While a recent Forbes article on machine learning in supply chain focuses mainly on a particular vendor’s supply chain solution, it serves to highlight some of the ways that machine learning has more broadly been used to address persistent logistics challenges in business. (Given some companies’ reluctance to adopt “unproven” technologies, articles demonstrating that machine learning has been helping optimize operations for a long time are most welcome.)
A notable example from the article describes how machine learning can forecast across different time horizons to solve production or distribution problems, such as needing to predict a two week production schedule or a one week projection of inventory levels in a given region.