HOW YOUR PROCESSES REALLY RUN

Classic analysis documents a process as people describe it; process mining derives how the process actually runs from the event logs the systems produce. Procedures describe the ideal flow, event logs show reality. Loops, rework and waiting time that never surface in workshops only become visible through data.

Three fields are essentially enough: a case identifier, an activity name and a timestamp. That data is extracted from the transaction records of ERP, CRM or operational systems. Additional fields such as resource, department or amount enrich the analysis but are not required. Data quality is assessed before analysis begins, because incomplete or inconsistent records would distort the findings.

You can, but the prioritisation rests on assumption. Process mining shows with evidence which process is genuinely high-volume, repetitive and costly, which ties the automation investment to data. The two feed each other: mining finds the opportunity, automation realises it, and the new data coming back from production becomes the input for the next analysis.

We work with a team certified in industry-leading tools, including UiPath Process Mining. Tool selection follows from your data sources, the scope of the analysis and your existing licence structure; if a platform is already in place we start there. The platform decision comes after the scope is clear, not before the analysis.

It does not have to be. Instead of a single snapshot, continuous monitoring can be set up: compliance with regulation and internal policy is tracked and deviations become visible as they occur. Data from production reveals new bottlenecks and becomes the input for the next improvement round.

A real process map, a measured list of bottlenecks and deviations, compliance findings and a prioritised list of automation opportunities. The output is not a presentation but a basis for deciding which process is addressed, in what order, with which tool, and why.