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THE TECHNICAL LANGUAGE OF DIGITAL B2B INFRASTRUCTURE

PRACTICE
INTELLIGENT AUTOMATION

Process Discovery

The systematic identification and documentation of how work is actually performed across people, systems and decisions.


BUSINESS RELEVANCE

Process discovery shows how work really flows, including rework, delays and workarounds, which gives a factual basis for automation, cost reduction and compliance decisions instead of relying on documented procedures.


IMPLEMENTATION EXAMPLE

An accounts payable team exports 6 months of invoice events from its ERP with invoice ID, activity and timestamp. Process mining reveals that 18% of invoices loop back to approval, so the team targets those cases first.


LIMITATIONS

Event logs capture only system activity, so manual steps, emails and offline decisions are missing unless added through interviews or task mining. Poor data quality, such as inconsistent case IDs, produces misleading process maps.


TECHNICAL EXPLANATION

Process discovery combines workshops, interviews and observation with data-driven process mining. In process mining, an event log with a case ID, activity name and timestamp for each event is fed to discovery algorithms, such as the alpha miner or inductive miner, that build a process model. The resulting map shows variants, frequencies and waiting times, and can be checked against the intended process through conformance checking.


Secondary Topics

Revenue Operations, Systems Architecture

Sources

Microsoft Learn — Prepare processes and data — https://learn.microsoft.com/en-us/power-automate/process-mining-processes-and-data; Wikipedia — Process mining — https://en.wikipedia.org/wiki/Process_mining

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