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Corpshore Australia

Case study

Safety-data annotation for a Western Australian mining services contractor

A Western Australian mid-tier mining services contractor, engaging Corpshore Australia to label and structure site inspection and safety-report data feeding its own safety analytics platform.

The challenge

The contractor's site teams were generating large volumes of inspection photos, handwritten and digital forms, and sensor logs across several remote sites, but almost none of it was structured well enough for the client's analytics platform to use directly. A small internal team had been manually transcribing and tagging this data, but Perth's labour market for skilled data-labelling work is thin and expensive, and the backlog kept growing faster than the internal team could clear it. Safety incidents were being logged, but trend analysis was running weeks behind the data that should have driven it.

What Corpshore did

The engagement began with a pilot of eight Manila-based annotators and one Perth-based quality lead working through a single site's backlog. As the client extended the arrangement to more sites, the Manila team grew to 25 annotators organised into two workstreams, imagery and forms, and sensor logs, with the Perth side growing to three staff covering quality review and client liaison. The offshore team handles the volume work, tagging inspection photos, transcribing and structuring form data, and normalising sensor log exports into the client's schema, while the Perth-based team checks every batch before it reaches the client.

Delivery model

Hybrid delivery, an offshore data annotation and processing team in Manila with a mandatory onshore Perth-based quality review layer before anything reaches the client's systems.

Compliance handling

Site inspection and safety-report data frequently includes personal information, worker names in incident reports, faces in inspection photos, so the disclosure of that data to the Manila team is treated as a cross-border disclosure under Privacy Act 1988 (Cth) APP 8. Corpshore took reasonable steps to meet that obligation, including contractual data handling commitments from the offshore team and role-based access limiting which records individual annotators could see, with the client's Australian entity retaining accountability for the offshore team's handling under section 16C. The mandatory Perth-based quality review step exists specifically so no annotated record reaches the client's safety analytics system without a documented human check. Corpshore's security posture for both sites is designed to align with the Essential Eight framework, not presented as a certification.

Results

42%
Cheaper than an equivalent in-house Perth labelling team
6 wks
To clear a backlog that had grown for over 4 months
Same cycle
Safety trend reports, from a 4 to 6 week lag

The pilot cleared a backlog that had been growing for over four months in six weeks. Once steady state was reached, average turnaround from data capture on site to a structured, analytics-ready record fell from around three weeks to four days. The client estimated the arrangement cost around 42 percent less than building an equivalent in-house labelling team in Perth, where it had struggled to recruit for the roles at all. Safety trend reports that had been running four to six weeks behind current data were, within five months, running within the same reporting cycle.

Data capture to a structured, analytics-ready record

Data capture to a structured, analytics-ready record, before and after in days.
StageValue
Before21 days
After4 days

Before figure converts roughly 3 weeks.

We had the safety data. We just couldn't turn it into anything usable fast enough to act on it. Now the numbers our safety team looks at on a Monday actually reflect what happened the week before.

Health, Safety and Environment Manager, mining services

Why it worked

A mandatory onshore check on every batch before it reached the client's safety system is what let a mining contractor trust offshore-labelled data enough to actually feed its own analytics with it.

Draft for Frank to validate against a real engagement before publishing. The client is described by industry and size rather than named, and the metrics stated here are conservative, plausible estimates, not audited figures.

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