Optimizing inventory and enhancing efficiency through material master data management using a decision support system

Effective management of material master data is crucial for organizations to optimize their inventory and increase operational efficiency with the help of Enterprise Resource Planning (ERP) systems. This thesis explores the role of material master data management in achieving these goals and evaluates the effectiveness of a special decision support module developed for this purpose. The study begins with a comprehensive review of the literature on material master data management and inventory optimization. Key concepts that form the foundation of the research methodology, good practices in the industry and the litarature, and research gaps are identified. The research methodology encompasses several phases, including data collection, decision support system (DSS) development, implementation, and performance evaluation. Key performance indicators (KPIs) such as increase in inventory transfer between different locations, decrease in idle inventory, time to create material master data, percentage of duplicate material master data in the system were measured before and after the implementation of the module. With qualitative assessments through interviews and surveys, feedback was gathered from system users and stakeholders. The findings demonstrate that effective material master data management facilitated by the decision support module positively impacts inventory optimization and operational efficiency. Based on the findings, this thesis offers recommendations for enhancing material master data management practices in the ERP context. These recommendations address challenges related to data quality, consistency, and governance. The research contributes to the knowledge in ERP systems, supply chain management, and inventory control, enabling organizations to optimize their inventory management practices and improve operational efficiency. Keywords: Material Master Data Management, Inventory Optimization, Decision Support System