Simulation is a cheap and safe method to test process adaptations before they are actually implemented. However, creating an appropriate simulation model is very time-consuming and requires a lot of research. With Process Mining, realistic simulation models can be generated quickly and easily with derived rather than estimated data.
What does simulation of business processes mean?
Simulations are used to carry out experiments whose results cannot be calculated because the systems or processes to be simulated are highly complex and dynamic.
If a process change is too dangerous or cost-intensive to actually be implemented, or is simply not possible due to certain circumstances, a simulation makes sense. Simulating makes it possible to evaluate the effects of a process change without affecting ongoing business operations. This means that you can also evaluate various possible adjustments so that the process is ultimately implemented with the most beneficial changes.
To be able to simulate a system or a process, an abstract representation in the form of a model is required. This model must reflect the course of the process and must also be enriched with simulation-relevant parameters such as times, resources, costs, and so on.
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Easily create realistic simulation models
For the simulation model, you need information such as the process flow, required resources (employees), different process times, and the costs for materials and execution of the process steps. In a conventional simulation, the simulation model is still created manually. In addition, all these parameters are usually recorded manually as well, e.g. through employee surveys, observations or estimations. Only in a few cases is this information taken directly from the IT systems involved, although the system data is very suitable for such a purpose.
But if you simulate on the basis of Process Mining, you can use the process model derived from the system data as the basis for a simulation very close to the real process. Once you have created the basis for a simulation model, you must enrich it with the parameters already mentioned. These parameters and their actual distributions are also derived from the real process data. Thus your process model is based on real data instead of subjective assumptions. This enables you to obtain realistic results for well-founded decisions. In addition, the creation of the simulation model with Process Mining can be simplified to such an extent that simulation also becomes interesting for operative and short-term decisions.
Discover how Process Mining tools like LANA simplify the simulation of your business processes with extracted system data. Talk to our experts today.