Apparel / Manufacturing
AI-Driven Forecasting for Apparel Production and Demand Planning
Faced with volatile demand and overproduction, the client partnered with GC Consulting to implement AI-powered forecasting. Using Azure ML integrated into D365 SCM, we delivered automated demand predictions that cut excess inventory by $2.7M in the first season.
Global sportswear manufacturer
Azure Machine Learning, Dynamics 365 Supply Chain Management, Power BI
The Challenge
- Overproduction driven by static forecasts and manual planning
- 15 percent average mismatch between projected and actual sales
- Excess inventory storage costing over $600K per year
Our Solution
We first collected three years of sales, returns, and market data, combining it with promotion calendars and macroeconomic indicators.
Our data science team developed an ensemble forecasting model using Azure ML, incorporating seasonality, product hierarchy, and regional behavior.
The model was deployed into D365 SCM using embedded APIs and triggered weekly updates to procurement and production schedules.
We built monitoring dashboards in Power BI to measure forecast accuracy and alert planners to anomalies.
The process was paired with scenario planning workshops with merchandisers and supply planners, increasing trust in the forecasts and enabling agile responses to demand shifts.
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Implementation Timeline
Results After 2 Seasons
reduction in excess inventory
improved forecast accuracy
reduction in emergency production cycles
faster adaptation to regional product trends
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