Operational Excellence through drone-based inventory monitoring: a mathematical model proposal

Managing inventories is associated with high costs, which may account for about a third of the total logistics costs. These costs arise from different factors such as the consequences of Inventory Record Inaccuracy (IRI). IRI represents the discrepancies between the physical and digital inventories. These discrepancies generate great labor efforts to solve them, along with write-offs and oversells. This leads to economic and productivity losses. To reduce the impact of IRI, inventories are periodically controlled for audit compliance and correct the physical-digital discrepancies. This is usually done through costly, time-consuming, and labor-intensive approaches. The recent advances in drones have led to their adoption for logistic purposes, including inventory monitoring. Drone-based inventory monitoring entails several benefits compared to conventional approaches such as being automated and quicker. This may result in better accuracy and performance, contributing to operational excellence. Despite this, available literature mainly focuses on the technical and conceptual development of drone-based inventory monitoring systems. Less interest has been devoted to evaluating their economic viability compared to conventional labor-intensive approaches, particularly considering in the analysis reduction in labor and IRI-related issues. To this end, this work aims to develop a mathematical model to compare drone-based inventory monitoring with the labor-intensive conventional technique, considering the presence of write-offs and oversells. The model is tested on two case studies: a manufacturer and a third-party logistics (3PL). Warehouse managers may exploit the model for preliminary assessment of the economic benefits of drone-based inventory monitoring.