Wil M.P. van der Aalst
Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, The Netherlands w.m.p.v.d.aalst@tue.nl Abstract. Computer simulation attempts to “mimic” real-life or hypothetical behavior on a computer to see how processes or systems can be improved and to predict their performance under different circumstances. Simulation has been successfully applied in many disciplines and is considered to be a relevant and highly applicable tool in Business Process Management (BPM). Unfortunately, in reality the use of simulation is limited. Few organizations actively use simulation. Even organizations that purchase simulation software (stand-alone or embedded in some BPM suite), typically fail to use it continuously over an extended period. This keynote paper highlights some of the problems causing the limited adoption of simulation. For example, simulation models tend to oversimplify the modeling of people working part-time on a process. Also simulation studies typically focus on the steady-state behavior of business processes while managers are more interested in short-term results (a “fast forward button” into the future) for operational decision making. This paper will point out innovative simulation approaches leveraging on recent breakthroughs in process mining.
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Limitations of Traditional Simulation Approaches
Simulation was one of the first applications of computers. The term “Monte Carlo simulation” was first coined in the Manhattan Project during World War II, because of the similarity of statistical simulation to games of chance played in the Monte Carlo Casino. This illustrates that that already in the 1940s people were using computers to simulate processes (in this case to investigate the effects of nuclear explosions). Later Monte Carlo methods were used in all kinds of other domains ranging from finance and telecommunications to games and workflow
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