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/ USE CASE /
DEMAND FORECASTING
RETAIL
← Return to Retail Industry
The Challenge
.
Demand forecasting is one of the most important problems in retail. An accurate forecast can improve planning and reduce inventory costs.
Often, companies use high-level demand forecasts based on trends from the previous year.
These methods do not forecast at the product/store level, and often do not account for important factors such as seasonality, promotions, and weather.
The Solution
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Built statistical models to forecast sales by product and store up to 24 months in the future.
Used sales of similar products to forecast sales of new products with insufficient historical data.
Included features promotions and weather data into the model for added accuracy.
The Results
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Product-level forecasts lead to a major reduction in out-of-stock.
Significant reduction of total inventory.
Improved the buying process by enabling data-driven demand planning and budgeting.
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