Thomas Filaire has a nice primer on Process Mining up on Medium. Including a nice venn diagram showing where process mining "lives" - at the intersection of business process management and data mining.
It's especially useful when applied to systems that are, effectively "data maintenance" solutions - where the process is implied rather than implemented. Or inferred rather than defined.? Think: your CRM system (most likely).? T&E systems.? Case-oriented tooling.
By looking at the data, the changes to the data, and the order in which those occur, a process can be inferred... this may be different than even the process as modeled in a BPMN diagram and implemented by a BPM engine.? Because our clever business team might find workarounds for changing systems of record, or our clever process mining algorithm might find implied process from data changes that we would normally think of as "just data."
I've been a fan of the idea ever since I saw the Process Optimizer in an early version of Lombardi Teamworks.? And since then the techniques for this sort of work have improved considerably.? Here's an effective abstract for the whole article:
Most of the time, business owners know very well their processes from a theoretical perspective: what is supposed to happen, when, who is supposed to do what, under which condition.
However, they usually do not have a way to investigate what is really happening throughout the process lifecycle. Traditional reporting, Business Intelligence (BI), statistical tools have difficulties in revealing both the big and the very detailed picture. Such a back and forth navigation from the big picture and the detail is actually what is the most efficient way to comprehend the real life situation. Process mining solutions such as Disco?focuses on making it easy to digest and exploit.