Inventory accuracy is critical in most industrial environments such as distribution, warehousing, and retail. Many companies use a technique called cycle counting and have realized outstanding results in monitoring and improving inventory accuracy. The time and resources to complete cycle counting are sometimes limited or not available. In this work, we promote statistical process control (SPC) to monitor inventory accuracy. Specifically, we model the complex underlying environments with mixture distributions to demonstrate sampling from a mixed but stationary process. For our particular application, we concern ourselves with data that result from inventory adjustments at the stock keeping unit (SKU) level when a given SKU is found to be inaccurate. We provide estimates of both the Type I and Type II errors when a classic C chart is used. In these estimations, we use both analytical as well as simulation results, and the findings demonstrate the environments that might be conducive for SPC approach.
Proceedings of the International Material Handling Research Colloquium
Huschka, Kyle; English, John R.; Easton, Todd; and Huschka, Andrew, "Monitoring Inventory Accuracy With Statistical Process Control" (2010). 11th IMHRC Proceedings (Milwaukee, Wisconsin. USA – 2010). 4.