Simulation Tools For Supply Chain: Forecasting Warehouse Space and Optimizing Freight Spend
Clarkston Consulting recently partnered with a client on a project that required use of simulation tools for supply chain and operations. The client is a leading global medical device manufacturer with a mission to deliver high quality solutions and innovation for advancing eye surgery and improving the vision of patients in more than 115 countries.
Clarkston advanced the maturity of the client’s forecasting capabilities through the development of warehouse and freight modeling tools. These tools replaced a manual, qualitative process for strategic planning, annual budgeting and 3PL negotiations and monitoring. The effort involved defining and aligning on business impact and requirements, success criteria, and data pipelines for advanced analytics and reporting.
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The team developed two tools. The first was a simulator tool that forecasts required warehouse space based on the inventory plan against current company-owned and contracted capacity. This simulator enabled analysts to update storage location configurations and add new facilities as the company grows. The second was a freight spend optimization model, which allowed the supply chain team to choose the optimal mix of transportation modes and supply cadence based on total cost and demand signals for shipments across their worldwide network.
The primary objectives for the team on this project included robust warehousing planning and freight spend optimization modeling capabilities, while deriving insights to recommend process improvements to generate significant savings for the company while utilizing simulation tools for supply chain. This resulted in the team building two analytical models to forecast warehousing space and optimize freight spend with simulation tools for supply chain. The team also designed a flexible architecture to add new locations, products, and grow with new acquisitions and portfolio expansions.
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The key benefit of this project was that this provided greater budgeting accuracy and efficiency for the supply chain logistics function within the organization. It also minimized freight spending through balancing shipment frequency and the optimal mode of transportation.
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Contributions by Dimitar Kunev
