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.
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.
$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.
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