Process mining vs task mining
By Ledgerium Research TeamUpdated July 2026How we research this
Process mining reconstructs a process from the timestamped event logs that IT systems already keep, while task mining observes a person's actual screen activity — clicks, keystrokes, app switches — to capture work that never touches a loggable system. Most real processes need both to see the full picture.
Key takeaways
- Process mining works from system-generated event logs; task mining works from directly observed screen activity — they capture the process from two different vantage points.
- Process mining needs a system that already logs structured, case-identified events. Task mining needs nothing from the underlying systems — it watches the user instead.
- Task mining sees cross-application, manual, and ad hoc work that process mining cannot, because that work never produces a loggable event in any single system.
- The two techniques are complementary, not competing: mature process-intelligence programs often combine system logs with observed activity for a complete picture.
Definition: Process mining vs task mining
Process mining and task mining are two techniques for reconstructing how a business process actually runs, distinguished by their data source: process mining derives the process from timestamped event logs already produced by enterprise systems, while task mining derives it from directly observed user interactions such as clicks, keystrokes, and application switches captured during the work itself.
Where each technique gets its data
Process mining's raw material is an event log: a table of case-identified, timestamped records exported from a system like an ERP, a ticketing tool, or a case-management platform. Task mining's raw material is direct observation — software that watches the screen and records clicks, keystrokes, window switches, and field entries as a person actually works, regardless of which systems are involved. That difference in data source is the reason the two techniques see different parts of the same process.
What each technique is good at
Process mining is strong wherever the process already lives inside systems with clean, structured logging — it can process years of historical case data in one export. Task mining is strong wherever the real work is manual, spans multiple unrelated applications, or involves steps — like copying a number from a spreadsheet into a web form — that never generate a loggable event in any single system's log.
Choosing between them (or using both)
Teams whose process lives mostly inside one well-instrumented system, like a mature ERP, get the most value from process mining. Teams whose process spans multiple systems, involves manual steps, or is not yet well-logged get more value from task mining, because it captures the work directly rather than depending on the systems to have recorded it. Many process-intelligence programs eventually use both: system logs where they exist, and observed activity to fill the gaps.
Process mining vs Task mining
| Aspect | Process mining | Task mining |
|---|---|---|
| Data source | Timestamped event logs exported from IT systems | Direct observation of screen-level user activity |
| Setup requirement | Systems must already log structured, case-identified events | No system logging required — captured by watching the work |
| Sees cross-application work | No — limited to what one system logs | Yes — captures work across any application the user touches |
| Historical data | Can analyze years of past cases from existing logs | Only sees work recorded going forward |
| Best fit | Processes concentrated in one well-instrumented system | Processes that are manual, cross-application, or ad hoc |
How Ledgerium captures this
Ledgerium sits on the task-mining side of this comparison: it records the actual clicks, systems, and timing of a workflow as it happens, which is how it captures cross-application work that a log-based process-mining export would miss.
1. Install the extension
Add the Ledgerium recorder to Chrome. No screenshots and no keystrokes are ever captured.
2. Record the real workflow
Perform the process once. Ledgerium captures the structured steps, timing, and system context.
3. Get the output
Receive an SOP, a process map, and a workflow intelligence report generated from the real work.
Worth knowing
Ledgerium's recordings function like task mining — capturing real browser and application activity directly — rather than mining existing system event logs, so it will not surface historical process data from before a workflow was recorded.
Related terms
Sources
- Ledgerium AI — Product overview — verified 2026-07-18
- Ledgerium AI — Methodology (how we research this) — verified 2026-07-18
Frequently asked questions
- Neither is universally better — they capture different data. Process mining is best where systems already log clean, structured events; task mining is best where the real work is manual or spans multiple systems.
- Yes. Many process-intelligence programs combine system-derived event logs with directly observed activity to get a complete picture, using each technique where it is strongest.
- No. Task mining fills the gap where process mining cannot see — manual and cross-application work — but it does not replace the years of historical case data a mature system's logs can provide.
- Ledgerium's recordings work like task mining: they capture real browser and application activity directly as a workflow happens, rather than mining historical logs from existing systems.
See this in a real workflow recording
Record a workflow once and get a structured SOP, a process map, and an intelligence report generated from real work, not memory.
Free plan includes 5 documented workflows per month. No screenshots ever captured.