Term Process Mining

Process Mining is a group of techniques that analyze the behavior of business processes. It also contains specialized data mining algorithms and extracts information from any system event logs. These event logs are then used to analyze, understand, monitor, and optimize the business processes. Process mining applies data science to discover, validate and improve workflows. By combining data mining and process analytics, organizations can mine log data from their information systems to understand the performance of their processes, revealing bottlenecks and other areas of improvement.

History of Process Mining

The first term “Process Mining” appeared in a research proposal by Wil van der Aalst in 1998. In the late 1990s, while studying workflow and workflow management at the Eindhoven University of Technology in the Netherlands, Mr. Aalst realized that existing methods were for understanding current business processes. Apart from the mainstream techniques of process discovery and conformance checking, process mining branched out into multiple areas leading to the discovery and development of “Performance analysis”, “Decision mining” and “Organizational mining” in the year 2005 and 2006 respectively. In the late year 2007s, companies were established and developed for process mining tools. As of the year 2018, more than 30 process mining tools are published for commercial use.

What is Process Mining?

There are five main stages in every process of mining. Understand the process, monitor the process, improve the process, redesign the process and execute the best design process.

What can you do with process mining tools?

Normally process mining tools can be used to train and educate people, design or redesign processes, document all the detailed processes, discover the automatable repetitive areas, improve the process area, and monitor the process.

Requirements of process mining tools

In every process, only three main things are necessary and these are “Case ID”,” Activity Name” and” Timestamp.” These three elements allow you to take a process perspective on the data. The case ID determines the scope of the process. The activity names determine the steps in your process map and their granularity. Timestamps determine where the case ids were performed.


Ideal processes are also known as “Happy Path” which can only capture the main steps in a few details.

Process mining reveals the real deviations, exceptions, bottlenecks, and workflow inefficiencies.

Facts and Assumptions

The “Textbook” process means most of the common processes are visualized first. After that people think they detect some anomalies and inefficient process variants later on. In reality, there are a lot of unusual process paths or defects and hidden areas are found.

Process Mining Benefits

  • Enable data-driven decision making
  • Reduce time and cost
  • Transparency to business management
  • Measure performance accurately
  • Standardize and improve the process
  • Easily noticeable the pain points
  • Analyze data faster and identify non-compliant processes
  • Detect customer behavior and improve customer experience