Improving Inventory Management at an Automotive Company by Applying the ABC–XYZ–FSN Classification Method

• M. van As School of Industrial Engineering, North-West University, South Africa https://orcid.org/0009-0003-3574-7366
• J.H. Bührmann School of Industrial Engineering, North-West University, South Africa https://orcid.org/0000-0003-0657-9933

DOI:

https://doi.org/10.7166/36-3-3344

Abstract

Automotive dealerships often face inefficiencies in spare parts inventory management owing to demand fluctuations, long backorder lead times, and inconsistent categorisation practices. At Dealership X, these issues have resulted in 37% overstock and 24% dead stock, leading to financial losses and reduced service efficiency. The aim of this study was to improve inventory control by analysing the dealership’s stock data, evaluating current classification practices, and developing a more accurate reclassification approach. The research combined detailed data analysis with a review of established inventory management studies to identify proven methods for handling intermittent demand and obsolete stock. Based on these insights, the ABC–XYZ–FSN classification system was selected and applied to the dealership’s dataset to provide a more reliable categorisation of parts. A user-friendly dashboard was also designed to display reclassified results, showing the category of each part, whether there is excess stock, and whether ordering is necessary. While implementation of the system fell outside the project scope, the results demonstrate that the ABC–XYZ–FSN classification method, supported by the dashboard, could improve stakeholder decisions, and is recommended for future adoption to reduce overstocking and to improve the management of critical parts.