Process Mining Definition | What is Process Mining

Learn what process mining is, different types, use cases, tools, and how process mining is different from data mining.

What is Process Mining?

Process mining is the deep-dive analysis, discovery, monitoring, and improvement of as-is processes, revealing the efficiencies your business benefits from. It takes all of the process data within a corporation’s walls and mines it to understand potential improvement, focusing on finding better, more efficient tracks in operations.

The goal is to find touchless process paths that require minimal human intervention. This permits businesses to boost speed and accuracy, permitting teams to focus on doing what they do best as efficiently as achievable. 

Process Mining Use Cases

Process mining strategies have been used to improve process flows across diverse industries. Here are some important use cases of process mining:

  • Education: Process mining can help determine useful course curriculums by observing and considering student performance and manners, such as how much time a student devours viewing class materials. 
  • Finance: Financial organizations have used process mining software to enhance inter-organizational processes, audit accounts, increase income, and broaden their customer base. 
  • Public works: Process mining has been used to facilitate the invoice process for public works projects, which affect different stakeholders, such as building companies, cleaning industries, and environmental departments.
  • Software Development: Since engineering strategies are typically messy, process mining can help recognize a written process. It can also help IT directors observe the process, confirming that the system operates as expected. 
  • Healthcare: Process mining provides suggestions for relieving the treatment processing time of patients. 
  • E-commerce can provide insight into buyer behaviors and provide concrete suggestions to increase sales. 
  • Manufacturing: Process mining can help assign the appropriate resources depending on the case—i.e., product—attributes, allowing managers to transform their business operations. Accordingly, they can gain insight into production times and reallocate resources, such as storage space, machines, or workers. 

What Are The Different Types Of Process Mining?

Wil van der Aalst, from RWTH Aachen University, Dutch computer scientist, and educator, is credited with much of the academic analysis about process mining. His research and the manifesto mentioned above describe three types of process mining: discovery, conformance, and enhancement. 

1. Discovery

Process discovery utilizes event log data to build a process model without external influence. 

Under this category, no previous process ideals would exist to disclose the development of a new process model. This type of process mining is the most widely assumed. 

2. Conformance

Conformance checking verifies if the planned process model is imaged in practice. This type of process mining resembles a process description of a current process model based on its event log data, determining any variations from the planned model.

 3. Enhancement

This process mining has also been directed to extension, corporate mining, or performance mining. 

In this class of process mining, extra data is used to improve an existing process model. For example, conformance checking can help 

identify bottlenecks within a process model, permitting managers to optimize existing processes.

Process Mining Vs. Data Mining

Business Process Management Process mining sits at the junction of business process management (BPM) and data mining. While process mining and data mining both perform with data, the extent of each dataset varies. Process mining especially uses event log data to develop process models that can locate, resemble, or improve a given process.

The scope of data mining is much more overall, and it opens to a variety of data sets. It is used to monitor and anticipate behaviors, having applications in client churn, scam detection, and market basket research, to name a few. 

Process mining takes a more data-driven approach to BPM, historically managed more manually. BPM generally contains data more informally via workshops and discussions and then uses software to verify that workflow as a strategy map.

Since the data that reports these process maps is more qualitative, process mining brings a better quantitative method to a process problem, describing the basic process via event data. 

Process Mining Tools

You can use the method on any process if the relevant data is stored in an available IT system. Nowadays, that represents any digitized process.

 Modern Process Mining tools do better than fantasize about your process. 

1. QPR Process Analyzer

QPR has a range of tools based on process mining to streamline business operations.

QPR Process Analyzer is one such product with a fairly comprehensive set of features. QPR is trusted by Nokia and Occidental, along with other large companies. 

2. Celonis

Celonis is the multinational leader in enactment management. Powered by its process mining core, 

Celonis has developed from its openings as a Process Mining corporation into a performance management missionary, enabling businesses to open enactment ability and accomplish at full potential. Celonis offers progressive technology in data undertaking,  condensing real-time process data.


ARIS Process Mining is one of the earlier retail Process Mining tools and offers standard process discovery functions, better checking, highly customizable dashboards, and automated root cause research.

4. Minit

With its first version cast in 2015, Minit has created a strong Process Mining tool with advanced process enhancement credentials.

5. Prodiscovery

Puzzle Data’s ProDiscovery key comprises a puzzle library with cultured widgets for operation discovery, statistical studies, social grids, and managerial graphs. South Korea’s first and only Process Mining tool is created to process extensive datasets.

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