Virtual Roundtable- Risk Assessment for Retailers: Using AI for Demand Planning & Critical Decision-Making

Today’s businesses survive depending on how effectively they can sense and react to situations in a dynamic and unpredictable world. Influences from geopolitical issues, weather, and diseases to rapidly changing customer expectations will require businesses to make decisions at the edge.

Traditional approaches to retailing, which includes forward-looking multi-seasonal planning, merchandising, sourcing, and supply-chain decisions, are strangling retail companies. The proof is in the spate of recent bankruptcies. All of these organizations had one common factor — a complete mismatch between demand and supply. Business models are made of two elements: data and decisions. Data, the new oil, is now abundant and getting richer by the minute; and in turn, decisions need to be made rapidly at the edge of the organization — where demand meets supply.

Join IRPA AI for a free virtual roundtable discussion for senior Retail executives on August 26th covering how AI is being used to crunch enormous amounts of data, find patterns and trends in that data, provide scenarios to key decision makers in the value chain, and make those decisions when they need to be made in a split second.

Using Artificial Intelligence, businesses can move all critical decisions including Capital Budgeting, Merchandising, Sourcing, Supply Chain, Allocation and Fulfillment closer to the market and closer to the season; businesses can design multiple levels of supply chain and use machines to suggest mitigation strategies, deciding how — and where — to fulfill a customer request from.

Panelists include:

– Ajit Patel, CIO Forever 21

– Digital Transformation Expert Mark Etwaru, CIO at WhoWhatWhy & Transformation Advisor, Estée Lauder

 – Supply Chain Optimization Expert Pierluigi Riva, CTO  of AI Supply Chain Platform ORS ai.& Professor, University of Torino

– Daniel Goodstein, President Media & Events, IRPA AI & Digital Enterprise Institute


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