Supply chains traditionally are linear in nature, with a discrete progression of design, plan, source, make, and deliver. Today, the shift from linear/sequential supply chain operations to an interconnected system of supply operations gives us that picture of how companies would compete in the future. Looking specifically at demand management, there are numerous factors influencing the demand like point-of-sale, shipment, out-of-stock, excess inventory, promotions, cannibalization, competitor promotions, pricing, social media influence, product review, policies, and so on. The traditional statistical methods are unable to accommodate these inputs into the demand generation, hence the need for an AI-based process can evaluate the multiple factors influencing demand and project a forecast with higher accuracy.

In this session, Sugantha discussed the rapidly changing consumer landscape across increasing customer demands for agility & speed, eCommerce induced demand volatility, impacts of new normal, socio economic political influence, etc. She also presented the challenges with traditional processes & systems and how a highly responsive AI-backed mechanism can drive significant improvements across the supply chain and its metrics.