Machine learning in supply chain management

Abstract

Almost every day newspapers and online media publish articles about the ongoing development of machine learning and related applications. Eventually, the practical use cases seem infinite and the potential especially for the efficient organization of supply chains is difficult to determine. This paper examines different applications as well as the underlying operating principles of self-learning algorithms in order to derive implications for supply chain management. Furthermore, an outlook for the prospective development of machine learning and the related further establishment of cognitive automation will be presented.