# PM Optimization Using Failure Data

**URL:** <https://forum.cybermetrics.com/t/pm-optimization-using-failure-data/123>\
**Category:** Facility Maintenance\
**Created:** [January 30, 2026, 8:40pm UTC](https://forum.cybermetrics.com/t/pm-optimization-using-failure-data/123 "2026-01-30T20:40:34Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![aavila](https://avatars.discourse-cdn.com/v4/letter/a/a6a055/32.png) [@aavila](https://forum.cybermetrics.com/u/aavila)\
**Post date:** [January 30, 2026, 8:40pm UTC](https://forum.cybermetrics.com/t/pm-optimization-using-failure-data/123/1 "2026-01-30T20:40:34Z")

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**Why This Topic?**

Many PM programs are built on:

- OEM recommendations

- Legacy practices (“this is how it’s always been”)

- Copy-paste CMMS setups

Yet breakdowns still happen—and PMs keep piling up.

**Honest question:** Are your PMs actually preventing failures… or just filling calendars?

* * *

**The Core Idea**

Failure data should drive PM optimization.

Every corrective work order tells a story:

- What failed

- How often it failed

- How long it took to fix

- What it cost (labor, parts, downtime)

Ignoring this data turns PMs into assumptions instead of controls.

* * *

**Common Issues Seen in Facilities**

- PMs added after every failure without analysis

- Repeat failures on the same asset

- PM intervals that don’t match real-world usage

- PM tasks that don’t address the actual failure mode

- No review cycle for PM effectiveness

If this sounds familiar, you’re not alone.

* * *

**What Failure Data Is Actually Useful?**

Instead of focusing on single incidents, look for **patterns** :

- Repeat corrective WOs on the same asset

- Same failure mode occurring multiple times

- MTBF trending downward

- Failures occurring shortly after PMs

- High-cost or high-downtime failures

These usually point to PM design gaps—not technician performance.

* * *

**What PM Optimization Looks Like in Practice**

Facilities that optimize PMs typically:

- Adjust PM frequency based on failure trends

- Modify PM steps to target known failure modes

- Add condition checks instead of adding more PMs

- Eliminate PMs that don’t reduce failures

- Validate changes using MTBF and reactive vs planned ratios

Optimization is about precision, not cutting corners.

* * *

**Common Mistakes to Avoid**

- Making PMs longer instead of more focused

- Overreacting to one failure

- Ignoring environmental and usage factors

- Changing PMs without documenting why

- Never reviewing the impact of changes

* * *

**Field Reality Check**

- More PMs ≠ better reliability

- Failure history beats OEM intervals

- One targeted PM can replace several generic ones

- If techs consistently question a PM, it deserves review

* * *

**Let’s Discuss**

- Which PM in your facility adds the **least value**?

- Have you ever reduced or removed a PM? What was the outcome?

- Do your PM tasks align with real failure causes?

- How often do you review PM effectiveness using actual data?