Fictional sample output

See what the $1,500 assessment actually produces.

This example uses fictional CMMS data for a packaging facility. It demonstrates structure and specificity—not claims about a real customer.

Maintenance health
62

Reactive work, backlog age, and data quality suppress planning effectiveness.

Reactive work
43%

Five assets account for 31% of reactive labor.

PM compliance
78%

Several PMs are vague, duplicated, or not tied to observed failure modes.

Example bad-actor findings

AssetPatternReactive laborRecommended focus
CV-301Belt tracking, bearings, photoeyes188 hrTracking standard, alignment verification, bearing-condition task.
CP-17Jams, sensors, pneumatics154 hrSensor setup standard and pneumatic job plans.
AC-02High temperature, condensate132 hrCooling path, drains, separator condition, PM review.

Example PM disposition

22

PMs requiring scope modification.

18

Duplicate/consolidation candidates.

14

Strategy or interval review candidates.

Control: unknown torque, lubricant, vibration, clearance, or other authoritative values are flagged rather than invented.

Example 30-day action plan

TimingActionOwnerEvidence
Days 1–5Validate highest-impact bad actors and disposition open corrective work.Maintenance ManagerApproved list and assigned actions.
Days 6–10Disposition priority PMs: Keep, Modify, Consolidate, Investigate, Add.Reliability / PlannerApproved PM register.
Days 11–20Rewrite highest-value PM tasks with failure-mode and acceptance-criteria logic.Reliability + CraftsTechnician review complete.
Days 21–30Establish bad-actor, backlog, and monthly intelligence review cadence.Maintenance ManagerOwners and review dates established.

The real assessment uses your maintenance history.

Founding Maintenance Intelligence Assessment: $1,500.

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