Is your enterprise capitalizing on this year’s biggest trends? Evaluate your competitive edge with the 2022 Virtusa Trend Almanac. View report

Digital Themes

Process Mining

What is process mining?

One of the data science and process management techniques, process mining supports operational process analysis based on event logs to derive actionable insights. Process mining techniques utilize event data to improve these processes by identifying the execution path to address performance and compliance problems. 

It is interesting to note that process mining is often identified as a field related to data science. On the contrary, it is a connecting link between data science and process science. The scope of process mining focuses on transforming event logs into a meaningful representation of the process. 

An event log is a primary input for the process mining that analyses the event from a specific lens. Each event log contains a case ID, an activity, and a timestamp to answer various process-related questions. A process mining technique has three categories, namely:

  • Process discovery transforms the event log into a process model.  As mentioned above, an event log can be an entry in an organization’s data storage system that records activities along with the timestamps. 
  • Conformance checking compares an event log for discrepancies with an existing process model. 
  • Performance analysis is used when a model has certain additional performance information. This step aims to improve the performance of the existing model against specific process performance measures. 

In business, the process mining technique is usually implemented when the quality of existing documentation is questionable. Or in other words, when one cannot obtain any formal description of the process by any different approach. With process mining, organizations can identify the root causes of bottlenecks in real-time to optimize their resources and scale with total productivity.

Many industries have embraced process mining to transform their operations to be more proactive. A few use cases or applications of process mining methodology in the business world are listed below:

  • Manufacturing and distribution: Process mining can help avoid major disruptions or delays when making products and getting them to market. 

  • Sales: With process mining, one can closely examine sales cycles to help companies with better resource allocation and process enhancements. To remove any deviation and inefficiency in the sales cycle, one can monitor strategic metrics like days to close that may last for many months with process mining.

  • E-commerce: Process mining helps online stores better understand their customers, which in turn improves their customer experience and sales. An e-commerce company can focus on critical metrics such as the relationship between web pages, order-to-cash, and time-to-issue resolution.

  • Healthcare: Process mining improves the efficiency of patient encounters by enhancing costs associated with interdepartmental workflows and ensuring shorter wait times within a healthcare setting, for example. 
Related content