Abstract
pare parts inventory management is different from other types of inventory as it has unique characteristics that make it complex to control. The random demand patterns and necessity to ensure accessibility of high value items are just two of the major challenges in managing such inventory. The company which has served as a basis for this research is taking steps to improve their current practices. This research is exploratory and aims to identify practical systematic methods to improve business efficiencies in inventory management. Based on observations, interviews, literature research and analysis, various improvement options were identified. To streamline current inventory, we recommend various changes. First, we propose revising the current inventory classification so that inventory is classified based on function and consumption patterns. Second, with the revised classification, we suggest specific inventory model control systems and forecasting techniques to be adopted for the respective types of inventory. Third, we recommend exploring further the concept of centralization and examining its benefits in planning across multi-echelon entities. We also examined other transactional improvements that did not involve statistical approaches. This included streamlining process flows, enhancing the IT systems’ capabilities and establishing decision models for stocking inventory at various store locations. This research demonstrates how models can help companies manage the risks in reducing spare parts inventory, while ensuring that factors such as service levels and reliability are not compromised. Some of these recommendations can also be extended to other inventory types that bear similar characteristics.