Determining optimal inventory positions in an urban network

Abstract

Supply chain networks are becoming increasingly complex due to the aggressive growth of multiple digital trends, like the rise of e-commerce and the increased customer expectations, which have been enhanced through the pandemic over the last few years. Therefore, this study proposes a model to develop an inventory optimization strategy for a multi-tier supply chain case study in the US market, considering the supply and demand variability for local and international distribution. First, different approaches from the theoretical perspective are analyzed, from traditional inventory management to the new end-to-end perspectives. After that, details of the methodology will be explained, considering the statistical benefits of demand pooling. Finally, real numbers from a case study are applied to the methodology to measure the solution's impact, followed by the conclusions found from the study.