Ofner, MartinMartinOfnerStraub, KevinKevinStraubOtto, BorisBorisOttoÖsterle, HubertHubertÖsterle2023-04-132023-04-132013-05-01https://www.alexandria.unisg.ch/handle/20.500.14171/8934610.1108/JEIM-05-2013-0026Purpose - The purpose of the paper is to propose a reference model describing a holistic view of the master data lifecycle, including strategic, tactical and operational aspects. The Master Data Lifecycle Management (MDLM) map provides a structured approach to analyze the master data lifecycle.Design/methodology/approach - Embedded in a design oriented research process, the paper applies the Component Business Model (CBM) method and suggests a reference model which identifies the business components required to manage the master data lifecycle. CBM is a patented IBM method to analyze the key components of a business domain. The paper uses a participative case study to evaluate the suggested model.Findings - Based on a participative case study, the paper shows how the reference model allows to analyze the master data lifecycle on a strategic, a tactical and an operational level, and how it helps identify areas of improvement.Research limitations/implications - The paper presents design work and a participative case study. The reference model is grounded in existing literature and represents a comprehensive framework forming the foundation for future analysis of the master data lifecycle. Furthermore, the model represents an abstraction of an organization's master data lifecycle. Hence, it forms a theory for designing More research is needed in order to more thoroughly evaluate the presented model in a variety of real-life settings.Practical implications - The paper shows how the reference model enables practitioners to analyze the master data lifecycle and how it helps identify areas of improvement.Originality/value - The paper reports on an attempt to establish a holistic view of the master data lifecycle, including strategic, tactical and operational aspects, in order to provide more comprehensive support for its analysis and improvement.enDatenqualitätsmanagementStammdatenmanagementjournal article