As the maintenance world embraces predictive analytics, IoT, and AI-driven insights, it’s no longer enough to simply do the work — you need to measure it.
For interactive visuals and an explanatory heatmap, see the Risk-Based Maintenance article: Risk Matrix Heatmap → Maintenance KPIs (Key Performance Indicators) help teams benchmark performance, track progress, and drive continuous improvement. But in 2025, smart maintenance isn’t about tracking everything — it’s about tracking the right metrics and knowing how to act on them.
Below are the 10 essential maintenance KPIs every modern maintenance organisation should be monitoring, complete with formulas, real-world examples, and practical improvement strategies.
1. Mean Time Between Failures (MTBF)
Why it matters
MTBF measures equipment reliability. A higher MTBF indicates fewer breakdowns and a more stable operation.
How to calculate it
MTBF = Total Uptime / Number of FailuresReal-world example
A power station tracked the MTBF of its cooling pumps and found failures occurred every 90 days. After upgrading seals and installing vibration sensors, MTBF increased to 180 days.
How to improve it
Use condition-monitoring technologies (vibration, temperature, oil analysis) and apply failure mode analysis to identify weak points before breakdowns occur.
2. Mean Time to Repair (MTTR)
Why it matters
MTTR reflects how quickly your team restores operations after a failure.
How to calculate it
MTTR = Total Downtime / Number of RepairsReal-world example
A packaging line experienced an average repair time of five hours. By digitising manuals and pre-organising spare parts in their CMMS, MTTR dropped to 2.5 hours.
How to improve it
Create clear repair SOPs, attach them to work orders, train technicians on critical assets, and pre-stage repair kits.
3. Planned Maintenance Percentage (PMP)
Why it matters
PMP shows how much maintenance work is proactive versus reactive. The higher the percentage, the better.
How to calculate it
PMP = (Planned Maintenance Hours / Total Maintenance Hours) × 100Real-world example
A food manufacturing plant increased PMP from 60% to 85% after implementing runtime-based PM schedules through their CMMS.
How to improve it
Use meter- or condition-based triggers and optimise PM frequency using historical data and FMEA findings.
4. Schedule Compliance
Why it matters
Schedule compliance indicates whether planned maintenance work is completed on time — a critical factor in preventive programs.
How to calculate it
Schedule Compliance = (Completed PMs on Time / Total Scheduled PMs) × 100Real-world example
A fleet maintenance team improved compliance from 65% to 92% after using mobile CMMS reminders and assigning PMs directly to technicians.
How to improve it
Break PMs into manageable tasks, review overdue work weekly, and introduce scheduling buffers for critical assets.
5. Overall Equipment Effectiveness (OEE)
Why it matters
OEE combines Availability, Performance, and Quality into a single productivity metric.
How to calculate it
OEE = Availability × Performance × QualityReal-world example
An injection moulding line improved OEE from 68% to 80% by addressing micro-stoppages and retraining operators.
How to improve it
Use machine data and sensors to identify performance losses and focus improvements on the weakest OEE component.
6. Maintenance Backlog (Weeks)
Why it matters
A healthy backlog indicates effective planning. Too high suggests understaffing; too low suggests underutilisation.
How to calculate it
Backlog (weeks) = Total Outstanding Work Hours / Weekly Available Labour HoursReal-world example
A mining site reduced its backlog from six weeks to 3.5 weeks by improving prioritisation and adding a dedicated planner.
How to improve it
Prioritise work using asset criticality and risk. Outsource or defer low-priority tasks when necessary.
7. Cost per Work Order
Why it matters
This KPI highlights high-cost assets and inefficiencies in maintenance execution.
How to calculate it
Cost per Work Order = Total Maintenance Cost / Number of Work OrdersReal-world example
A utility company discovered pump-related work orders cost four times the average. Improved PM practices reduced costs by 35%.
How to improve it
Analyse costs by asset class, identify repeat failures, and use CMMS cost codes to categorise expenses.
8. Emergency Maintenance Ratio
Why it matters
High emergency work signals poor planning, higher costs, and increased downtime.
How to calculate it
Emergency Ratio = (Emergency Maintenance Hours / Total Maintenance Hours) × 100Real-world example
A beverage plant reduced emergency maintenance from 25% to under 10% through weekly failure reviews and root cause analysis.
How to improve it
Tag emergency work in your CMMS, conduct after-action reviews, and convert recurring failures into preventive tasks.
9. Wrench Time (Technician Utilisation)
Why it matters
Measures how much of a technician’s day is spent doing actual maintenance work.
How to calculate it
Wrench Time = (Hands-on Time / Total Available Time) × 100Real-world example
A utility company increased wrench time from 35% to 55% by improving job planning, kitting parts, and reducing walk time.
How to improve it
Plan jobs thoroughly, ensure parts and permits are ready, and use mobile work orders.
10. Asset Downtime (Total Downtime Hours)
Why it matters
Downtime is one of the most visible and impactful maintenance metrics for leadership.
How to measure it
Track total downtime hours per asset over time.
Real-world example
A hospital reduced HVAC downtime by 40% after implementing a digital twin to simulate system performance under varying loads.
How to improve it
Monitor high-risk assets in real time, prioritise top downtime causes, and use simulation tools where available.
Technology-Driven KPI Optimisation
In 2025, high-performing maintenance teams don’t just report KPIs — they actively use technology to improve them.
- CMMS dashboards — real-time KPI tracking and alerts
- AI analytics — failure forecasting and resource optimisation
- IoT sensors — automated data capture for vibration, temperature, runtime, and downtime
- Digital twins — virtual testing of maintenance strategies and asset behaviour
For an interactive risk matrix and heatmap, see the Risk-Based Maintenance article: Risk Matrix Heatmap →
Final Thoughts
KPIs are only valuable when they drive action.
By focusing on the right maintenance metrics — and pairing them with modern tools, disciplined planning, and human expertise — maintenance leaders can move from reactive firefighting to proactive, data-driven decision-making.
Track less. Act more. Improve continuously.