28 Mar, 24

Key Performance Indicators in CMMS Software: Measuring Success in Asset Management

Charlie McFarlaneBLOGNo Comments

Computerized Maintenance Management Software has become pivotal for organisations looking to digitise and optimise their maintenance operations.

However, simply implementing a system isn’t enough to achieve maximum efficiency; great value lies in using the tool’s reporting features to improve outcomes.

CMMS software helps maintenance managers track vital metrics so they can keep tabs on asset performance and maintenance efficiency, and identify issues quickly. In this article, we’ll review some vital KPIs and how to use them.

Benefits of Monitoring KPIs Using Maintenance Management Software

KPIs gauge how efficient maintenance operations are, providing insights into areas such as cost-efficiency, asset uptime, compliance with maintenance schedules, and overall operational effectiveness.

Monitoring KPIs allows organisations to identify bottlenecks and areas where costs can be reduced without compromising on asset performance or maintenance quality. They also assist in asset lifecycle management and predictive maintenance.

Cloud based maintenance software enables quick and effective decision-making thanks to the use of real-time data. However, that’s not the only reason that using software to track KPIs is the most powerful option. Organisations that do so manually run the risk of missing on important trends, and on being alerted automatically when certain metrics aren’t as expected.

Key Asset Management KPIs

Mean Time to Repair (MTTR)

MMTR measures the average time required to repair a failed component, machine, or system and return it to operational status.

Monitoring MTTR lets organisations identify areas where maintenance processes can be improved; for example, a high MTTR might indicate the need for better training for maintenance teams, improved access to tools and parts, or more effective scheduling processes. Also, efficient repair processes, indicated by a lower MTTR, can lead to labour cost savings.

Tracking MTTR over time helps identify trends and potential problems before they lead to significant downtime, and this data can be used to move from reactive to predictive maintenance strategies.

In some industries, prolonged downtime can pose safety risks or result in regulatory non-compliance. Monitoring and improving MTTR can help mitigate these risks.

Work Order Resolution Time 

Similar to MTTF, work order resolution time helps identify bottlenecks in the repair process – specifically regarding the execution of work orders themselves. It’s a key indicator of efficiency, impacting both production throughput and customer satisfaction.

Monitoring this metric allows for targeted improvements in resource allocation, training, inventory and supply chain inefficiencies, and so on.

Mean Time Between Failure (MTBF)

MBTF measures the average time between failures of a system or component during its operational period, offering a straightforward measure of reliability.

It has a role in preventive and predictive maintenance as it gives teams an expectation of when a failure is likely. In turn, maintenance can be scheduled pre-emptively, reducing the risk of unwanted and costly surprises. For this reason, a high MTBF is especially crucial in industries where safety is paramount.

Knowing the MTBF of different equipment helps in strategic planning for resource allocation, inventory management, and budgeting for replacements or upgrades.

This KPI is an essential factor in the total cost of ownership and is also used to predict costs related to warranty claims.

Asset Availability and Reliability

Asset availability is the percentage of time in which an asset has been operational during a given period. It’s calculated as follows: (MTBF / (MTTR + MTB)) x 100. Availability should be above 90%.

Reliability is the probability that an asset will perform its required function within a certain period. In other words, availability is the actual measure of uptime while reliability is used for predicting likely availability.

Reliability could tell us that within the next seven days, there’s a 60% chance that the piece of equipment will operate without failing, for example.

The formula for reliability is: R (t) = eλt, where t = time (the same unit used for MBTF); λ = failure rate; and e = Euler’s number, which is 2.71828.

The failure rate is calculated as follows: number of failures / total operating time.

Preventive Maintenance Compliance (PMC)

PMC is the proportion of preventive maintenance tasks completed on time. In other words, it indicates how well a maintenance team adheres to the planned maintenance schedule.

High compliance suggests that the CMMS is being effectively used to establish proactive maintenance practises. It’s also a good indicator of equipment reliability and longevity, since preventive maintenance is vital for extending asset lifetimes.

Tracking PMC therefore helps in improving maintenance schedule adherence, which in turn helps in controlling maintenance costs.

The formula is: PMC = (number of completed preventive maintenance work orders completed within a specified period / total number of preventive maintenance work orders scheduled for that period) x 100.

Unplanned Maintenance Percentage

Similar to PMC, this KPI indicates the effectiveness of one’s preventive maintenance scheduling plan. The maximum value for unplanned maintenance should be 20%, but ideally it will fall below 10%. It’s calculated as follows: unplanned maintenance percentage = (time spent on unplanned maintenance / total time spent on maintenance) x 100.

Overall Equipment Effectiveness (OEE) 

OEE Monitoring is an important practice for assessing the effectiveness and efficiency of a machine or a production line. It combines multiple KPIs to provide a holistic view of how well equipment is utilised, indicating how well a manufacturing unit performs relative to its designed capacity.

OEE helps in pinpointing specific areas of loss in the manufacturing process, including availability losses, performance losses, or quality losses. Targeted improvements can then be made.

Monitoring this metric regularly enables manufacturers to identify trends in equipment performance, which helps direct long term strategy, process optimisations and equipment upgrades.

Another benefit of understanding OEE is that it allows for realistic estimations of machine capacity, helping to optimise production schedules.

Our asset management software solutions have an OEE Monitoring module. As well as helping improve productivity, it provides real-time data on labour costs and energy and water consumption for intelligent cost reduction.


This KPI is the maintenance cost for a piece of equipment as a percentage of its estimated replacement value. As such, it helps determine whether it’s worthwhile to replace an item or continue maintaining it.

It’s calculated as follows: MC/ERV = (total maintenance cost / estimated replacement value) x 100. There are different values that are considered acceptable for different types of assets.


Maintenance management KPIs are the compass that points towards efficiency, cost-effectiveness, and operational excellence.

Carefully selecting, monitoring, and acting on these indicators lets organisations significantly enhance their maintenance strategies, leading to prolonged asset life, reduced costs, and improved overall performance.

Of course, the most effective way to do so is using a cloud based Computerized Maintenance Management System. With a continuous stream of real-time data and easy to read dashboards, your maintenance team will always be ready to make data-driven decisions and act accordingly.

To book a demo of our world class solutions and see how easy KPI monitoring can be, contact us today.

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