What is process mining?
Process mining reconstructs how your processes actually run, from the event data your systems already record, so you can see the bottlenecks, rework and deviations that opinion-based process maps miss. Here's how it works, where it helps, and how to turn the insight into governed action.
Evidence, not opinion.
Ask ten people how a process works and you'll get ten idealized diagrams, none of which include the rework, the shortcuts, or the three-day wait that nobody mentions. Process mining sidesteps the guesswork. Every time an order is created, an invoice approved, or a ticket escalated, the system stamps it with a time and an ID. Stitch those digital footprints together and the real, end-to-end process appears: every path, every loop, every bottleneck.
In short: process mining is x-ray vision for your operations, built from data you already have, not from a workshop.
From event logs to the real process, in four steps.
Pull the digital footprints your systems already keep, each record reduced to three things: a case ID (the order, ticket or batch), an activity, and a timestamp. That's the raw material.
Stitch the events into a directly-follows graph and the real flow appears, every path, every loop, every variant, not the idealized diagram from a workshop.
Overlay the process you designed. Where reality diverges, skipped approvals, rework loops, out-of-order steps, is exactly where risk and cost hide.
Quantify the bottlenecks, waits and cost of each deviation, then watch the process continuously so a regression is caught the day it starts.
Discover, conform, enhance.
Discovery
Build a model of the process purely from the event log, with no prior diagram. This is the 'show me what actually happens' step, and it routinely surprises the people who own the process.
Conformance checking
Compare the real behavior against a reference model or a set of rules. It answers 'are we following the process we think we are?', the foundation of continuous compliance.
Enhancement
Enrich the model with performance data, durations, frequencies, cost, to move from 'what happens' to 'where it hurts and what it's worth fixing.'
Process mining vs. BI, task mining and RPA.
They're often confused, and they're complementary. BI reports the numbers; task mining watches the desktop; RPA does the work. Process mining is the layer that reconstructs the flow and tells the others where to look.
| Capability | BI dashboards | Task mining | Process mining |
|---|---|---|---|
| Reconstructs the end-to-end flow across systems | |||
| Based on evidence, not interviews | |||
| Captures desktop / human steps between systems | |||
| Measures conformance to a target process | |||
| Tells you what to automate, and proves the result |
What process mining gives you.
The real process, from the data, not the version that survives a workshop.
See the bottleneck, the rework loop and the deviation, with the cost attached.
Invest in the fixes that pay off, ranked by impact and effort.
Turn compliance from a periodic audit into a live signal.
One picture spanning the systems where the process actually lives.
Every deviation carries a number, so improvement is measurable.
Use cases, from finance to the factory.
Order-to-cash, purchase-to-pay and accounts payable, find the leakage, the maverick spend and the missed early-payment discounts.
Maverick buying, off-contract spend, and the approval detours that slow a PO down.
The handoffs between WMS, TMS and ERP where SLAs quietly slip.
Reopened tickets, escalation loops, and the SLA breaches nobody saw coming.
Incident and change flows, where the process forks from the runbook.
The one most tools can't reach: mine the as-run technological process from machine telemetry, bottleneck, rework and conformance to the master recipe.
Insight isn't the deliverable. A better process is.
Classic process mining ends where it should begin: with a beautiful diagram a human has to act on, and nobody checks whether the fix worked. The value is only realized when the discovered problem becomes a governed action that's executed and verified.
That's the loop worth closing: discover → recommend → approve → execute → verify → learn, across the back office and the plant floor, on the systems you already own.
See how Tokoaido closes the loopProcess mining, answered.
Is process mining the same as data mining?+
No. Data mining looks for patterns in data generally; process mining is specifically about reconstructing and analyzing how a process flows over time, using event logs with a case, an activity and a timestamp.
What's the difference between process mining and task mining?+
Process mining reconstructs the end-to-end flow across systems from their event logs. Task mining watches the desktop, clicks and keystrokes, to capture the human steps between systems. They're complementary: process mining for the big picture, task mining for the fine-grained work in the seams.
How is process mining different from BI dashboards?+
BI tells you what happened as KPIs and charts. Process mining tells you how and why, the actual sequence of steps, the variants, the loops and the waits that produce those KPIs.
What data do I need to get started?+
At minimum, an event log: for each case (an order, ticket or batch), a list of activities with timestamps. Most enterprise systems already record this; the work is extracting and cleaning it.
Is process mining only for large enterprises?+
No. The value scales down: any organization with a process that spans a few systems and matters to the business can benefit, and modern, manifest-driven connectors make the data extraction far less of a project than it used to be.
Can process mining work on manufacturing or OT processes?+
Yes, though most tools stop at the ERP. The same technique applies to the plant floor: derive discrete events from machine telemetry (over OPC UA or MQTT Sparkplug) and you can mine the real technological process, its bottleneck and its conformance to the master recipe.
Does process mining fix the process?+
On its own, no, classic process mining produces the insight and hands it to a human. The value is only realized when the insight becomes a governed action that's executed and verified. That's the loop worth closing.
See process mining that runs the fix.
Explore a live, seeded workspace where a discovered process becomes a governed, verified action, across OT and IT.