Demand planning is a complicated, collaborative process wherein the understanding of future customer demand helps in deciding inventory, production, revenue, and services across the organization. While accurate forecasting is an important step towards it, the end decisions are about deciding between various plausible tradeoffs. Typically, such tradeoffs are evaluated in an ad-hoc manner at the best, and there is no one-size-that-fits-all solution in terms of which tradeoff to choose to operationalize.
In this webinar, we’ll be discussing recent technological advances that enable evaluation of feasible trade offs between multiple objectives using historical data with the help of scenario analysis so that teams working collaboratively can make such decisions that are right for them at that time.
Dr. Devavrat Shah successfully combines academia and entrepreneurship: he is a professor and a director of Statistics and Data Science Center at MIT and a CTO and co-founder of Ikigai Labs. Devavrat co-founded Celect, a predictive analytics platform for retailers, which he sold to Nike. Devavrat holds a Bachelor and PhD in Computer Science from the Indian Institute of Technology and Stanford University, respectively.
Todd has extensive experience in coordinating demand planning processes and S&OP. He was involved in Finance, Customer Service, Supply Chain, and Sales Planning. He is an Advanced Certified Professional Forecaster (ACPF) and holds a BS degree from Boston College and an MBA from University of New Hampshire with a focus in Supply Chain Management and Marketing. Todd is also a member of the Institute of Business Forecasting & Planning (IBF) Board of Advisors and has served as a keynote speaker & panelist for IBF Executive Forums and conferences. Todd has also published in the IBF’s Journal of Business Forecasting.