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Process mining allows organizations to gain transparent insights into their workflows, identify inefficient steps, and optimize process performance. This is achieved by analyzing event logs captured within information systems.
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Process mining reconstructs real business processes from event logs and compares them with intended flows.
Process mining grew at the intersection of process management and data mining; Wil van der Aalst and colleagues consolidated the discipline through the IEEE Process Mining Manifesto and research on event-based process models.
Each case leaves a trail of case ID, activity, and time. Process mining overlays those trails, discovers actual behavior, and highlights variants, waiting times, and deviations.
Time-ordered activities for individual cases.
Deriving a model from observed events.
Comparing actual and intended processes.
Process mining reveals how work really runs and exposes bottlenecks. Its validity and privacy depend on complete, correctly linked event logs.
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