Exchange curve and coverage analysis tools for better inventory management: A case study

Abstract

In this paper, we explore how historical demand information can be used to forecast future demand and how these forecast affect the inventory management system. Forecasting, which have a long-term perspective of operations, is typically based on demand for the goods and services it offers, compared to the cost of producing them. It is used to determine the direction of future trends by using some historical data. We develop a novel and useful yet very simple methodology known as optimal policy curve or exchange curve for planning inventory by using these forecasted demands. Using this curve, reduction of average investment in inventories in the form of cycle stocks/total stocks or number of orders per year or both as desired are done. Controlling the inventory at aggregate levels is analyzed by using a scientific analysis, known as coverage analysis. We verify the idea of exchange curve and coverage analysis using a real-life problem for which data are collected from Durgapur Steel Plant, Durgapur, India, and find its optimal ordering policy and coverage for each raw material. It is found that the results obtained from economic order quantity (EOQ) model are same as the results calculated on the basis of exchange curve.