Global supply chains are more volatile than ever. Traditional linear forecasting models are failing, leading to excess inventory or critical shortages.
From Reactive to Predictive
Our recent work with LogiChain focused on integrating non-traditional data—weather patterns, geopolitical sentiment, and port congestion—into their demand forecasting.
- Dynamic Routing: Real-time logistics adjustment based on predictive delay alerts.
- Inventory Balancing: AI-driven redistribution of stock across regional hubs to meet shifting demand.
Results
By shifting to a multi-modal ML approach, the client achieved a 34% reduction in operational overhead and a 78% decrease in stock-out incidents over 12 months.
34%
Cost Reduction
78%
Fewer Stock-Outs