced. On this basis, this paper argues that methods for reducing product complexity need to incorporate data quality perspectives more.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Number of pages5
PublisherIEEE
Publication date2021
Pages949-953
ISBN (Print)978-1-5386-7220-4
DOIs
Publication statusPublished - 2021
Event2020 IEEE International Conference on Industrial Engineering and Engineering Management - , Singapore
Duration: 14 Dec 202017 Dec 2020

Conference

Conference2020 IEEE International Conference on Industrial Engineering and Engineering Management
Country/TerritorySingapore
Period14/12/202017/12/2020

Keywords

  • Product complexity cost
  • Data quality
  • Product-process complexity
  • Complexity reduction

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