1. PM Compliance
Definition: The percentage of preventive maintenance work orders completed on schedule within the defined time window (typically ±10% of due date).
PM Compliance (%) = (PM WOs completed on time ÷ PM WOs due) × 100
Target: ≥95%. Below 85% means your PM programme is effectively not being executed — unplanned failures will increase.
Why it matters: PM compliance is the single most predictive leading indicator of future equipment reliability. Plants with PM compliance above 95% typically have 40–60% fewer unplanned breakdowns than plants at 70%.
2. Schedule Compliance
Definition: Percentage of planned/scheduled work orders completed during the week they were scheduled.
Schedule Compliance (%) = (WOs completed as scheduled ÷ WOs scheduled) × 100
Target: ≥90%. This is a measure of planning quality, coordination with operations, and parts availability.
3. Wrench Time
Definition: The percentage of a maintenance technician's available time actually spent doing hands-on work (turning spanners, testing equipment, replacing parts). Also called "tool time" or "productive time".
Target: ≥55% for a well-organised maintenance department. Industry average is 25–35%.
The remaining time is spent travelling, waiting for permits, sourcing parts, receiving instructions, and documentation. Improving wrench time from 30% to 55% is equivalent to hiring 40% more staff — without adding headcount.
Measuring wrench time requires direct field observation or detailed time-stamp analysis from your CMMS. Work sampling studies are the standard method — 200+ random observations over 2 weeks give a statistically valid baseline.
4. Planned vs Reactive Ratio
Definition: The proportion of total maintenance labour hours spent on planned work (PM, planned corrective, predictive) vs reactive work (emergency breakdown, urgent corrective).
P/R Ratio = Planned hours ÷ (Planned hours + Reactive hours) × 100
Target: ≥80% planned. World-class is ≥90%. Below 60% indicates a predominantly reactive maintenance culture where planning is impossible because every shift brings new emergencies.
5. Backlog Weeks
Definition: The number of weeks of work in the approved work order backlog (work requested but not yet scheduled), expressed as weeks of available craft capacity.
Backlog Weeks = Total planned hours in backlog ÷ Weekly craft capacity (hours)
Target: 2–4 weeks for each craft (mechanical, electrical, etc.). Less than 2 weeks = insufficient backlog to schedule efficiently. More than 6 weeks = maintenance is falling behind and equipment risk is rising.
6. Mean Time Between Failures (MTBF)
Definition: Average time between successive functional failures of an asset (or fleet of assets).
MTBF = Total operating time ÷ Number of failures
Target: Trending upward over time. Absolute values are asset-specific. See our full MTBF & MTTR calculation guide.
Track MTBF per asset class (pumps, motors, gearboxes) to identify systemic reliability problems.
7. Mean Time to Repair (MTTR)
Definition: Average time required to restore an asset to service after a failure, from the moment failure is detected to the moment the asset is returned to operation.
MTTR = Total downtime ÷ Number of failures
Target: Trending downward. MTTR is improved through better spare parts availability, documented repair procedures, and trained technicians.
8. Overall Equipment Effectiveness (OEE)
Definition: A composite measure of manufacturing productivity — the percentage of planned production time that is truly productive.
OEE = Availability × Performance × Quality
Target: World-class OEE = 85%. Most plants run 40–60%. Maintenance directly controls the Availability component (unplanned downtime). See our OEE calculation guide and calculator.
9. Availability
Definition: The proportion of time an asset is in an operable state (not failed or undergoing corrective maintenance).
Availability = MTBF ÷ (MTBF + MTTR) × 100%
Target: Asset-specific. Critical single-point assets: ≥99%. General rotating equipment: ≥97%.
10. Maintenance Cost per Unit Produced
Definition: Total maintenance expenditure (labour + parts + contractors) divided by production output in the same period.
Target: Benchmark against industry norms. For process industries, maintenance cost is typically 1–4% of Replacement Asset Value (RAV) per year. Trending downward while reliability improves indicates programme effectiveness.
11. Stores Service Level
Definition: The percentage of spare part requests filled from stock without delay.
Target: ≥95% for critical parts, ≥85% for general stock. Poor service level is a leading cause of high MTTR — technicians wait for parts while equipment is down.
12. Safety: Near Misses and Incidents
Definition: Number of reported near-miss events, first-aid injuries, and lost-time injuries per million man-hours worked.
Target: Zero LTIs. Near-miss reporting rate should be high (many near-misses = good safety culture; zero = under-reporting). Track the near-miss ratio to LTIs — world-class organisations report 300+ near misses per LTI (Heinrich's triangle).
Building your KPI dashboard
Start with three KPIs, not twelve. A common effective starting set:
- PM Compliance (Are we executing the plan?)
- Planned vs Reactive Ratio (Are we managing proactively?)
- MTBF by asset class (Is equipment getting more reliable?)
Review weekly with the maintenance team and monthly with operations. Add more KPIs only when the first three are stable and well-understood. A maintenance team drowning in data but missing action is worse than one tracking three KPIs consistently.
CMMS data quality is the foundation of all maintenance KPIs. If technicians don't close work orders accurately with actual failure codes, start times, and end times, your KPIs are measuring data quality, not maintenance performance. Fix the data before building the dashboard.