Using Transportation Optimization to Evaluate Dedicated Fleet and LTL Networks
A major third-party provider of temperature-controlled warehousing in the United States was relying on a network of LTL carriers to manage the last leg of its supply chain, from cold storage facilities to end customers. Facing continued expansion in a highly competitive marketplace, the provider wanted to test the impact of using a dedicated fleet to replace its LTL delivery network to help lower costs. With stringent end-user service constraints, accurate vehicle route and cost-to-serve modeling was of the utmost importance in analyzing any possible network change, however the company did not have the technical skills needed to perform such a complicated task.
The company turned to LLamasoft® software and modeling expertise to tackle the challenge. LLamasoft’s combined network optimization, simulation and transportation optimization program, Transportation Guru®, was used to model the entire delivery network including all user-defined service constraints. By generating potential itineraries for over 1,800 delivery destinations, Transportation Guru made it easy to evaluate the cost-of-service differences between LTL carriers and dedicated fleet service on a route-by-route basis. The models also determined the transportation assets needed for each scenario and allowed the company to simulate routing strategies to predict actual costs and service levels. With these models in hand the company was able to make rational decisions about the nature of its future delivery network.
The models built using Transportation Guru indicated that in many cases dedicated fleet services could provide a more economical solution than using LTL carriers. With the analysis provided by LLamasoft, the company created a hybrid solution, using dedicated fleet service for most delivery needs, while maintaining a smaller LTL network to handle routes too expensive to be served by fleet services. The company calculates a potential freight savings of greater than 10 percent per year from the existing network, with additional potential savings to be realized as the company expands.