Inventory Cost Minimization Through Item Categorization and Demand Forecasting: A Case Study-based Approach

Abstract

Inventory of spare parts is needed for proper maintenance and repair of final products, vehicles, industrial machines and equipment. Holding of excess spare parts for long time generally results in extra cost (in form of holding cost, tied up capital and obsolescence cost). This study, therefore, tries to minimize the inventory cost through spare parts categorization and demand forecasting. ABC analysis was used to identify to most valuable items (Category A Items). Croston's method was used to determine forecasted demand of the Category A items obtained from ABC analysis. Existing spare parts inventory is found to hold a substantial fraction (39%) of idle or unused items. Croston's method showed its potential in predicting the forecasted demand of Category A items used in cement industries. Even though the ordering cost increases four times the existing one, the overall inventory cost of the Category A items decreases by 64% as compared to their existing inventory cost.