PM compliance tells you whether preventive maintenance was executed on time. It does not tell you whether the PM tasks were technically capable of preventing, detecting, or controlling the failures you care about.
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PM compliance answers:
Did we complete the preventive maintenance that was due, inside the completion window we defined?
A common calculation is:
The site must define “on time” consistently. That may mean by the due date or within an approved tolerance based on the task frequency and risk.
PM effectiveness asks:
Did the task actually prevent a failure, detect deterioration early enough to act, restore a required condition, or control the failure mode it was designed for?
It is not one universal percentage. It is a body of evidence connecting PM content to asset failure behavior, findings, corrective follow-up, reliability, and maintenance burden.
That matters. A technically excellent PM program that is never completed cannot protect the equipment. But once execution is under control, the next question has to be whether the work itself deserves to remain in the program.
Scheduled PM work is being completed inside the organization’s defined timing rule.
The task addresses the correct failure mode, uses the correct method, or has a defensible frequency.
A completed inspection produced useful findings, corrective action, or a measurable reduction in recurrence.
The PM is executed exactly as written, but the recurring failures are caused by conditions the task never inspects, measures, restores, or detects.
“Inspect motor,” “check conveyor,” and “service pump” can all close on time while giving technicians no consistent inspection point, method, or acceptance criterion.
A legacy interval can be executed perfectly while being too short, too long, or simply unrelated to the deterioration pattern it is supposed to manage.
An inspection finds looseness, leakage, wear, contamination, or abnormal condition, but no corrective work is generated and the defect survives until failure.
Duplicated, overly intrusive, or low-value tasks can consume labor and equipment access without creating enough risk reduction to justify the maintenance touch.
The plant is not consistently executing the program, and the technical content may also be weak. Stabilize work management while identifying the highest-risk PM gaps first.
The PM strategy may be technically sound, but labor capacity, scheduling, access, parts, production pressure, or reactive work is preventing execution.
This is the dangerous false-positive state. The KPI looks strong, but repeat failures, emergency work, weak findings, or poor failure-mode coverage show the strategy needs redesign.
The team executes the intended work consistently, the tasks are technically defensible, defects are found early, corrective work follows, and failure behavior supports the strategy.
A stronger PM review combines execution data with failure behavior, finding quality, corrective follow-up, and task-level evidence.
Are assets continuing to experience the same failure modes even though the relevant PMs were completed on time?
Which inspection or condition tasks actually identify actionable deterioration, and which repeatedly close with no useful condition information?
When a PM finds a defect, does it create, prioritize, and complete corrective work before functional failure?
Do credible asset failure modes have an appropriate maintenance strategy, or are important mechanisms uncovered while low-value tasks remain?
Where the data is trustworthy, are failure frequency, downtime, reactive labor, emergency work, or similar asset-level signals improving after strategy changes?
How much labor, access, production interruption, parts consumption, and planning effort does the PM program require for the risk it controls?
A conveyor line completes 95 of 100 scheduled PMs inside its defined completion window. Compliance is 95%.
But the same drive-end bearing continues to fail. The monthly PM says only “inspect conveyor.” Technician notes contain no bearing condition, temperature, vibration, lubrication condition, contamination finding, or acceptance criterion. No corrective work is generated before failure.
The execution metric is strong. The maintenance strategy is not.
The corrective response is not “push compliance to 100%.” The response is to validate the failure mode, determine the appropriate maintenance strategy, rewrite the task, establish the technical basis and acceptance criteria, and verify whether the new strategy changes the failure behavior.
MaintenanceAI reviews PM master data against corrective work history, repeat failures, task quality, frequency basis, failure-mode coverage, and available technical evidence. The goal is not simply fewer PMs. It is a more defensible maintenance strategy.
See the full preventive maintenance optimization workflow, including Keep, Modify, Consolidate, Investigate Frequency, Convert Strategy, Add, and Remove dispositions.
Review a fictional PM effectiveness analysis showing task-level findings, evidence controls, confidence, and human-review requirements.
The stronger question is: did we do the right maintenance, at a defensible interval, in a way that controls the failures the asset actually experiences?
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