What is Process Mining?

Definition: Process mining is a data-driven technique used to analyze and improve business processes. For this purpose, insights and knowledge are extracted from event logs, which are digital traces of the actions and interactions within a process.

It involves the use of specialized software and algorithms to collect and analyze data about the flow of activities, decisions, and interactions among people and systems within a process. By analyzing these data, process mining can help identify inefficiencies, bottlenecks, and other areas of improvement in a process, as well as evaluate the effectiveness of process changes and interventions.

Process mining is a data-driven technique used to analyze and improve business processes by extracting insights and knowledge from event logs

Benefits of Process Mining

  • Enhanced visibility: By providing a visual representation of the process flow, process mining allows stakeholders to gain a better understanding of how the process works and identify areas that require improvement.
  • Improved compliance: Process mining can help ensure that processes are compliant with regulatory requirements and internal policies by identifying non-compliant activities and areas for improvement.
  • Improved process efficiency: Process mining can identify bottlenecks, inefficiencies, and areas for improvement in business processes, allowing organizations to optimize their operations and reduce costs.
  • Better decision-making: By providing insights into how processes are actually being executed, process mining can help organizations make more informed decisions about how to optimize their operations.
  • Increased agility: Process mining can help organizations identify and respond quickly to changes in their processes or market conditions, enabling them to stay competitive and adapt to new opportunities.

What are the types of Process Mining?

  • Discovery: This type of process mining is used to discover the actual process flow by analyzing event logs or other data sources.
  • Conformance: Conformance process mining is used to compare the actual process flow with the intended or ideal process flow, highlighting areas of non-compliance and deviations from the expected process.
  • Enhancement: Enhancement process mining focuses on identifying areas for process improvement and optimization by analyzing the actual process flow and identifying bottlenecks, inefficiencies, and other areas for improvement.

How does it work?

Here are the key steps involved in the process mining process:

  • Data collection: The first step in process mining is to collect the event logs that contain information about the process. These logs can be obtained from a variety of sources, including enterprise software systems, databases, or IoT devices.
  • Data preprocessing: The event logs are cleaned, filtered, and transformed into a format that can be analyzed by process mining algorithms. This step involves removing irrelevant data, correcting errors, and transforming the data into a standardized format.
  • Process discovery: The process mining algorithm analyzes the event logs to discover the process flow. This involves identifying the start and end points of the process, the sequence of activities performed, and the conditions that determine the flow of the process.
  • Process visualization: The process flow is visualized using process models such as flowcharts, process maps, or Petri nets. This visualization helps stakeholders understand the process flow and identify areas for optimization.
  • Process analysis: The process mining algorithm analyzes the process flow to identify bottlenecks, inefficiencies, and other areas for optimization. This analysis may include statistical analysis, simulation, or predictive modeling.
  • Process optimization: Based on the insights gained from the analysis, the organization can optimize the process by making changes to the process flow, automating certain activities, or improving resource allocation.
  • Monitoring and control: Process mining can also be used to monitor the performance of the process over time and identify deviations from the optimal process flow. This allows organizations to take corrective action and maintain the efficiency of the process.

Used terms

Event Log

A record of events and activities that occur within a process, used as a data source for process mining.

Process Improvement

The act of making changes to a process to optimize its performance, efficiency, and effectiveness.

Process Discovery

The process of discovering the actual process flow by analyzing event logs or other data sources.

Process Analysis

The examination and understanding of a process flow and its related data to identify areas for improvement.

Glossary of Process Mining Terms

Data Mining

The process of discovering patterns and insights from large datasets through statistical and computational techniques.

Big Data

Refers to extremely large and complex datasets that require advanced tools and techniques to process and analyze.


A single instance of a process that can be analyzed and improved through process mining.

Process Excellence

A continuous improvement approach that seeks to achieve the highest level of efficiency, effectiveness, and customer satisfaction in a process.

Business Intelligence

The process of collecting, analyzing, and presenting data to support better decision-making and drive business performance.

Process Transparency

The ability to clearly understand and communicate the steps, actions, and outcomes of a process.

Target Process

The desired or ideal process flow that an organization strives to achieve through process improvement efforts.

Conformance Checking

The process of comparing the actual process flow to the intended or ideal process flow, identifying areas of non-compliance and deviations.

Continuous Improvement

Continuous Improvement is an ongoing process of enhancing products, services, processes, or systems to optimize their efficiency and effectiveness. It involves continually identifying areas for improvement, analyzing them, and implementing solutions to achieve better results.