Case Study: Supply Chain Network Optimization for a Building Materials Company in the US to Increase Service Levels and Cut Costs

Background

An industry-leading building materials company with multi-million-dollar annual revenues wanted to identify the ideal location for a new distribution center in order to increase its service levels. The client’s supply chain was responsible for the transportation of over 100 thousand tons of product and over 300 thousand shipments annually throughout North America. This was accomplished by three primary distribution centers throughout the US using various modes of transportation, including Parcel, LTL, and TL.

The Challenge

Customers have grown accustomed to fast, low-cost, and efficient shipping options. In 2022, 42% of shoppers expected a 2-day shipping option for every online purchase they made. The client realized this was a business area that needed improvement and contacted Establish to identify a solution. Before Establish, the client could service just 55% of its North American customers in 1-2 days. The challenge was to determine the optimal four distribution center network strategy that could service 95% or more of its North American customers within 1-2 days while maintaining or reducing transportation costs. In addition, the client also wanted to know the optimal five and six distribution center network strategy for long-term planning.

The Approach

We first created a baseline model that accurately depicted the operational costs associated with the client’s network. The baseline model was used as a benchmark for future scenarios and was critical to the project’s success. The baseline was built using 12 months of client data, including sales, purchase, transportation, inventory, and warehousing data. The baseline model revealed key “quick wins” that could be implemented immediately, mainly driven by optimizing the current customer demand for new lanes based on reduced mileage and transportation costs. This “quick win” model was referred to as the “optimized baseline” model. Once the baseline model was complete, the focus was shifted to future network optimization. A center of gravity analysis was performed to determine the ideal distribution locations based on the client’s supply and demand. This can be run for single or multiple locations; for this client, we performed analyses for four, five, and six distribution center networks. In addition to the center of gravity analysis, qualitative factors from the client were added to the model to determine the specific locations to be considered. Once the locations were chosen, parameters were added to Assign, Establish’s proprietary network optimization tool, which ran multiple scenario variations and calculated transportation costs, customer service levels, warehousing costs, and transportation costs.

The Outcome

The results yielded multiple vital takeaways and insights for the client. First, the model determined that the existing three distribution center network could service 80% of its customers within 1-2 days by optimizing the current shipment lanes to the optimal distribution center. Secondly, the model determined the location of the optimal fourth distribution center location that was capable of servicing over 97% of customer orders within 1-2 days, which had an overall cost comparable to the baseline. Lastly, the model recommended a four and five distribution network for a long-term view of the network strategy.