Operational Efficiency Improvement through Integrated Inventory Management and Control: Case Study of PT XYZ

Abstract

This study examines how integrated inventory control improves operational efficiency at PT XYZ, a wholesaler of imported frozen beef. We apply ABC classification, three time-series forecasting techniques (Moving Average, Exponential Smoothing, Least Squares), and the Economic Order Quantity (EOQ) model. At the SKU level, Exponential Smoothing consistently yields the lowest forecasting error across 2023–2024 and most closely tracks actual demand patterns. EOQ analysis indicates substantial cost efficiency relative to actual practices for the majority of SKUs; for instance, TRRL00068 achieves 43–45% annual savings over 2022–2024 and TRSFF00066 achieves 43–46% savings in the same period. These findings demonstrate that disciplined inventory control—anchored in accurate forecasting and EOQ-based ordering—reduces total inventory costs and supports more reliable service levels. The implications align with sustainable operations by lowering waste from overstock and mitigating stockout risks.