Process mining

WHAT IS IT?

Process mining is a family of techniques used to analyze event data in order to understand and improve operational business processes. This data-driven approach transforms event log data from corporate IT systems into a meaningful representation (“digital twin”) of the actual business processes. By examining the records of start and end times of activities within a process, it reconstructs the actual flows of these processes to uncover deviations, bottlenecks, and opportunities for optimization. This allows organizations to see how processes are really running, not just how they think they are running. 

There are three main categories of process mining techniques: process discovery (creating a process model from event logs), conformance checking (comparing an event log with a process model), and process enhancement (extending or improving an existing process model). This enables organizations to enhance operational efficiency, ensure compliance, and implement process improvements based on factual insights rather than assumptions, bridging the gap between theoretical process models and actual performance.