Dynamic Simulation
This Dynamic Simulation exercise aimed to meet following Compelling
Business Needs:
- Right-Size Installed Capacity & Sourcing locations
- Reinvent Wholesaler-Retails distribution network
We developed a network model and used ALX Network Optimization (NO) engine to obtain an optimal network structure. We provided full flexibility to model in term of intersite (Plant to DCs, and between DCs), and direct customer shipping (DC to Wholesalers) connectivity, so that NO engine comes up with optimal network design to minimize transportation and warehousing costs. The results revealed that new recommended design has a significant saving vs. current network from Intersite shipping.
Network Optimization
For building a network optimization model of an FMCG company in Asia, we applied anyLogistix supply chain software. The combination of network optimization and dynamic simulation capabilities in one package would allow us to measure every aspect of supply chain performance and would provide more accurate and transparent decision making. A powerful set of in-package experiments would save time when designing and testing new policies.
The final network design and policies, compared to the current design, showed better performance in terms of service level and cost saving. The designed structure was proposed to the executives, received positive feedback, and was advised for implementation.
Inside 4-Walls DC Simulation
In the new supply chain design, the company has many DCs to fulfil customers in Asia. Therefore, a dynamic sourcing logic is designed to assign orders to one of DCs. MRP replenishment policy is modelled to calculate inventory replenishment. Using ALX extension, we built an agent-based simulation model to address following problem statements:
- What will be the business target outcome of proposed sourcing and inventory strategies?
- What will be the robustness of supply chain to the failure of certain assumption?