Reducing Cost Though Optimal Outbound Goods Flows and Product Allocation
A global food processing and commodities trading corporation wanted to focus on its supply chain in Ireland to optimize the historic flow and reduce transportation and inventory costs. The company ships to 10 Irish ports; after products arrive they are stored in bulk quantities in warehouses and then directly collected by customers. They wanted to reduce these handling costs while still maintaining service levels to customers. In order to do this, they reached out to LLamasoft to help them use optimization to allocate the products to the correct ports for each customer to reduce total movement of goods.
The first step was to use the Supply Chain Guru supply chain design platform to map current flows and optimize for quick wins. The company and LLamasoft first identified a total reduction of €4M, or 24 percent of total costs. However, the solution was not executable. They quickly realized that not all product and port combinations were allowed and constraints needs to be added to the model to get viable results. With this restriction new challenges arose that required innovative solutions:
Challenge 1: Port-product combinations scenario-matrix – identifying the best choice out of 38 possible port/product combinations. This was difficult because same products could repeat in different ports, but not in others. In order to solve this, 13 “dummy” manufacturing sites were created and collocated with sides at each port for production count constraints.
Challenge 2: Inventory modeling – there was a lack of inventory strategy information available. Inbound inventory was out of scope and therefore the information on where goods were stored as a result of inbound strategy was not provided. To overcome this lack of detail they used weekly inbound and outbound inventory movements to calculate annualized turns. They then used the turns and ‘inventory cost other’ field in Supply Chain Guru to calculate ‘inventory holding cost’ output.
Challenge 3: The company identified some optimized outbound flows that were unrealistic. Although inbound flow optimization was out of scope for this project, there are maximum vessel capacities, which needed to be taken into account. In order to address this, transportation modes and assets were created, identifying which vessel sizes each port could accommodate from each of the dummy manufacturing sites.
By optimizing transportation modes and assets the company was able to save €2.2M or over 14 percent on overall costs and each of its top three customers were able to see at least a 30 percent service distance improvement.