Increasing Efficiency in Inventory Control of Products with Sporadic Demand Using Simulation

Abstract

The goal of this paper is to examine whether, in Q-system inventory control policy, a combination of the reorder point exceeding order quantity leads to minimal holding and ordering costs when dealing with sporadic demand. For this purpose, a past stock movement simulation is applied to a set of randomly generated data with different numbers of zero demand periods ranging from 10 to 90%. The outputs of the simulation prove that in situations where stock holding costs are too high, the simulation tends to reduce average stock by overcoming periods between two demand peaks with an increase in the numbers of small replenishment orders and reaches lower stock holding and ordering costs. Furthermore, the correlation analysis proves that there is a statistically significant relationship (r = .847, p = .004) between the number of time series that reach minimal holding and ordering costs under the control of reorder point (replenishment order) and the demand standard deviation affected by the evolving sporadicity. These findings can support decision making linked with inventory management of products with sporadic demand and contribute to development of business information systems.