What are MTTR, MTBF, MTTF, and MTTA? A guide to Incident Management metrics

It has become critical for businesses to measure and track their service delivery performance in the fast-moving digital world. However, when an incident management software measures various metrics and monitors the uptime and the downtime, a slight glitch in the system can disrupt the business processes, costing millions of dollars.

MTTR, MTBF, MTTF, and MTTA are abbreviations of some of the most important incident management metrics. In the domain of IT service management, these acronyms help organizations to plan their resources to ensure they can take care of problems cause by failed hardware and software glitches.  The full forms are as follows:

• Mean Time to Repair
• Mean Time Between Failure
• Mean Time to Failure
• Mean Time to Acknowledge

Let’s take a deep dive into each metric.

What is Mean Time to Repair (MTTR)?

Mean time to repair (MTTR) is the average amount of time required to repair a system and reinstate it to full functionality. The MTTR calculation begins once a repair starts, and they go on until the disrupted services are completely restored including any testing time needed.

In the IT service management industry, the R in MTTR doesn’t always symbolize repair. It could also represent recovery, respond, or resolve. While all these metrics do correspond, they have their own implications so it is always a good practice to clarify which MTTR is to be used. Let’s briefly look at what each of them means.

• Mean time to recovery (MTTR) is the average time it takes to recover from a breakdown of a device or system. This spans the entire process from shutdown due to an outage to the time the system is completely operational again. MTTR is a good indicator to measure the speed of the overall recovery process.
• Mean time to respond (MTTR) stands for the average time it takes to recover from a system failure from when the first failure alert came in, not including any delay in the alert system. This MTTR is typically used in cybersecurity to measure the team’s efficiency in defusing system attacks.
• Mean time to resolve (MTTR) represents the average time spent to completely resolve a system breakdown including the time it takes to detect the failure, diagnose the issue, and resolve the issue by making sure the breakdown doesn’t happen again. This MTTR metric is mostly used for measuring the resolution process of unforeseen incidents and not service requests.

How do you calculate MTTR?

Since MTTR is an incident management metric that IT teams utilize to keep repairs on track, businesses should aim to keep the MTTR number as low as possible. This is achievable by improving the productivity of the teams that conduct the repair processes. MTTR can be calculated as follows,

MTTR= total time spent on repairs during a given period/number of repairs

Let’s assume there were 6 failures in a system and the maintenance required to restore the system to full functionality took 3 hours which is 180 minutes. So, the MTTR would be,

MTTR=180 / 6= 30 mins

This means that an organization’s MTTR is 30 minutes, which is the time on average the organization spent on each downtime.

What is Mean Time Between Failures (MTBF)?

Mean time between failures (MTBF) is the average time passed between a repairable failure of a hardware and the next time it occurs. MTBF gauges availability and reliability so the higher the number of MTBF, the more reliable the system.

MTBF is a metric that aims to help customers make informed decisions about when to upgrade a system or put a hardware into maintenance. If, after a preventive maintenance phase, the MTBF has improved, this suggests an improvement in the reliability of the hardware. The rise in MTBF also demonstrates the efficiency of the maintenance processes.

How do you calculate MTBF?

MTBF is the time passed between one failure to the next. Mathematically, it can be calculated as follows,

MTBF=total operational uptime between failures / total number of failures

Suppose a system functions perfectly for 13 hours. During this period, 3 failures occurred which caused a total downtime of 1 hour. So, the MTBF would be,

MTBF = (13-1) / 3 = 4 hours

This figure means that a failure in the system occurs every 4 hours, causing the system to be down and generating losses for the organization. Tracking this metric can help plan strategies that can reduce this downtime.

Since MTBF is used to track reliability, it only reflects unexpected outages and does not take into factor any probable downtime during planned maintenance.

Like we mentioned earlier, MTBF is used to track failures in repairable systems. To track failures that require a system replacement, a metric called Mean Time to Failure (MTTF) is used.

What is Mean Time To Failure (MTTF)?

Mean time to failure (MTTF) is the average time passed between non-repairable failures of a hardware. MTTF measures the reliability of non-repairable systems and signifies the extent of time that the system is expected to function before it fails completely.

MTTF is an important metric used to measure the lifespan of replaceable or non-repairable hardware like keyboards, batteries, desk telephones, mice, etc. Historical data on the MTTF of each kind of hardware allows IT technicians to plan obsolesce in a phased manner.

Since the metric is used to identify how long a system would usually last, seeing whether a new version of a system is outdoing the old, would also help understand expected lifetimes and when to plan system check-ups.

How do you calculate MTTF?

MTTF is the primary indicator of a non-repairable hardware’s reliability, so the intention is to amplify the asset lifetime. Shorter MTTF leads to frequent downtime and disruptions. To calculate MTTF, use the below formula,

MTTF=total hours of operation / total number of failures

Presuming we were to examine three identical systems until all of them failed. The first system lasted 14 hours, the second one lasted 16 hours, and the third lasted 12 hours. MTTF in this instance would be,

MTTF= (14 + 16 + 12) / 3 = 14 hours.

This means that this particular type of system on average would need to be replaced every 14 hours to prevent longer downtimes and subsequent damages.

What is Mean Time To Acknowledge (MTTA)?

Mean time to acknowledge (MTTA) is the average time it takes for an organization to respond to complaints, outages, or incidents across all departments. The incident management metric MTTA is used to track a support team’s responsiveness and the alert system’s efficiency.

Sluggish responses can reduce the effectiveness of workers when internal systems face issues and cost organizations money. By tracking and minimizing MTTA, organizations can optimize their processes, improve customer satisfaction, and enhance profits.

How do you calculate MTTA?

MTTA is a useful measure to monitor responsiveness. If a team is taking too long to respond and is suffering from alert fatigue then this metric will help highlight the issue. To calculate MTTA use the following mathematical representation,

MTTA=total time taken between alert and acknowledgement / total number of incidents

Let’s say there were 5 incidents that happened in an organization and it took a total of 30 minutes of time between alert and acknowledgement for all the incidents, then the MTTA would be

MTTA= 30 / 5 = 6 minutes

This means that the MTTA for the organization is 6 minutes and the organization should work on reducing this time to optimize their resolution process.

Conclusion

To summarize, mean time to repair (MTTR) is a measure through which you can see how fast you can get a failed hardware to work again. Mean time between failures (MTBF) gives you a sense of how effective your support team is at minimizing or preventing impending incidents. Using the metric mean time to failure (MTTF), you can determine the lifespan of a system or hardware. Finally, mean time to acknowledge (MTTA) is a valuable measure through which you can track your IT support team’s responsiveness.

Now that you understand these incident metrics in detail, you will realize that each metric offers a different perspective. When used simultaneously these powerful metrics can provide a deeper perspective on how your support team is in managing service disruptions and help you reduce losses due to inefficiencies and quality issues. To learn more about which other service management metrics you should be tracking, read our article 7 Important Service Desk Metrics to Measure.