ICIQ 2012, the 17th International Conference on Information Quality 1 ORGANIZATIONAL ISSUES IN ESTABLISHING MASTER DATA MANAGEMENT FUNCTION (Research Paper) Riikka Vilminko-Heikkinen Department of Information Management and Logistics Tampere University of Technology, Finland riikka.vilminko-heikkinen@tut.fi Samuli Pekkola Department of Information Management and Logistics Tampere University of Technology, Finland samuli.pekkola@tut.fi Abstract: Master data management (MDM) provides an access to the consistent views of the organization´s most important data, also referred to as master data. In addition to technical issues, there are many organizational items related to MDM and its organizational implementation. However, current academic literature lacks empirical studies on organizational challenges influencing the MDM initiatives. Consequently organizational issues in establishing master data management function in an organization are studied in this paper. Data collection is conducted by partici- patory observations of a year-long MDM project. Reflecting the findings to the literature shows that several new is- sues have emerged. These indicate that the implementation of MDM is also affected by the organization´s ability to identify data owners and associate them with appropriate roles and responsibilities, and to create a unified understand- ing of the key terms and concepts regarding MDM. Also the importance of communication is emphasized. Key Words: Master data management, MDM, organizational issues, organizational implementation, data quality, qualitative research INTRODUCTION Data has been developed in silos over the years. This and the fact that the amount of data has increased rapidly, have caused the data to be stored in numerous information systems (IS) and databases. It is also common that multiple information systems hold the same or nearly the same data [16]. Disparate systems and applications create segregated information. This results in duplicate, incomplete and inaccurate data that leads to inappropriate analytics and, at the end, inaccurate business decisions [25]. Problems with data quality and reliability have thus emerged. These problems create additional costs for organizations and make it problematic for them to use the data [20]. The quality of transactional and inventory data depends directly on the quality of master data [15]. Another angle on the subject is that still 40 % of organizations are unaware of the problems with their data [29]. In order to cope with several data siloes and vast amounts of data quality problems, data is often organized according to its business criticality. To manage business critical data, a new concept, master data as the organization’s core data that forms the basis for business processes [19] has been introduced. Its typical characteristics are stability [26], reuse [5] and high value for the organization [17]. Common examples of master data are customers, products, and vendors. Loshin [17] describes master data management (MDM) as a collection of data management practices that are orchestrated by key stakeholders, participants, and business clients. They utilize business applications, information management methods, and data management tools to implement policies, services, and infra- structures to support the capturing, integrating, and sharing accurate, timely, consistent, and complete mas- ter data. MDM aims at supporting the organization’s functions by providing an access to consistent views of uniquely identifiable master data entities across the operational application infrastructures [17]. MDM