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Business Process Analysis using Process Simulation

Business process analysis through process simulation can be described is as a tool for analyzing business processes even before they are put to action. One can use it to assess the performance and dynamic behavior of processes over time, in reaction to changes occurring in certain environment or system parameters. It empowers stakeholders and business analysts to evaluate and refine prospective processes along with an option to choose among alternatives.

Benefits of simulation

Process simulation provides information about how a process may perform over time, by using hypothetical and simulated data and metrics. It helps to identify cost-intensive activities hidden in the overall process flow, even when the data is not available at the desired granularity. This business process analysis activity also provides details about the duration of the processes, as well as consumed resources which helps in testing and comparing process alternatives.

Simulating business processes not only provides a preview into how your new processes will perform, it also offers the opportunity to validate changes to existing processes and highlights possible errors, queues and bottlenecks at an early stage without impacting the business.

The individual running the simulation can make assumptions about frequency of process instances, probabilities related at each decision point along the way and the timing and cost involved in executing each task. Based on these, useful insights can be derived under scenarios such as, “If I initiate 100 onboarding requests, how many of them will be approved, how many will be in backlog and where will the bottleneck exist?”

Simulation and IBM BPM

business-process-analysis-using-process-simulation
IBM BPM provides a simulation capability built into the Process Designer which is called the Optimizer. The Optimizer can be used to examine how a process may perform by using simulated executions with hypothetical data. In addition, the Optimizer can be used with actual data collected over time from runs of the processes in production. The latter is part of optimization which pinpoints areas in the process models where one can make design changes to help streamline execution and, thus, improve performance.

IBM BPM imitates (internally) execution of the steps in the process and calculates timings and other numerical data. After the simulation has ended, the results are shown to the user in graphs, charts and tables.

Setting up a Business Process Simulation

Let’s have a closer look at the steps to run a business process simulation/optimization using IBM BPM Optimizer.

Configuring Prerequisites:

The configuration requirements vary for simulation and optimization. For simulation, the process starts with setting up simulation profiles, configuring simulation properties for teams and building Simulation Analysis Scenarios which are utilized by Optimizer to run a simulation process.

Optimization requires setting up Autotracking to track performance data and send it to the Performance Data Warehouse and creating historical analysis scenarios.

Running simulations, historical analysis and comparisons:

The scenarios generated in the above step can be run in Optimizer or compared with each other. Live reports are generated after the simulation is run. The Visualization modes can be changed using the Heat-map Settings view provided in the designer. Results are usually gathered and saved per scenario and simulation run for analysis purposes. The selection of results to be gathered depends on the analysis goals.

Reviewing results:

After enough results are gathered IBPM Optimizer presents analysis results in different ways: Heat maps, Live Reports, Recommendations and Smart Start hotspots. The results of business process simulation comprise quantitative, time-based and cost-related information about process execution and resource usage, e.g. waiting times, throughput times, completed process instances, resource utilization or cost per instance. This data can be aggregated for the different model objects but also given per instance. For the analysis it can be interesting to evaluate the data at a certain point in time, e.g. the number of completed process instances at the end of the simulation time, or over time.

Detailed steps and information on how to setup a simulation environment can be found here. We hope this post helps you improve your business process. Learn about our BPM consulting services and contact us to see how we can help you.

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  1. Pingback: Business Process Life-cycle | Princeton Blue

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