Sales Forecasting Model
Machine learning forecasts by product and region, delivered inside Power BI for planners.
FMCG & Retail · Supply Chain
Illustrative example build, not a client case study.
Demand planning relies on last year's numbers and gut feel, leading to stock-outs in some regions and excess stock in others.
Technology
- Python
- Microsoft Fabric / SQL
- Power BI
- Excel
- 1
Prepare history
Sales, promotions, seasonality and distributor data cleaned and combined.
- 2
Train & test models
Forecast models compared against actuals to choose the most reliable approach.
- 3
Deliver to planners
Forecasts with confidence ranges published in Power BI and the planning workbook.
- 4
Monitor
Forecast accuracy tracked monthly and models retrained as patterns change.
Designed to deliver
- More reliable demand plans
- Earlier warning of shortfalls
- Planning discussions based on evidence
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Demand & inventory forecasting
Machine learning forecasts by product and region feed the planning workbook and Power BI.
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