AI helps supply chain analytics make better predictions

What if you could apply machine learning and other types of AI to the terabytes of transactional and sensor data being collected from the supply chain? The result could be a much more autonomous and effective form of supply chain analytics and, ultimately, a more responsive supply chain. In fact, there is a lot of interest in using AI and machine learning to enhance supply chain analytics, according to David Simchi-Levi, professor of engineering systems at MIT. Much of the focus in the supply chain is driven by the ability to integrate predictive and prescriptive analytics to, in essence, blend AI and optimization technologies. Specifically, organizations are using AI in two areas of the supply chain: to enhance predictive analytics to understand behaviors and for prescriptive analytics, where optimization technologies take input from machine learning and try to help decision-makers make better decisions, Simchi-Levi said.