Task mining is a technology-driven approach that captures and analyzes user interactions with applications at the desktop level to understand how employees perform their daily work.
Task mining uses screen recording, computer vision, and AI to analyze how users interact with software applications. It captures keystrokes, mouse movements, application usage, and screen changes to create a detailed picture of how tasks are actually performed.
| Aspect | Task Mining | Process Mining |
|---|---|---|
| Data Source | Desktop interactions (screen recordings, clicks, keystrokes) | System event logs and timestamps |
| Focus | Individual user activities and behaviors | End-to-end processes across systems |
| Visibility | Shows "how" tasks are performed at user level | Shows "what" happened in a process sequence |
| Granularity | Micro-level task details | Macro-level process flows |
| Use Case | Understanding variations in how people work | Analyzing process efficiency and compliance |
| Implementation | Desktop monitoring software | Log extraction from enterprise systems |
Process mining typically starts with structured event logs from systems like ERP or CRM, showing which activities occurred, when, and by whom. It's excellent for analyzing formal processes but misses desktop-level activities that don't generate system logs.
Task mining fills this gap by capturing the "last mile" of work—what employees actually do on their screens—making it particularly valuable for understanding manual tasks and system interactions that process mining can't see.
Organizations often combine both approaches for a complete picture: process mining for the structured process backbone and task mining for detailed user behaviors within each process step.