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A complete guide to MTTR and other incident management metrics

Incident management metrics are indispensable for companies that want to assess how smooth their incident response mechanism is. These metrics help tech, maintenance, and security teams follow incident frequency and streamline the recovery of malfunctioning systems. Discover what each incident management metric stands for and how it can improve the organization’s well-being.

A complete guide to MTTR and other incident management metrics

Table of Contents

Table of Contents

What is MTTR? All four different measurements explained

MTTR is an incidental management framework that tracks how often accidents in an organization occur and how quickly teams are able to resolve them. These metrics are typically used in the IT, maintenance, and reliability engineering fields, with DevOps and ITOps teams relying most on the data incident management tools provide.

MTTR usually represents four distinct measures, with “R” standing for either repair, recovery, resolution, or response. Each of these metrics have some functions in common. Using all four measures helps organizations to track and minimize downtime caused by system disruptions and increase systems’ reliability.

Besides the four MTTR facets, organizations are encouraged to use additional incident management tools to enhance their response to system malfunctions and other accidents. Among these useful metrics are MTBF (mean time between failure), MTTF (mean time to failure), MTTD (mean time to detect), MTTC (mean time to contain), and MTTA (mean time to acknowledge).

Let’s examine how the mentioned incident management tools function.

MTTR: Mean time to repair

Mean time to repair definition

The mean time to repair signifies the average time needed to fix failed or malfunctioning systems. It starts counting from the moment the issue is detected until it’s fully solved, and the system functions normally again. This criteria helps to track how fast an organization’s maintenance and support staff can fix the malfunctioning elements. The goal of this metric is to make the repairs as speedy as possible by optimizing them.

It’s important to understand that mean time to repair doesn’t incorporate total system outage time – it only concerns the repair time from its beginning to end. This means it doesn’t include the time from the first alert till when the repair works begin. In some specific cases, when the nature of the incident is unknown, the mean time to repair may also include the time spared to diagnose the issue. However, that’s only the case when repair teams cannot proceed with repairs without extensive diagnostics.

Because it only measures the actual time spent repairing, the mean time to repair is not the right metric to judge about problems related to alert systems or the maintenance staff delays in replying to the issue.

How to calculate mean time to repair

To calculate the mean time to repair, you should determine the time frame you want to examine, for instance, a month. Then add up all time spent repairing systems during that month and divide it by the number of incidents. For instance, if you’ve spent 18 hours repairing systems in 6 unrelated incidents, your mean time to repair is 3 hours.

What is an acceptable mean time to repair?

The mean time to repair depends highly on the industry, the fixed system, and the resources available to the maintenance team. As a result, no unanimously acceptable MTTR time is applicable to all use cases. Industries in which uptime is critical, such as data centers or healthcare facilities, strive to make MTTR as short as possible. Meanwhile, other sectors, such as manufacturing, can usually allow longer mean time to repair as long as it doesn’t lead to production losses or extensive service disruptions.

MTTR: Mean time to recovery

Mean time to recovery definition

The mean time to recovery measures how much time it takes for a system to fully recover after its outage, counting from the moment it fails. Unlike mean time to repair, this metric includes the incident alert, detection, and repairs. Mean time to recovery helps to check whether the organization has any issues with the recovery process. On the other hand, this factor cannot pinpoint where the actual problems lay and which part of the recovery process potentially lags. Overall, the mean time to recovery is mainly helpful in measuring the overall speed of the recovery process.

How to calculate mean time to recovery

To calculate the mean time to recovery, you should first define the time frame you want to examine, let’s say two months. Afterward, add up all the downtime a system or a product experienced during this period and divide this sum by the number of incidents. So if your systems were down for 20 hours for four different events over the two months, your mean time to recover is five hours.

What is a good mean time to recovery?

The desired mean time to recovery is always as low as possible. However, the standards for this metric depend on the industry and systems it’s applied to. If the measured system is critical to the organization’s operations, it will likely assign more resources to fix all possible issues and will have a short mean time to recovery. Alternatively, if the organization is small and cannot spare many resources for incident management, the system recovery process may be significantly slower and result in more extended downtimes.

MTTR: Mean time to resolve/resolution

Mean time to resolution definition

The mean time to resolve is a metric that concentrates on the entire incident resolution process, representing a period from when the incident occurs until it’s fixed. This parameter considers time spent on incident detection, diagnosis, troubleshooting, and decision-making as well as time spent making sure the same issue won’t appear in the future. In a sense, the mean time to resolve focuses on long-term system repairs. When used in tandem with mean time to recovery, the resolution metric helps to identify how efficient maintenance teams are to ensure the failed system is reliable again and stays so in the future.

How to calculate mean time to resolve

Similar to MTTR calculations described before, to count mean time to resolve you need to determine the time frame you want to examine, add up resolutions time over that period, and divide it from the number of the incidents that occurred. For instance, if you spent 10 hours resolving two different issues in the last week, your mean time to resolve for that week comes to five hours.

What is the difference between mean time to resolve and mean time to repair?

The main difference between mean time to resolve and mean time to repair is that mean time to resolve focuses on the entire cycle of a system or product’s recovery process, from incident detection to taking the right steps to make sure the same issue doesn’t happen in the future. Meanwhile, mean time to repair considers only the time spent hands-on repairing the issue.

MTTR: Mean time to respond

Mean time to respond definition

The mean time to respond, also referred to as the mean time to remediate, measures the time between the first failure alert to when the repairs begin. The idea behind this metric is to assess how efficiently risk teams react to malfunction or security alerts and how fast they warn the necessary departments about a system’s malfunction. Mean time to respond is particularly used in cybersecurity because it helps assess how speedy security teams are when dealing with system attacks.

