Strategies for Master Data Management: A Case Study of an International Hearing Healthcare Company

Abstract

Data quality (DQ) issues consume a significant part of many companies' administrative and operational costs. To reduce such costs, companies often engage in master data management (MDM) initiatives to improve their DQ. MDM is, however, not a silver bullet that solves all data quality issues, but typically there are trade-offs between different data management strategies. Such trade-offs have not received much attention in the academic literature, and conceptualizations of the strategies for implementing MDM are sparse. Thus, with the aim of conceptualizing MDM strategies and understanding their consequences, this paper conducts a longitudinal case study at a large international hearing healthcare company in which an MDM initiative was implemented. The analysis identifies consequences of centralized and decentralized MDM approaches, on which basis four distinct strategies for data management are defined.