Freight Optimization: AI-Driven Cost Reduction

Client: Fortune 500 Manufacturing Company

Challenge

Rising freight costs, inefficient route planning, and frequent delivery delays.

Manual adjustments in manufacturing and logistics caused inefficiencies.

Needed a data-driven approach to streamline supply chain decision-making.

Solution

Cleaned and structured supply chain data, including sales forecasts, production costs, and freight rates.

Implemented Mixed Integer Programming (MIP) for real-time, scalable optimization.

Designed rules to optimize manufacturing and shipping while ensuring operational feasibility.

Automated decision-making, improving efficiency and reducing manual interventions.

Results

$8M cost savings by eliminating inefficiencies and manual planning.

Optimized order allocation with real-time manufacturing and shipping recommendations.

Reduced planning time, increasing operational efficiency.

Enhanced customer experience with faster, more cost-effective deliveries.

Data-driven insights enabled visualized, instant decision-making.