How to calculate mean time to respond

To estimate the mean time to respond, you should sum up the response time of incidents that happened during a particular time frame and divide that sum by the number of incidents. So if you’ve spent 15 hours responding to system failures over two weeks in three separate events, your mean time to respond is five hours.

MTBF: Mean time between failures

Mean time between failures definition

Mean time between failures measures the time between repairable but unexpected product or system failures. It’s typically used to evaluate the system’s reliability – the higher the MTBF, the more reliable the product. Because it’s meant to track product availability and reliability, MTBF doesn’t take expected issues and scheduled maintenance into account.

Mean time between failures helps maintenance teams to track unforeseen shortcomings of a system and issue recommendations to users about when it’s best to replace particular parts, reboot and upgrade systems, or bring the product for a scheduled check-up. MTBF is a vital metric for building an effective system maintenance plan because it tracks the performance and safety of the product.

How to calculate mean time between failures

To calculate MTBF, you should first determine the period you want to examine. Afterward, measure the total operating time of a product and divide it by the number of its failures. For instance, if a product was fully operating for 22 hours in a 24-hour span during which two failures occurred, your MTBF is 11 hours.

How does MTBF relate to MTTR (mean time to repair)?

MTBF and MTTR show different aspects of the system’s reliability and lifespan. The mean time between failures measures how long the product functions properly without unexpected interruptions and how reliable it is. Meanwhile, the mean time to repair indicates how fast systems can be brought back to life after failure and demonstrates the efficiency of maintenance teams.


MTTF: Mean time to failure

Mean time to failure definition

MTTF measures a product or system’s lifespan until its final and non-repairable failure. This metric provides valuable insight to customers about the expected duration of a product or system and informs them how often they need to schedule system check-ups. MTTF is also useful in assessing if new versions of a product are outperforming old ones. However, it’s important to note that mean time to failure is typically used for systems with shorter lifespans.

How to calculate mean time to failure

To count mean time to failure, you have to derive an arithmetic average: Sum up the operating time of the same model devices you’re checking and divide that sum by the number of devices. Imagine if a product was operational 800 hours during last year, and during that time it broke eight times, the MTTF for that product would be 100 hours.

MTTD: Mean time to detect

Mean time to detect definition

The mean time to detect, also referred to as the mean time to identify (MTTI), indicates the duration of the issue before it’s noticed. A metric to evaluate an incident detection system’s efficiency, MTTD is crucial to IT and DevOps teams because it shows how long an incident can remain undetected. Delayed detection can have a crushing impact on system stability and induce long-term disruptions.

How do you calculate MTTD?

To calculate the mean time to detect, determine the period you want to examine, add up all the incident identification times, and divide their sum by the number of incidents. So if in a week you’ve taken up to four hours to detect four different problems within the system, your MTTD is one hour.

MTTC: Mean time to contain

Mean time to contain definition

Mean time to contain measures the time it takes for security teams to fully contain all sorts of security risks or incidents. It’s a period between the alert and the isolation of affected systems, ensuring the issue stops harming the system or spreading further. A low MTTC indicates that the organization is fast and efficient in responding to security incidents.

How to calculate mean time to contain

The mean time to contain is counted by determining the period you want to examine, adding up the time spent detecting and containing the issue, and dividing it by the number of incidents. For example, if you’ve spent eight hours to contain security incidents in a particular week, during which two separate issues occurred, your MTTC is four hours.

MTTP: Mean time to patch

Mean time to patch definition

Most often used in the cybersecurity sector, the mean time to patch metric reveals the average time it takes for an organization to apply newly released security patches to its software, systems, and devices. Timely patching helps to protect systems from known vulnerabilities and reduce the risk of security breaches, making MTTP critical for maintaining a solid security posture. The rule is the lower the MTTP, the better

How to calculate mean time to patch

The mean time to patch is calculated by subtracting the time difference between the patch’s release date and the moment when the company installs the patch on its systems and devices. For better understanding, if a new patch for the software you use was released on January 4, but you implemented it on January 6, your MTTP is two days.

MTTA: Mean time to acknowledge

Mean time to acknowledge definition

Mean time to acknowledge shows how long it takes for the company to notice the security alert and acknowledge that an incident has occurred. It starts from the first issue alert and lasts until the company recognizes a security incident and takes action to deal with it. MTTA is typically used to assess how responsive the respective teams are and check if the system is suffering from alert fatigue.

How to calculate mean time to acknowledge

MTTA is calculated by determining the period you want to assess, then summing up the time between the alerts and their acknowledgment, and dividing it by the number of incidents. So if your team spent 10 hours acknowledging issues resulting from five different incidents that happened last week, your MTTA for that week is two hours.

The importance of tracking incident management

The discussed incident management tools are crucial for gaining insight into organizations’ incident response apparatus and staff efficiency. MTTR metrics help companies identify bottlenecks in current incident resolution processes and make necessary improvements. They also help recognize areas with bigger downtime than they should have and reduce it. When incident management tools are used in combination, they can provide a comprehensive outline of how effectively incident response teams are handling malfunctions and security issues.

MTTR metrics are vital for reducing the impact of data breaches and cyberattacks because they closely monitor the staff’s response times. Thanks to incident management tools, companies can more accurately set performance benchmarks for incident management teams.

Incident management tools can help boost an organizations’ resilience against cyberattacks and help them better manage system failures.