David Simchi-Levi is an American academic working as a Professor of Engineering Systems at Massachusetts Institute of Technology. He is also the founder or co-founder of several companies. Simchi-Levi’s research focuses on supply chain management, revenue management, and business analytics.
Companies face a variety of challenges in designing and optimizing their supply chains. Over the past few decades, advances in information technologies have allowed firms to move from decision-making based intuition and experience to more automated and Data-driven methods. As a result, businesses have seen substantial cost reductions and improved customer service.
Unfortunately, business planners still need to spend considerable time and effort to understand the recommendations coming out of their systems, analyze various scenarios, conduct what-if analyses, and update models to reflect current business environments. Addressing these challenges requires involving data science teams to explain results or update models, hence slowing down decision making.
Motivated by recent advances in Large Language Models, we report how we applied this disruptive technology to address the challenges described above, thus reducing the time to decision from days and weeks to minutes and hours and dramatically increasing planners and executive productivity and impact.
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