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Logistics
Supply Chain Optimization Saves $12M Annually
ML-powered demand forecasting and route optimization across international supply chain network, delivering $12M in annual savings.
Client: Global Shipping CompanyDuration: 7 months
$12M
Annual Savings
18%
Faster Delivery
92%
Forecast Accuracy
25%
Less Inventory
The Challenge
Inefficient routing, poor demand forecasting, and excess inventory were costing millions. Manual planning couldn't keep up with the complexity of global operations.
Our Solution
We implemented ML models for demand forecasting, route optimization, and inventory management, integrating real-time data from IoT sensors, weather, and market conditions.
Key Results
Annual logistics costs reduced by $12M
Delivery times improved by 18%
Demand forecast accuracy reached 92%
Inventory carrying costs reduced by 25%
Tech Stack
PythonOR-ToolsProphetSnowflakeTableau
"The optimization system has given us visibility and control we never had before. We're making smarter decisions faster across our entire network."
Chief Operations Officer
Global Shipping Company
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