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Process Mining vs Task Mining

Lari Numminen

March 2, 2023

In this article we summarize the key differences between process mining and task mining software.

What is process mining?

Process mining is a powerful process mapping tool used for end-to-end process analysis and optimization. It uses data from event logs that are available in IT systems. Based on that data, it builds the as-is process and then compares it to the "desired" process. By doing this conformance checking, companies can find process deviations and thus improvement opportunities.

Typical process mining use cases:

Process mining can be used in many different fields for various purposes but here are some of the more popular use cases.

  • Auditing & compliance
  • Order management
  • Purchase-to-pay
  • Order-to-cash
  • Lead-to-order
  • Logistics

What is task mining?

Task mining is another process mapping tool focused on task optimization typically on desktops or workstations. Much like process discovery, it monitors the digital traces of the users. Using character recognition, natural language processing, and other tools, it analyzes the data gathered and finds patterns that could be interpreted as improvement opportunities.

Typical task mining use cases:

  • Data entry
  • Invoicing
  • Reporting
  • Reconciliation
  • Customer service

What's the difference between process mining and task mining?

In simple terms, process mining involves the analysis of business processes based on IT system event log data while task mining involves the analysis of workflow tasks from user interface interactions. In practice, process mining and task mining are both closely related aspects of process intelligence software that differ in the way data is collected, the scope of data analysis and the end goal of data analysis.

Difference 1: How the data is collected

Process mining vs task mining visual comparison

Process mining typically involves the collection of event logs from IT source systems, such as the enterprise resource planning (ERP) or customer relationship management (CRM) systems used by enterprise businesses. In practice, process mining software is configured to integrate and extract event logs from each different source system, and process mining algoritms are used to merge and visualize processes and process variations in a business intelligence dashboard.

Task mining software usually collects workflow and task activity from the user interface of employees, typically from an agent on a desktop computer or in some cases extensions to web browsers used to access business applications. Some popular task mining solutions use image capture algorithms to automatically record activity data that is then visualized in task and workflow analysis dashboards.

Difference 2: scope of data analysis

Process mining typically involves the analysis of broader defined business processes and workflows at large scale, such as the accounts payable, order-to-cash or customer lifecycle processes. On the other hand, task analysis can go into specific detail into individual tasks within a specific workflow or process, outlining individual steps taken, for example, to create a purchase order.

Difference 3: goal of data analysis

The third clear difference in the scope of process mining and task mining is the end goal for analysis. As a broad generalization task mining may be used in teams and business units with a lot of repetitive work to measure and compare employee performance, while process mining is often used in relation to process re-engineering or operational excellence initiatives.

Bottom line

Ultimately, process mining and task mining are highly related areas of business process management software. Some software vendors may offer process mining and task mining solutions separately as part of the same process intelligence platform, and Workfellow is a new software vendor that offers a hybrid process intelligence solution combining both methods natively into one solution. For more information, book a demo.

Written by

Lari Numminen

Chief Marketing Fellow