AI-Powered Inventory Manager
Ecommerce
Overview
A multi-channel retailer was simultaneously losing revenue to stockouts on high-margin SKUs and tying up working capital in slow-moving overstock. Manual spreadsheet-based planning used 6-week rolling averages, too slow to respond to promotional spikes or supplier variability. VINSINFO delivered an AI-driven demand forecasting and inventory optimisation system that automates reorder decisions across the full SKU catalogue.
Stockout reduction
60-
%
Overstock minimised
25-
0
%
Forecast accuracy gain
0
%
Challenge
- Demand forecasting based on slow, inaccurate 6-week rolling averages
- Stockouts on high-margin SKUs causing recurring revenue loss
- Overstock tying up working capital and requiring markdown clearances
- Manual planning unable to respond to promotions or seasonality
- No visibility into supply chain lead time variability
- Inventory planning team overwhelmed by SKU volume
Solution
- ML demand forecasting combining time-series models with seasonal and promotional signals
- 12-week SKU-level forecast horizon with weekly refresh
- Automated reorder recommendations fed directly into procurement workflow
- Safety stock calculations dynamically adjusted to lead time variability
- Multi-location inventory optimisation across warehouses and channels
- Supply chain disruption prediction for high-risk supplier routes
Impact
Stockouts reduced by 60–70% across the SKU catalogue
Overstock minimised by 25–40%, releasing working capital
Inventory carrying costs cut by 20–35%
Forecast accuracy improved by 30%
80% of reorder decisions now fully automated
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