On the published evidence, yes — but the honest range is narrower than the one you have been shown. US Department of Energy figures put predictive maintenance at 8 to 12% better than preventive maintenance, and 30 to 40% better than running to failure.
The savings are real and they are documented by a government source rather than a vendor. What is not documented is most of what you will read. The widely circulated claim that predictive maintenance cuts downtime by 30 to 50% and maintenance costs by 10 to 40%, usually attributed to a large consultancy, is repeated across hundreds of vendor pages without a retrievable citation. We could not verify it, so we do not use it. Below is what we can source.
US Department of Energy, Federal Energy Management Program, O&M Best Practices Guide — hosted by Pacific Northwest National Laboratory.
Savings from a properly functioning predictive maintenance program over a preventive maintenance program alone.
Savings opportunity the same source says a predictive program could easily recognise against a reactive, run-to-failure baseline.
Savings from preventive maintenance alone over reactive. Useful as the floor: this is what a calendar-based program already buys you before any prediction.
Read the middle column carefully. The 30 to 40% figure is against reactive maintenance. If you already run a disciplined preventive program, the honest incremental number for you is the 8 to 12% — plus whatever the avoided failures are worth, which on power equipment is usually the larger term. See what an unplanned failure costs.
The baseline is reactive when yours is preventive. Most ROI calculators quietly compare against run-to-failure, which inflates the number by roughly a factor of three for anyone already doing scheduled maintenance.
CommonThe avoided failure is assumed, not measured. A model that predicts a failure you then prevent leaves no evidence that the failure would have happened. This is genuinely hard, and honest programs treat it as an estimate rather than a saving.
StructuralFalse alarms are not costed. Every unnecessary intervention carries labour, an outage window and risk. A system that predicts aggressively can cost more than it saves, which is why the ability to decline to predict matters commercially and not just scientifically.
UnderpricedBuyer scepticism here is warranted and widely shared — one maintenance-software vendor publishes a post titled Why Most Predictive Maintenance ROI Cases Are Wrong, which tells you where the conversation actually is.
On expensive power equipment, the maintenance saving is the small prize.
The large prize is extending useful life and converting an unplanned failure into a scheduled swap — which, with replacement lead times running two to four years, is worth far more than the labour you save. A predictive program that pays for itself on maintenance efficiency alone is a program aimed at the wrong number.
The standards buyers reference when they need to justify the spend internally are NFPA 70B, IEEE 493 and the NETA maintenance testing specifications.
A read-only assessment runs on data you already have, before any hardware conversation. You see the record; you decide what it is worth.
Choir™ Corp