Inventory optimization is important for reducing supply chain costs. However, inventory levels are driven by factors that are difficult to assess. The purpose of this paper is to identify the main drivers of optimizing inventories and to assess their impact on a supply chain. The main drivers of optimizing inventories were identified in a two-stage process. First, a thorough study of literature was conducted, followed by a series of interviews with selected employees of a global Danish manufacturer that was used as a case study. Simulation modeling was used to create different scenarios and to assess their impact on the supply chain. The results of the simulation suggest that product classification (based on ABC analysis) is a useful tool for optimizing inventories, especially in relation to stock on hand, whereas lead time and shipping frequency offered few improvements in the studied case. Moreover, demand variance appears to have a significant impact on stock on hand and service levels (measured by fill rate). The paper proposes: (1) a practical framework for identifying the main drivers of inventory optimization, (2) simulation modeling as a way to assess their impact, and (3) a multi-echelon assessment method. As a result of the proposed work compared with the current practices, this study undertakes a holistic approach to identifying and assessing the impact of inventory drivers, presents a framework and approach that is useful for practitioners, and makes a novel contribution to the body of research on multi-echelon inventory optimization.
- Product classification
- ABC analysis