Classification of Inventory Management Methods Based on Demand Analysis in Supply Chains

Abstract

Improving the efficiency of inventory management in supply chains remains relevant for industrial, commercial, service and other enterprises. The results of a supply chains survey (distribution center - stores) with weekly deliveries throughout the year demonstrated that inventory management strategies may be classified into three groups: smooth (more than 47 weeks per year deliveries are recorded), low (from 20 to 46 weeks per year), and sporadic and lumpy (less than 20 weeks per year). The conducted studies have shown that for three groups of inventory management strategies in supply logistics, it is advisable to form three groups of calculation models that allow obtaining quantitative estimates of supply amount and making decisions under conditions of certainty, risk and uncertainty. The first group of calculation models includes Last period or Naive, as well as Exponential smoothing with trend, Multiple regression, etc. The second group consists of combined models, including estimates of the first group and expert estimates under risk conditions. The third group involves models based on decision-making under conditions of uncertainty. The proposed approach allows making reasonable management decisions based on the identification of the demand type to improve the efficiency and reliability of the supply chain.