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In brief
- Process mining works well where a process runs end to end inside one or two systems with complete event logs.
- In regulated operations, much of the most expensive work runs across email, spreadsheets and portals, which leave no usable log.
- Facilitated capture, validated by a named person and carrying provenance, maps those steps so they can be scored consistently.
How process mining works
Process mining reconstructs a process from event logs, the timestamped records that transactional systems produce as work moves through them. Given a case identifier, an activity name and a timestamp, it can rebuild the real path work took, show variants, and quantify where time is lost.
Where a process runs end to end inside one or two systems, this is genuinely excellent. Order-to-cash in a single ERP. A claims workflow in one claims platform. The data is there, it is complete, and the analysis is close to objective.
Where regulated work runs
Now consider the processes that typically cost a fund administrator or a specialist insurer the most.
Investor onboarding runs across a transfer agency platform, a document store, three email threads and a counterparty portal. AML periodic refresh is tracked in a spreadsheet one person maintains. Dealing exceptions are worked from a shared mailbox with no queue and no ageing. Client reporting is assembled from four extracts and finished by hand.
Those steps produce no usable event log. There is no case identifier that spans the whole journey, no activity names, and no timestamps for the parts that happen in someone's inbox.
Typically, the processes with the largest prize run across inboxes, spreadsheets and portals. That is where facilitated capture adds the most coverage.
Dark work
A useful term here is dark work: activity that consumes real capacity but leaves no trace in any system of record.
- The shared mailbox that three people work without a queue, an ageing report or a record of who resolved what.
- The spreadsheet that tracks a rolling population and would take some explaining to a regulator.
- The chase-up call, the workaround that exists because two systems do not talk, the check somebody does because of something that went wrong in 2019.
- The exception path, which is where the cost concentrates and which seldom appears in the documented procedure.
Dark work is where rework, risk and capacity loss cluster. It is also where the AI opportunity is largest, because the work is manual precisely where no system was ever built for it. This is why an AI opportunity assessment works best when it covers the whole process, including the steps that system data does not show.
Structured capture with provenance
Where the data is yet to exist, create it deliberately, with the people who do the work.
- Facilitated capture with the people who do the work day to day. Activities, actors, systems, handoffs, controls, volumes, cycle times, exception rates and, critically, where the work waits.
- Validation by a named person for each process, recorded. That signature is what makes the map stand up to scrutiny later.
- Evidence carries provenance. Where a procedure document is used as a starting draft, it is marked as such, with a confidence flag, and where observed practice differs the divergence is recorded in full. That divergence is frequently the most valuable finding in the engagement.
- A structured record. The output is queryable, scoreable, re-runnable and comparable. A diagram is a photograph of a moving object; a structured record keeps up with the work. Once it is structured, every step can be scored consistently.
When process mining is the right answer
Helpful guidance
If your highest-cost processes run end to end inside one or two systems, and you have the data engineering capacity to support it, process mining will serve you better on precision and on ongoing cost, and we will say so.
If an enterprise implementation is already under way, completing it first usually makes sense, and that is what we would recommend.