Not theoretically. Not based on the manufacturer’s general guidance. Based on this specific unit, in this specific building, with its actual service history, its current condition data, and the maintenance spend that has accumulated against it over the last several years. When does it need to be replaced?
Most facility operations cannot answer that question with confidence. The FM who manages that building can probably offer a range — “it’s getting old, probably in the next two or three years” — based on experience, observation, and the general principle that units of that age and type don’t last forever. The ownership group that needs to plan the capital allocation wants a number, a timeline, and a basis for both. The gap between those two positions is not a budget gap. It’s a data gap.
The gap between those two positions is not a budget gap. It’s a data gap.
What Most Operations Would Say
Ask a Director of Operations at a multi-site commercial portfolio when a specific piece of equipment needs to be replaced, and the answer tends to be one of three things: “we’re monitoring it,” “it’s on the list for next year’s budget conversation,” or “we’ll know when it starts causing problems.” None of those answers is wrong. They’re honest reflections of what the data supports.
“We’re monitoring it” usually means someone is physically checking it periodically and it hasn’t failed yet. “It’s on the list” usually means someone knows it’s aging but there’s no documented case to accelerate it to the top. “We’ll know when it causes problems” is the reactive posture — waiting for the failure event to create the urgency the data should have already created.
These responses are the rational output of an information environment where asset condition is assessed through periodic inspection rather than continuous monitoring, where maintenance spend is tracked at the work order level but not aggregated by asset, and where useful life estimates come from general guidelines rather than condition data specific to that unit.
What a Well-Managed Operation Can Answer
The metrics a facility team with asset lifecycle visibility can access without pulling reports across three systems are specific and integrated. Installation date and expected useful life remaining are calculated against the asset’s actual operating hours, service environment, and maintenance history. ASHRAE publishes equipment useful life data; applied to a specific unit with known operating conditions, it produces a range, not a guess.
Cumulative maintenance spend tracks total corrective spend on this asset, aggregated across all work orders over its operating life. The unit that has consumed $28,000 in corrective maintenance in the last three years is not making the same CapEx case as the unit that has consumed $3,200. Failure frequency details how many times this asset generated an emergency or corrective work order in the last 12, 24, and 36 months. A unit with three corrective events in 18 months is making a different argument than a unit with one.
Asset health is judged by age and visual snapshot inspection, leading to vague timelines like “in two or three years.”
Work orders, vendor invoices, and runtime hours are consolidated at the asset level to map cumulative maintenance spend.
Replacement schedules shift to data-driven timelines built on continuous monitoring trends and documented failure frequencies.
The Gap Between the Two — and What Closes It
The difference between the FM who says “probably in the next two or three years” and the FM who says “Q3 of next year based on current condition trend and cumulative spend” is not expertise. It’s information infrastructure.
The data required to make that second answer exists in most buildings. It’s distributed across work order records, vendor invoices, BAS logs, and inspection reports. What’s missing is the mechanism that aggregates it by asset, surfaces it in a format that supports a capital decision, and connects it to the replacement cost estimate that makes the CapEx request coherent.
According to IFMA and BOMA benchmark data, facilities teams that operate with consolidated asset maintenance history and condition monitoring consistently make capital replacement decisions earlier — and at lower total cost — than teams operating without that visibility. The reason is not that they’re more aggressive about spending. It’s that they’re not forced to wait for failure events to create the urgency that data should have already created.
The CapEx Baseline
The CapEx conversation that stalls in most organizations stalls because someone asks “why now?” and the honest answer is “because it’s old.” That’s not a capital case. It’s an observation. The CapEx conversation that moves forward is the one where the answer to “why now?” is a timeline built on condition data, cumulative spend, and failure frequency — not on age and intuition. The next time the capital planning conversation comes up for an aging asset in your portfolio: what data are you bringing to that conversation?
Sources:
- ASHRAE — Equipment useful life data by asset type: https://www.ashrae.org
- IFMA Benchmarking — Asset lifecycle and capital planning data: https://www.ifma.org/resources/research-benchmarking/
- BOMA EER — Operational cost and capital expenditure benchmarks: https://www.boma.org/BOMA/Resources/EER
- McKinsey — Predictive maintenance and capital decision timing: https://www.mckinsey.com/capabilities/operations/our-insights