Machine Learning & Supply Chain Management - InTek Freight & Logistics: The Podcast Episode 35

Machine learning - a subset of AI - is a tool that many in the supply chain management field already use for inventory forecasting. But using optimal machine learning - a technique developed by our guest Dr. Naren Agrawal and his co-authors - can unlock a whole new world of decision-making ability for businesses.
Dr. Agrawal, the Benjamin and Mae Swig Professor of OMIS at Santa Clara University, shares what OML is, how it improves upon other uses of machine learning that focus only on the forecast and why getting to the decision is often the problem for companies that feature teams with competing perspectives, data & interests.
He talks us through two different types of companies with before and after scenarios for each, the need for agility and resilience in supply chain planning, and more. Plus, we discuss a commonality successful businesses he's worked with share, and his outlook for students and future supply chain managers.
Read How Machine Learning Will Transform Supply Chain Management via the Harvard Business Review here: hbr.org/2024/0..., and find more from Dr. Agrawal here: www.scu.edu/execed/custom/universitypartnerships/faculty/naren-agrawal-phd.
Subscribe or follow now to catch new episodes of InTek Freight & Logistics: The Podcast as soon as they're out, and please do rate and review us. Have a question? Contact us at [e-mail]. And visit our website, www.intekfreight-logistics.com to learn more about InTek.