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:
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: