Matching Inventory Replenishment Heuristics To Demand Patterns: A Cost/benefit Approach

Abstract

Behavioral research indicates that bounded rationality and resource constraints support the use of "fast and frugal heuristics" that intentionally exclude some available information from decision models. Inventory replenishment decisions must be made quickly and efficiently, and as such are a promising realm for the use of fast and frugal heuristics. This research includes a simulation study to identify significant relationships among heuristics and demand patterns, yielding inferences regarding the advantages of selecting replenishment models to match demand patterns. Findings from the simulation are validated against three years of actual usage data for 278 independent demand items from a single industrial company. The research also develops a process-driven analytical framework for identifying best-fit demand patterns for independent demand items. The final section of the study presents a cost/benefit analysis that recognizes the differential costs of implementing and managing alternative replenishment models, and offers inferences regarding the use of simple heuristics in lieu of more data-intensive models for inventory replenishment decisions.