A telematics feed can report location, engine hours, fault codes, idle time and fuel level, often all at once and all the time. Most of that stream is noise until it's tied to a specific decision — recover a stolen machine, service one before it fails, or stop paying to run one that's idling instead of working.
Key takeaways
Checked directly against Procore's own Equipment tool documentation: as of January 2026, “Equipment Telematics is now generally available,” delivering “real-time location” data through integrations with “Caterpillar, John Deere, Samsara, and United Rentals (beta).” That is a meaningfully recent capability — a fleet that hasn't looked at telematics integration in the last year is looking at a different feature set than what's available now.
The practical implication is that a mixed fleet running equipment from several manufacturers can now pull location data into one place rather than juggling each manufacturer's own portal separately, at least for the brands already integrated. That consolidation is what makes the data usable operationally instead of just technically available.
Real-time location is the easiest stream to justify because it maps to one clear action: if a machine leaves a defined site boundary without a corresponding move order, someone gets a flag. That's a recovery tool first, and a utilization-reporting tool a distant second — treating it primarily as a productivity dashboard undersells what it's actually good for.
It also connects directly to what happens after a theft. A GPS-confirmed last-known location narrows a police report and an insurance claim from “somewhere on a job site” to a specific point, which matters because the insurance mechanics that follow a theft run through the item's own capital cost allowance class — a faster, better-documented recovery attempt is worth pursuing before that process starts, not after.
Idle time is one of the easiest data points a telematics system reports and one of the least often turned into an actual decision. It sits in a dashboard as a percentage or an hours figure, gets glanced at, and rarely gets converted into what it actually costs in fuel — which is the only form of that number that changes anyone's behaviour.
The fix isn't more monitoring, it's translation: a fleet manager who can see “this machine idled 9 hours this week” has a fact. A fleet manager who can see what that costs in fuel has a decision to make about whether that idling is legitimate (waiting on a delivery, running a hydraulic system) or avoidable.
That same translated number is also the one worth taking to a financing decision. BDC's own equipment financing finances equipment on terms running “up to 12 years,” and a machine whose telematics data shows a chronic idle-cost pattern is a genuinely different candidate for replacement than one that simply looks old — the data makes that a cost comparison instead of a hunch.
A telematics dashboard with no assigned reviewer produces exactly the same outcome as no telematics at all: data accumulates, nobody checks it on a fixed cadence, and the first time anyone looks closely is after something has already gone wrong. The feed itself doesn't create the value; a person with a specific, recurring reason to look at it does.
That doesn't need to be a full-time analytics role on a mid-size fleet. It needs one person with a short, fixed checklist — flagged location alerts, idle-cost outliers, open fault codes — reviewed on a set schedule, rather than an open-ended dashboard everyone has access to and nobody is specifically accountable for checking.
A utilisation percentage — hours worked over hours available — is a genuinely different question from what a telematics feed reports, and answering it well requires deciding which of two common calculations a shop actually means by the term before the telematics data can even be applied to it. Treating telematics as the whole answer to a utilisation question skips that step and produces a number that looks precise without actually deciding anything.
The same caution applies to fault-code data: a code appearing in the feed is a signal worth routing to whoever owns preventive maintenance, not a data point worth building a dashboard around on its own. The value is in the routing — getting the right code to the right person quickly — not in accumulating a longer history of codes nobody acted on.
For the utilisation calculation itself, see measuring equipment utilisation honestly; for what an hour-meter reading should trigger on the maintenance side, see preventive maintenance on a mixed fleet. The location stream connects most directly to stopping material theft on an open site, since recovery and prevention are the same underlying discipline applied at different points.
A worked example
Say telematics data shows a piece of equipment idling roughly 9 hours a week beyond what its work actually requires, and it burns about 11 litres an hour at idle. At $1.65 a litre, that's $163.35 a week, or roughly $7,187.40 across a 44-week working year — fuel spent producing nothing, on one machine.
Multiply that across a fleet of a dozen machines with similar patterns and the number stops being a rounding error in the fuel budget. These figures are illustrative — the real number depends entirely on a specific machine's actual idle pattern and local fuel price, which the telematics feed itself already has; the missing step is usually just running the multiplication, not collecting more data.
Location. Real-time location is now generally available through Procore's Equipment tool ties directly to the clearest, easiest-to-justify action — flagging a machine that leaves a site boundary without authorization — before moving on to idle time or fault-code data, which take more work to turn into a decision.
No. Telematics reports raw facts — hours, location, idle time. Utilisation is a calculation built from those facts, and there are two genuinely different versions in common use (hours-based and cost-recovery-based). The data doesn't decide which calculation to run; that's a separate choice.
Usually yes, because the fix is cheap: price the idle hours in fuel cost rather than leaving it as a percentage on a dashboard. Even a handful of machines can carry a meaningful annual fuel cost sitting in unexamined idle time, and pricing it is a calculation, not a new purchase.
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