Overview: Simulation, applied to discovered process models and using historical data, offers a cost-effective method for evaluating proposed process improvement plans. Instead of requiring an expensive, time-consuming and error-prone process mapping project, the discovery phase delivers a BPMN (Business Process Model and Notation) process model whose behavior, when simulated, reflects statistically what has actually happened according to the historical system logs.Simulation as proposed here, utilizes a software application that facilitates the iterative investigation of a process and alternative improvement designs. We employ a synthesis of three particular techniques: BPMN (Business Process Modeling and Notation) models, analytic methods and optimization algorithms.
Adjusting a simulation model to reflect proposed changes, requires an understanding of the basic parameters that affect the outcome of the simulation. These parameters are initially determined by the historical data using data mining algorithms. Subsequent modification of the parameters is performed by a combination of optimization algorithms and analyst guidance. Key parameters include the following:
This webinar describes the execution semantics of the BPMN model, the use of simulation parameters to evaluate proposed improvements and visual reporting techniques for exploring what has happened and why.
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