We collaborated with a major US food retailer to streamline their dispatch operations. By implementing an AI-driven dispatch planning and optimization platform, we helped improve vehicle utilization, reduce shipping costs, and enhance overall logistics efficiency, delivering significant operational and cost-saving benefits.Â
Business Goals
The client is one of the largest food retailers in the US, operating a vast network of physical stores and e-retailers. As they expanded their logistics operations, ensuring timely and cost-effective delivery became crucial. With numerous constraints on truck capacity, delivery times, and shipping modes, the company was facing high transportation costs and inefficiencies in fleet utilization.
The client needed a solution to:
- Maximize vehicle load utilization.
- Reduce logistics costs while adhering to strict delivery schedules.
- Minimize manual effort spent on optimizing dispatch planning.
Solution
When we partnered with the client, we identified certain gaps in their first-mile dispatch process which included difficulties in managing multiple transport modes and a manual dispatch scheduling system that led to delays and increased costs. To address these challenges, SRM Tech leveraged an intelligent logistics planning platform to streamline the dispatch scheduling process. The system offered an integrated platform that automatically planned and optimized dispatches across multiple transport modes—ocean, rail, and road—based on real-time data and delivery requirements. By using advanced algorithms, the platform ensured the best possible combination of shipment modes, taking into account both cost and capacity.
It also included backlog management system to automatically reschedule unfulfilled orders, improving on-time delivery and resource allocation. The solution continuously adapted to field data, refining its planning strategies over time, and also focused on reducing the client’s carbon footprint by prioritizing eco-friendly transport methods like rail.
Key Highlights
- Multimodal Planning: Optimized dispatches across ocean, rail, and road transport to meet delivery deadlines.
- Shipping Cost Optimization: Identified the most cost-effective shipment combinations based on capacity and cost constraints.
- Backlog and Order Replanning: Automatically rescheduled unfulfilled orders for the next available dispatch to avoid delays.
- Real-Time Adaptation: Learned from field data, improving dispatch accuracy with every iteration.
- Sustainability Focus: Prioritized eco-friendly transportation methods, such as rail, reducing environmental impact.
- Labor Savings: Automated planning processes, saving thousands of man-hours and enabling more strategic use of resources.
Technologies Used
ML engine, Python, SQL, Streamlit
Outcomes
- 8% reduction in dispatch costs
- 25% increase in fleet utilization
- Thousands of man-hours saved
- Significant reduction in carbon footprint
Are you experiencing similar challenges in forecasting, inventory management, capacity planning, or labour productivity? Our expert team would be happy to extend assistance and deploy our solution accelerators to deliver value across your supply chain journey.
Drop in your enquiry here or email us at dpsales@srmtech.com!
