Process mining shows how work actually flows through your systems, not how you think it does. This guide explains what process mining is, how it works, and where live process operations extend it.
Process mining is a technique that reconstructs how a business process actually runs by analysing the event logs that systems produce, revealing the real end-to-end flow, its variations, bottlenecks and deviations, so teams can understand and improve how work happens.
Enterprise systems, ERP, CRM, ITSM and others, record events with timestamps as work moves through them. Process mining stitches these events into cases and reconstructs the real process: every path taken, not the idealized diagram. This exposes where reality diverges from the intended process, and where time and money are lost.
Process modeling draws how a process is supposed to work. Process mining discovers how it actually works from data. The gap between the two, the deviations, rework loops and bottlenecks, is where the value is: you cannot fix a process you only understand on paper.
Classic process mining is retrospective analysis. The newer angle is operating processes live: continuously monitoring running processes, predicting SLA and compliance breaches before they happen, and taking action when a process breaks, across procure-to-pay, order-to-cash, claims and ITSM.
Ops Singularity's ProcessOps pillar goes beyond retrospective mining to live operations: a real-time operational pulse of every process, bottleneck discovery, SLA and compliance monitoring with breach prediction, and governed action when a process breaks. Explore the ProcessOps pillar.
Process mining is used to discover how business processes actually run from system event logs, revealing bottlenecks, deviations and rework so organizations can improve efficiency, compliance and customer experience.
Process modeling draws how a process is supposed to work; process mining discovers how it actually works from event data. The difference between the two is where inefficiencies are found.
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