Enhancing managerial control in production economics through analytics: case of global spare parts supply chain management

Abstract

This thesis focuses on the interface of production economics and business analytics to support managerial control. Specifically, within the field of production economics the thesis deals with the study of spare parts supply chain management (SCM) for a global spare parts company and the utility of analytics, analyzing past performance to enhance managerial control through performance measurement. A review of the literature reveals that limited research has been conducted on the impact of integrating analytics and Big Data in global spare parts SCM. Based on the available research, the thesis develops a methodology for enhancing the utility of performance measurement for managerial control. A single case approach is utilized in the research. Big Data, compiled from several of the case company’s databases, is used within a Geographic Information System and Supply Chain Operational Reference (SCOR) framework to demonstrate that benchmarking would provide valuable insight into the existing business processes of spare parts SCM. It also demonstrates that the use of SCOR metrics provides a more comprehensive understanding of the case company’s Key Performance Indicators (KPI). Finally, the research finds that the use of benchmarking provides greater clarity concerning trends in current SCM processes for managerial control.