Category Demand Planning with
Machine Learning and External Data
The average one-year consumer goods category forecast is off by 20%, according to Institute of Business Forecasting. For a retail or CPG company with $1 billion in annual revenue, that can result in as much as $225 million in annual losses on excess inventory costs alone. Most CPG and retail companies rely on historical sales trends to predict future performance, nearly ignoring external factors that can affect demand.
Technologies such as machine learning and cloud-computing provide the ability to incorporate external data to understand changes in consumer behavior, demographics, and economic headwinds that will affect performance. In this webinar, we will discuss how these new technologies are used to dramatically improve category demand planning.
Speakers:
About Frank Mendoza
Frank Mendoza is CEO of Catalytics, a consulting firm that enables Fortune 500 companies to introduce emerging technologies, like AI and Advanced Analytics, to help create a more data-driven culture. Before founding Catalytics, he was an Executive Leader of the Services and Support Center of Excellence at 3M. Prior to working with 3M, Frank spent over a decade with Dell, serving in multiple roles in Strategy & Business Transformation, M&A, Manufacturing and Sales Operations.
Riddhi Sheth is Director of customer success at Prevedere. Riddhi oversees the engagement and delivery of Prevedere solutions to drive incremental value for the many Fortune 500 retail and CPG customers we have. Her prior experience include 15 years in SaaS organizations at DemandTec and IBM, serving in various leadership roles in Professional Services and Global Sales Enablement for their Merchandising Planning and Optimization solutions.
