Quarterly forecasting was not a strategy. It was a constraint.
Weekly Forecasting on Microsoft Fabric, Instead of Quarterly by Hand
“By the time the forecast is finished it describes a quarter that already happened. We are not planning. We are reporting, late.”
A global outdoor equipment manufacturer forecasted six seasonal product lines by hand in Excel, quarterly, from a dozen sources. ERP, supplier, and regional inputs had no common structure. Cadence was set by spreadsheet time. A critical input arrived as a third-party quarterly file. Planners were spending twenty hours a week being a data pipeline.
Phase one, three months: bottleneck analysis, daily data automation into a database, and reverse-engineering the third-party supplier logic so it could run monthly in-house. Twenty hours a week came back before any modelling shipped. Phase two, four months: Microsoft Fabric consolidation, model selection across Prophet, supply chain models, and machine learning with full feature engineering, best-fit per product line. A generative AI natural language layer over the forecast and dimension tables let planners self-serve.
- 20 hours per week returned to the planning team
- Forecast cadence moved from quarterly to weekly, a 13x increase
- Third-party supplier dependency removed, cadence moved from quarterly to monthly
- Seven months, first pipeline to consolidated Microsoft Fabric platform
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Detailed methodology, results, and implementation notes as a PDF.
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