Using Supply chain simulation and optimisation techniques to better equip your decision making.
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Thousands of companies around the globe now use supply chain simulation and optimization methods. Interest has risen significantly over recent years no doubt as a result of increased awareness of best practice coupled with a greater footprint from (and increased numbers of) software resellers. Simulation whilst not necessarily new includes concepts that help optimize processes and delivery structures helping organizations better manage risk and provide a degree of robustness to long term planning.
The use of simulation techniques can be wide ranging. However they are often commonly applied to logistics or distribution processes. For example, distribution centers commonly have their location and inventory make up simulated to better understand optimal storage locations, storage volumes and logistics routes.
Complex simulation and optimization scenarios can be lengthy to process and the results often require further review or discussion (the results of simulation are not commonly carried immediately through to an execution situation.) However there are some exceptions, with some stock modeling solutions being very well equipped to take results directly into operation and planning or procurement processes.
Simulation can be used both as a development or problem-solving tool. Supply chains, network planners, transportation planners, inventory optimizers and factory scheduling can use simulation techniques that incorporate best practice statistical methods including constraint-based rules to be better prepared for decision making in order to generate the most appropriate business model.
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A key challenge in simulation is that there can be many variables to track or calculate. Many organizations use supply chain simulation techniques to better understand the financial impact of change – whilst other organizations will be interested in what customer service levels can be maintained when changes are made to their supply chain or distribution network (e.g. reduced inventory levels or fewer distribution centers). Supply chain simulation helps via a “if I tweak that input I get that output” approach and therefore can often be an iterative process.
The more complex the organization, consider those with large global supply chain, numerous distribution centers, large volumes of product/parts, the more challenging the simulation. However optimization tools often excel in these situations as capability for data processing can help organizations better understand the risks that their organization face in establishing their supply chain. In such large supply chains, simulation allows modeling to be completed more quickly and accurately achieving faster buy in than standard empirical testing.
Simulations are usually time based and when running a simulation supply chain analysts can observe the behavior, and performance of the supply chain system over a period of time or as the inputs or variables change. In particular they can play close attention to cost and service levels.
Given this these tools are often applied at the outset of projects that have particularly long life cycles where an understanding of long term cost/service can be a key decision factor in whether such projects go ahead in the first place.
Used in this way, simulation and optimization can be a great tool in identifying bottlenecks that may affect performance. However, whilst this can be extremely useful , analysts must still maintain sufficient understanding of their network and those factors that can influence the performance of the system in order that it can be re-configured to deliver the best approach.