MASTER DATA MANAGEMENT: A CONCEPTUAL FRAMEWORK FOR SUCCESSFULLY SUPPORTING DATA-DRIVEN TRANSFORMATION AND CORPORATE SUCCESS

Digital transformation is reshaping business and public sector structures, increasingly relying on high-quality, strategically usable data. In this context, Master Data Management (MDM) emerges as a critical enabler of data-driven transformation. This study presents a framework – developed using the Design Science Research methodology – that illustrates how MDM, supported by effective change management, contributes to organizational success. A systematic literature review (SLR) identified key success factors, grouped into four dimensions (management, technology, people and organization, and support), and common pitfalls (CP). Change Management (CM) serves as the central link/bridge between MDM and business impact. A combined approach using CM models by Kotter, Hiatt, and Lewin is proposed to support transformation at organizational and individual levels. Using the success chain concept, the transformational framework shows how improved master data capabilities – driven by the success factors and change initiatives – leads to psychological and behavioural changes in data users and, ultimately, to enhanced corporate success like decision-making efficiency, process optimization or technology adaption. MDM is positioned not as a technical tool, but as a strategic asset in digital value creation and corporate success. The paper is part of a series of articles on the topic of “Measuring the Success of MDM”.