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.