When Not To Use Simulation

Date: 3/17/2017
Author: Descreye Solutions

Discrete-event simulation software can be an incredibly powerful tool for learning about the dynamic nature of complex systems. However, in many cases it is not the right tool for an analysis. The following are four instances where discrete-event simulation is unlikely to be helpful, but instead could end up being a distraction in achieving the insight that is necessary to inform the decision making process.

1. The answer is obvious

Often people want to create a simulation to justify a decision or to make a case for an improvement. However, if everyone agrees with the solution, then it is most likely not necessary to provide the detailed analysis that is inherent in a simulation model. Often simpler tools like Excel or flowcharts can be a better communication medium for those discussions. Simulation is most useful in cases where the answer is complicated or non-intuitive. In those cases simulation can help inform the discussion and in doing so add value.

2. The answer doesn't matter

This scenario is like the first. If a decision has already been made, then there is little value in creating a simulation. Simulations help inform the decision-making process. Once a decision is made then a simulation can be repurposed to inform other decisions, but little value is added if no more decisions can be made using the model.

3. There isn't a goal for the simulation model

Simulating for the sake of simulating is most often a waste of time. Without a goal for a simulation it is necessary to create an overly complicated model to anticipate any possible what-if scenarios. If a simulation has a focused goal, then it is possible to limit the scope of the model to those things that influence the outcome of the goal. Without a well-defined scope a simulation model becomes both unmanageable and unmaintainable.

4. The data doesn't exist

The popular saying is garbage in, garbage out. However, with simulation it is often even more risky. Simulations give the appearance of data and thorough analysis. This can make the saying with regards to simulation be more accurately told as; garbage in, garbage being used to make crucial decisions... This is obviously not desired. If there is not reliable data, then either a model should not be made or it should be highly qualified when presented to anybody.

When creating simulations, it is important to weigh the cost of the simulation (time, accuracy, etc.) with the anticipated benefit. If it does not seem justified, then it is useful to determine what justifiable tools can be used to produce the required analysis.

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