Data Quality Issues When Quantifying Costs of Complexity

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.