Assisted Demand Planning Using Machine Learning for CPG and Retail | SAS
Assisted Demand Planning Using Machine Learning for CPG and Retail

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Assisted Demand Planning Using Machine Learning for CPG and Retail

presented by SAS


More than 40 percent of a demand planner’s time is spent managing information and data. Another 30 percent to 40 percent is spent managing and fine-tuning the demand forecast based on new market and customer information, changes in marketing programming (tactics) and coordinating the consensus forecast (plan). Finally, creating and updating KPI reports represents about 10 percent of a demand planner’s time. With the introduction of intelligent automation using machine learning, a large portion of the manual, repetitive activities can be automated, which would enable demand planners to be more productive and add real value to the overall process.

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