Supply Chain Optimization
ML-powered demand forecasting system
The Challenge
A manufacturing company was facing significant inventory challenges - overstocking slow-moving items while frequently running out of popular products. Their rule-based forecasting system couldn't adapt to market changes or seasonal patterns, resulting in millions in tied-up capital and lost sales.
Our Solution
We developed an ML-powered demand forecasting system that analyzes historical sales data, market trends, seasonal patterns, and external factors to predict future demand with high accuracy. The system continuously learns and adapts to changing conditions.
The solution integrates with their ERP system to automatically adjust reorder points and quantities, optimizing inventory levels across their entire product catalog.
Results
- 25% reduction in overall inventory costs
- 40% decrease in stockout incidents
- 18% improvement in forecast accuracy
- Freed up $2.3M in working capital within 6 months