Process Mining and Business Process Simulation: The power duo for secure decision making

What if we automated a production process step? What if we doubled the workforce for transport? What if...? Such "what-if" scenarios can be tested in a virtual environment using Business Process Simulation (BPS) to make clear, data-driven decisions. However, the accuracy of such simulations depends heavily on the quality of the underlying data. This is where Process Mining comes into play.

By combining Process Mining and Business Process Simulation, organizations can make targeted improvements to business processes more efficiently. Let’s explore these two complementary disciplines in detail.

What is Business Process Simulation?

Business Process Simulation (BPS) involves creating a digital model—often referred to as a digital twin—of real-world processes. This simulation allows companies to test and visualize different scenarios, assessing their impact on efficiency, resource utilization, or other key performance indicators before implementing changes.

Traditional BPS: Challenges

Historically, BPS models were built manually through extensive documentation, stopwatches, and expert interviews. This approach was:

• Time-consuming: Requiring significant manual effort.
• Subjective: Prone to biases from human input.
• Limited: Unable to effectively model complex processes that span multiple departments, systems, or locations.

Modern BPS: Enhanced with Process Mining

Today, BPS benefits significantly from Process Mining, which creates an objective and data-driven foundation for simulation. By analyzing real data from IT systems, Process Mining eliminates biases and ensures simulations are as close to reality as possible.

What is Process Mining?

Process Mining is a technology that systematically analyzes and evaluates business processes based on data extracted from IT systems. This data is objective, comprehensive, and includes all processes across various programs and systems.

Key Features of Process Mining:

• Digital Twin Creation: A virtual representation of real business processes.
• Data-Driven Insights: Visualizations and key metrics to discover actual workflows.
• Optimization Opportunities: Identifies inefficiencies and deviations from ideal processes, enabling targeted improvements.

With its focus on understanding and optimizing current workflows, Process Mining is the foundation for continuous process improvement.

What is the difference between Process Mining and BPS?

Process mining generally has a backward-looking perspective, as historical data is extracted from the IT systems in order to understand the current as-is processes. The aim is to uncover inefficiencies and optimization potential.

Business process simulation, on the contrary, has a future-oriented perspective, as different future scenarios and their effects are simulated based on the current processes. The aim of these "what-if scenarios" is to make decisions more easily and reliably.

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How Do Process Mining and BPS Work Together?

When combined, Process Mining and BPS form a powerful duo:

1. Data Foundation with Process Mining: Process Mining extracts and analyzes historical process data to create a digital twin.
2. Scenario Testing with BPS: Business Process Simulation uses this digital twin to model, test, and validate various "what-if" scenarios.

By aligning these disciplines, companies gain both a clear understanding of current operations and the ability to predict and optimize future outcomes. This combination enhances decision-making, reduces risks, and drives more efficient process improvements.

Unlocking the Potential of "What-If" Scenarios

Imagine knowing exactly how a process change—whether due to external influences or strategic adjustments—would impact your organization. With the combination of Process Mining and BPS, this is no longer a dream.