I have noticed that the slowest part of a mining work order is rarely the repair. It is the time between spotting a defect and getting the right technician to the right asset. Teams I talk with in San Diego who support mining and natural resources operations often describe the same pattern: the systems work, but the handoffs between them do not.
The lessons below come from looking at where that time actually goes, and how a Power Automate workflow can close the gaps.
Lesson One: The Handoffs Are the Real Problem
Take a haul truck with a hydraulic leak. The defect lands on a paper card, then in an email, then in the ERP, then in the maintenance schedule, typed by three different people. Each retyping invites a mistake, and nobody is sure which record is current. Capturing every request in one structured record, whatever its source, removes most of that confusion before a person even touches it.
Lesson Two: Validate Before You Distribute
If I could give only one piece of advice, it would be about order. Check that the request is complete and that the people, equipment and parts are actually available before assigning anything. Flows that assign first and validate later tend to create conflicts and mismatched records. When resources do clash, sending the options to a supervisor in Teams keeps the job moving instead of leaving it in a queue.
Lesson Three: Keep Assignment Rules Where Supervisors Can Edit Them
Good job distribution uses a few simple rules:
Skill match, so the right certification reaches the right asset
Location, so crews are not crossing a large site unnecessarily
Shift, so work is not given to a crew that is off rotation
Priority, so safety defects come before routine maintenance
Workload, so one technician is not overloaded
The part that surprised me most is where those rules should live. Keeping them in an editable table means a change, such as a new certification requirement, is a quick update by operations and not a rebuild by a developer.
Lesson Four: Plan the SAP Connection and Error Handling Early
Many mine SAP systems run on-premises. That usually means setting up a data gateway and involving the SAP Basis team, so it is better to start that conversation early. Just as important is error handling. If one branch of an update fails and nobody is alerted, the ERP and the asset system end up disagreeing, which is the exact problem automation was supposed to remove.
Lesson Five: Keep Watching After the Job Is Assigned
Many projects automate intake and assignment, then go back to phone calls for everything after. A better approach is to keep tracking until the job closes:
Record each status change as technicians report from the field
Keep a running log for audits and reporting
Run a scheduled check that escalates any job running past its expected duration
For surface mines in the US, a timestamped history also helps when safety defects on equipment need to be documented.
Lesson Six: Let the Shift Roster Shape Approvals
Connectors are rarely the hard part. A mine with three rotating shifts needs different approval routing than one with a central planning office. If every approval goes to a single planner who works days, the bottleneck simply moves. Mapping where a delay in validation cascades into assignment and system updates, before building anything, makes the design much stronger.
A Simple Place to Begin
Start with intake and validation, confirm the improvement, then add distribution, parallel system updates and monitoring. The same event-driven approach can later extend to shipment tracking, where a loadout weight or assay result posted in SAP updates the customer record in a CRM. A useful first step is to list every place your team retypes a work order today.
If you want the specific Power Automate actions behind each step, the full seven-step walkthrough from Bitcot is worth a read:
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