Reducing inventory costs by 30% with AI-powered demand forecasting
Leading Australian retailer | Retail | 4 months
The challenge
The client was facing significant challenges with inventory management, leading to frequent stockouts and overstocking situations. Their manual forecasting process couldn't keep up with seasonal variations and market trends.
Our solution
We implemented a machine learning-based demand forecasting system that analysed historical sales data, seasonal patterns, external factors, and real-time market trends to predict future demand with high accuracy.
Results
- ✓30% reduction in inventory carrying costs
- ✓45% decrease in stockouts
- ✓25% improvement in forecast accuracy
- ✓ROI achieved within 6 months
Technologies used
PythonTensorFlowAWS
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