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Weather-Driven Demand Forecasting for CPG
Global Beverage Manufacturer (United States)
15%
Improvement in Forecast Accuracy
Problem
The client needed to improve demand forecasting accuracy by incorporating weather patterns to better align production and distribution planning with real-world consumption patterns.- Complex weather data across multiple geographies with varying formats and quality
- Aligning regional weather variations with corresponding sales data for accurate modeling
- Need for consistent, high-granularity data integration across locations
Approach
We designed and implemented a weather-informed demand forecasting solution using statistical and machine learning techniques.- Integrated weather variables (temperature and precipitation) and historical sales data across regions
- Built statistical and machine learning models to predict weather-driven demand
- Deployed scalable Azure pipelines and Power BI dashboards for planning insights
Results
The solution delivered measurable improvements in forecasting accuracy and planning efficiency.- 15% improvement in demand prediction accuracy
- Enabled weekly-level demand forecasting of beverage consumption volumes
- Improved supply and production planning
"More accurate, weather-aware forecasts have improved how we plan production and distribution across markets."
James Peterson
Head of Supply Chain Planning
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