Methodology for assessing the accuracy of inventory results

This article highlights the need to develop an objective methodology for evaluating the accuracy of inventory results, given the crucial roles that reliable data play in financial reporting and inventory management. The relevance of this research is also motivated by the persistent low levels of accuracy, which have led to significant financial losses and wasted energy. This work will develop a statistically based, technology-supported approach to inventory accuracy assessment that can pinpoint all types of errors quantitative, qualitative, and document-related in real-time. The novelty of the proposed methodology lies in the combination of five interrelated stages: formalization of tolerances and sample size calculation using a binomial model, a two-stage physical recount with mandatory recount, calculation of key performance indicators, application of threshold logic for cell blocking in the WMS, and continuous RFID monitoring with visualization on BI dashboards. Such a closed loop of target–measure–verify–classify within the PDCA framework ensures not only objective recording of the current state but also a quantitative link between improvements and economic effect. The main findings of the study demonstrate that integrating WMS blocking logic, continuous RFID identification, and streaming BI analytics can increase inventory accuracy to 97–99% and reduce shrinkage to double-digit percentages without increasing the frequency of full inventories. A pilot implementation in a retail chain showed an increase in accuracy from 72% to 99.4%, a reduction in shrinkage from 17% to 1.7%, and a decrease in audit time from 22 minutes to 38 seconds, accompanied by savings in labor and capital resources. The article will be helpful to inventory accounting and management specialists, logistics and finance managers, as well as WMS and RFID solution developers and integrators.