Business Process Simulation & Analysis

Why simulating BPMN 2.0 processes?

The aim of business process simulation is the improvement of process characteristics like quality, performance and/or resource utilization. Therefore ideally known processes are measured and key performance indicators are calculated. The results of the simulation experiments are presented in diagrams. By comparing the results of different process configurations, it's easy to determine the best configuration to archive the requested target.

How to simulate BPMN 2.0 processes?

You need to enhance your models with some additional parameter information. First of all, the average duration of activities or the effective dates of events have to be assigned to the process diagram elements. For mapping the realistic variability of such  parameters, pseudo-random-numbers are used, which are generated by stochastic distributions. Secondly, you ave to ensure that all exclusive and inclusive gateways have determinable conditions and/or probabilities. After entering all relevant parameters you can start the simulation experiment and afterwards analyze the results. Since simulation is based on stochastic, you need to execute various simulation experiments.

IYOPRO also offers some advanced simulation concepts:

• You can determine resource utilization and bottlenecks, if you link your processes with entities from organization diagram models.
• You can calculate activity based costing of your processes and products.

• You can use Python scripts to access simulation context data for complex computations

Content

IYOPRO Premium offers a simulation tool kit for substantial business process analysis. It has the capability of stochastic, discrete event driven simulation of processes together with the ability to analyze the dynamic behavior of business processes. It offers forecast indicators to estimate the potential run-time of processes in order to consider timescale, resources and costs to determine the optimal process by experimenting with different options.

• General Simulation Properties - Some general settings you need to execute simulation experiments
• Stochastic / Random distributions - Why and how to use stochastics. Explanation of available distributions in IYOPRO.
• Assigning Inter-arrival Times / Durations - Explains how to use events and activities in simulation experiments
• Element settings - Offers a complete list of available options for your model elements
• Gateway Decision Making - Explains how simulation chooses the next element after an exclusive or inclusive gateway
• Process Variables  - Explains how to model implicit knowledge in processes, e.g. for decision making at gateways
• Resources  - How to analyze resource utilization e.g. for bottleneck analysis.
• Report - How to analyze experiment results. This chapter explains the large number of provided statistics.
• Simulation Tutorial - Learn how to simulate BPMN 2.0 models step by step with a lot of example models