Simulation lets you see the impact of change. You can quickly make changes to your model to test out your ideas without disrupting your real system. With simulation you make your mistakes in the model, and not in your business.
Changes may not always produce the desired or expected results. Complex systems are often counterintuitive in their behavior and investments that address a problem in one area of the system may just move the problem to another area without improving the overall performance of the system. Simulation lets you separate the winning ideas from the losing ideas and optimize your business performance. Simulation lets you validate proposed designs and make the best use of your limited capital to focus your resources where they have the most impact on your results.
Simulation brings your ideas to life by providing an animated preview of a proposed change. You can also record and graphically display key performance measures for your system. This helps in not only analyzing proposed changes, but in communicating the benefits of those changes to the stakeholders in the system.
Finally, simulation is the one method that allows you to fully account for variation in your systems and the impact that it has on your overall system performance. Simulation lets you avoid the critical problems created by applying traditional static analysis to try to understand and predict the behavior of a variable and complex dynamic system.
One of the often overlooked aspects in the analysis of a systems performance is the role that randomness plays in determining the behavior of the system. By randomness we mean the idea that things occur within our system with variation from one to the next. Classical examples of randomness include the time between arrival of customers, the time between failures of equipment, or the time it takes to complete some activity.
Let's consider a very simple example where we have entities arrive to a single server for processing. We will assume that entities arrive an average of 10 minutes apart, and have a service time that averages 9 minutes. The entities might be customers arriving to a bank, work pieces arriving to machine, or patients arriving to a doctor's office. From a modeling perspective the basic system can be depicted as shown below.
We would like to study this system and answer the following two basic questions about this system's performance over a long period of time.