Application of ABC and XYZ methods to inventory management in an automotive industry enterprise

Abstract

This article explores the application of the ABC and XYZ classification methods in inventory management within the automotive industry. Effective inventory control is essential for ensuring supply chain resilience and cost optimisation in a sector characterised by high product variety and fluctuating demand. The objective of the study is to examine how combining demand-based (ABC) and variability-based (XYZ) analyses can support strategic decision-making in supply logistics. The methodology includes a theoretical review of inventory classification techniques, followed by a case study demonstrating the implementation of the ABC/XYZ matrix on a selection of automotive components. The results show that this cross-classification enables more precise inventory segmentation, enhances forecasting accuracy, and facilitates tailored inventory control strategies. For each inventory category defined by the matrix, specific management recommendations are proposed, addressing ordering policies, safety stock levels, and supplier coordination. The findings confirm that the integrated use of ABC and XYZ methods supports demand analysis, improves service levels, and reduces excess stock, thereby increasing operational efficiency. The study contributes to the ongoing development of data-driven approaches in inventory management and offers practical insights for practitioners in the automotive supply chain.