What is Task Mining?

Task mining is the automated analysis of user interaction data — clicks, keystrokes, screen captures, application usage — to reconstruct and understand exactly how workers actually perform a task, as a basis for identifying automation opportunities.

Where process mining reconstructs a business process from system event logs (order created, invoice approved, payment sent), task mining works one level lower — capturing the granular, desktop-level actions a person takes to complete their part of that process, often across multiple applications the underlying system logs never see. This surfaces the manual, undocumented work that process mining alone misses: the swivel-chair copy-paste between two systems, the workaround someone invented because the "official" process didn't handle an edge case. Task mining tools typically run as a lightweight recorder on employee desktops (with appropriate consent and privacy safeguards, since this is sensitive monitoring data), aggregating patterns across many employees performing the same nominal task to reveal variation, bottlenecks, and specifically which steps are mechanical enough to be strong robotic-process-automation or agentic-automation candidates.

In practice with Neotask

Before automating a manual back-office process, a Neotask discovery engagement can incorporate task-mining data to see exactly which steps a team actually performs (versus the official documented process) — surfacing hidden manual work like a spreadsheet reconciliation step that never appeared in the formal process diagram but consumes real time every day.

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