Supply Chain Network Design (SCND) is a potent tool for enhancing business operations. This article delves into the integration of simulation techniques into optimization, the construction of a stochastic optimization model, and the creation of a more resilient supply chain model.
Optimization and Simulation: The Twin Pillars of SCND
SCND is primarily driven by optimization, which accounts for over 90% of all work done by SCND teams. It is a versatile tool for resolving a myriad of supply chain issues. However, it has its limitations. Simulation techniques can bridge these gaps, providing a comprehensive view of a company’s supply chain.
Demand: The Core of SCND
The initial step in SCND involves converting business rules into data inputs such as demand, products, customers, sites, shipment rules, production details, and various constraints. Demand assumptions are central to this process due to their unpredictable nature.
Building a Resilient Supply Chain Model
The SCND team’s primary objective is to construct a baseline model that mirrors the current state of the business. The team then iteratively answers stakeholders’ questions about how the network will respond to various changes.
Stochastic Optimization: A Superior Approach to Demand Modelling
Stochastic optimization, which involves multiple time series demand input, can yield significantly different results compared to classic optimization. This article illustrates this difference using the network of a company with four manufacturing plants servicing demand in every mainland US state.
The Value of Stochastic Optimization
Stochastic optimization provides a more resilient, realistic, and robust supply chain strategy. It equips the supply chain leadership team with all the necessary information to make long-term strategic decisions regarding sourcing. It allows them to understand the cost effect of optimizing the network to minimize sourcing switches and balance that against the need to deal with flexing crewing, storage space, and carrier capacity.
In the changing world of supply chain management, stochastic optimization is a way to build a more resilient, realistic, and robust supply chain strategy.
