Power Platform
Power Automate
Workflow and integration. Moves data between systems, routes approvals and removes the manual re-keying that rarely appears in anyone's job description.
Construction & Field Services · Modern Work & Automation
Robotic process automation for repetitive field administration
A heavy equipment distributor and service business, Australia. Manual and repetitive processes were consuming staff time on administration that added no value but could not simply be dropped.
The situation
What the organization was dealing with
Manual and repetitive processes were consuming staff time on administration that added no value but could not simply be dropped.
Equipment distribution carries a long tail of repetitive administration: warranty claims, parts documentation, service records. Individually trivial, collectively a department.
What was done
The work, and the part that was actually hard
A robotic process automation solution was built using Power Automate with AI Builder to handle the repetitive processing directly.
Using low-code RPA with document understanding rather than a dedicated RPA platform kept this inside the existing licensing and skills. For a business of this size that is usually the deciding factor, because a separate automation platform brings its own operating cost.
Results
What was published
These are the figures exactly as reported in the source. Nothing has been rounded, extrapolated or restated.
Built on Power AutomateRPA
Applied to documentsAI Builder
Steps removedManual
What changed
- Repetitive manual processes automated with low-code RPA
- AI Builder applied to the document handling inside those processes
- Staff time recovered from administration
- Automation built on the existing Microsoft platform rather than a separate RPA product
Platforms involved
What each product was doing here
Power Platform
AI Builder
Document understanding and prediction models used inside Power Automate flows without a data science team.
What transfers
If you were to attempt this
Checking what your existing platform already covers before buying a specialist tool is the cheapest step available, and routinely skipped.
Where it usually gets harder than expected: Document understanding models need retraining as forms change. Treating the model as a build-once artefact is the common failure.
How we would take it on
Our approach to Modern Work & Automation work
1
Check what you already own
Most organizations are licensed for more than they have deployed. This step frequently reduces the engagement we were about to be paid for.
2
Assess permissions before AI
Copilot reaches whatever the user can reach. A decade of casual oversharing becomes visible on day one, and it is entirely avoidable if you look first.
3
Pick scenarios with the business
The functions that will use it know where their week goes. Scenario selection done inside IT produces pilots that impress nobody.
4
Measure in tiers
Usage, then time and quality, then business KPIs. Anyone promising the third before the first exists is guessing.
Recognise the problem?
If any of the above describes your organization, tell us where it hurts most. We will tell you what the same platforms could realistically do in your environment, what we would measure, and whether we think it is worth doing at all.
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