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Using Machine Learning to Enhance Short-Term Demand Sensing

Started ‎10-12-2022 by
Modified ‎10-25-2022 by
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Presenter: Charlie Chase

 

Consumer packaged goods (CPG) companies account for some of the biggest industries in the world and provide items that are used regularly by consumers including food, beverages and other household products. Since many products provided by CPG companies have short shelf lives and are intended to be used quickly, companies need to routinely replenish products on store shelves to meet consumer needs. Effective supply chain management is critical to ensure the timely replenishment of products by properly managing the movement and storage of raw materials and finished goods from the point of origin to the point of consumption. A key component of supply chain management for retailers and CPG companies is forecasting short-term consumer demand accurately to ensure their products are available to consumers when they need them. Implementing a short-term forecast (one-to-eight-week) is critical to understanding and predicting changing consumer demand associated with sales promotions, events, weather conditions, natural disasters and other unexpected shifts in consumer demand patterns. Short-term demand sensing allows retailers and CPG companies to predict and adapt to those changing consumer demand patterns.

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‎10-25-2022 03:04 PM
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