Task mining captures how people work on their desktops across all applications. Process mining reconstructs how cases flow through structured systems from event logs. The first sees manual work between systems; the second sees end-to-end flows inside them. Most organizations need the desktop view first.
Side by side
| Dimension | Task mining | Process mining |
|---|---|---|
| Data source | Desktop user activity | System event logs |
| Scope | Every application, including legacy and manual steps | One structured system at a time |
| Setup | Agent install, no integrations | Log extraction and data modeling per system |
| Time to first insight | Weeks | Months |
| Sees manual work between systems | Yes | No |
| Sees full case lifecycle inside an ERP | Partially | Yes |
| Typical cost driver | Devices in scope | Integration and modeling effort |
| Privacy risk | Depends heavily on tool design | Lower than desktop tools, but logs can identify users too |
Task miningProcess mining
EmailSpreadsheetERP orderERP invoiceEmailInside the ERP
Every step, in every application.Only the steps the ERP records.
How to choose
- Choose desktop-level observation when work spans many tools, when you need automation candidates fast, or when system data is incomplete
- Choose process mining when one structured system dominates the process and you need exact case-level flows inside it
- Combine them when both conditions hold: logs for depth, observation for the gaps between systems
Where Nodra sits
Nodra belongs to the desktop-level family but rejects its classic weakness: instead of recording detailed individual activity, it minimizes and pseudonymizes on the device and reports aggregated process insights. You get the breadth of task mining with a privacy architecture designed for European deployments, and a deliverable focused on prioritized automation opportunities rather than raw process maps.