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Process discovery analyses how work actually happens rather than how people describe it. Traditional process analysis relies on interviews, which capture the happy path but miss the exceptions, workarounds, and variations that consume most of the effort.
Two approaches work together. Process mining analyses system logs and event data to map actual workflows. Task mining records user activity (screens accessed, clicks, time per task) to reveal how individual steps are performed. Together, they show where time is really spent.
For example, staff might describe invoice processing as "receive, match to PO, approve." Task mining reveals that 15 percent of invoices lack PO references (triggering a search), 8 percent have amount discrepancies (requiring supplier contact), and 5 percent are duplicates. These exceptions don't come up in interviews but account for nearly 30 percent of effort.
Discovery also reveals which processes justify automation investment. A process with 10,000 transactions annually is a stronger candidate than one with 100. Volume patterns, bottlenecks, and dependencies become visible.
Roborana uses discovery during the strategy phase to build a prioritised automation roadmap based on evidence, not guesswork. You automate where the data says the impact will be greatest.
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