Case Study

Manufacturer Uses Supply Chain Network Optimization to Uncover 14 Percent Annual Savings


Double-digit savings possible just by optimizing existing distribution strategy

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A manufacturer of motors and electronics wanted to investigate whether there were service improvement and cost savings opportunities in its distribution network. The company had grown through acquisition over several years and knew there was likely opportunity to improve service times by evaluating and streamlining the end-to-end supply chain network. Specifically, the company wanted to quantify the impact of an optimized mixing center in Texas for its North American production and demand network.


The existing distribution network consisted of Texas distribution centers (DCs) receiving finished products from Mexico manufacturing facilities and shipping on to other U.S. DC locations. U.S.-based manufacturing was shipped directly to designated DCs based more on product type rather than alignment with the end customer, due to the company’s history of growth through acquisition. Company leaders wanted to optimize the network to identify the best go-forward distribution strategy to minimize cost and maintain or improve customer service levels.
The LLamasoft optimization validated the value of a Texas mixing center, and recommended a centralized distribution strategy as opposed to regionally-defined distribution. Several cost-savings areas were analyzed in order to arrive at this solution:
Visualizing demand: The project began by building and validating a baseline model to represent the existing network structure and flow, and then evaluated multiple potential network scenarios to determine the optimal go-forward solution. Greenfield analysis was used to establish a geographic center of demand and visualize where its products were coming from and how they were being consolidated.
Shipment consolidation: Another consideration was whether the company could shorten customer lead times and distance in order to reduce service time. The optimization showed significant opportunity for reduction in delivery times by simply consolidating customer shipments and shortening lead times for all existing DCs.
Facility sizing: The network optimization considered total throughput for each of the U.S. DCs in order to determine whether closing a DC or DC consolidation and defined regional distribution strategy for flow of products from the Mexico assembly locations would produce the best result. The model showed that by allowing more product to flow from the Texas DCs directly to customers would allow for faster service times as well as eliminate potential capital expense and drive additional cost savings.
Freight spend: The team also used optimization to evaluate the company’s LTL (less-than-truckload) and TL (truckload) spend. Scenarios were used to create a set of sensitivity analyses of TL/LTL utilization thresholds. The analysis showed an opportunity to reduce overall spend by consolidating shipments to truckload in order to significantly reduce LTL shipments and overall freight in the optimized network.


Using LLamasoft modeling technology the company was able to make data-backed decisions to reduce overall distribution cost and customer lead time. The analysis showed that by consolidating Texas DCs into one cross-border mixing center and moving away from regionally-focused DCs in favor of a centralized distribution strategy, the company could achieve double-digit savings and service improvements with no facility additions:
• Reduce annual distribution spend by 14 percent just by optimizing distribution strategy
• Significantly reduce service/delivery time for customer shipments through load consolidation
• Identify shipment consolidation strategy to increase truckload shipments and reduce LTL spend

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