What is MTTR? MTTR Explained: A Key Metric for Success

Mean Time to Repair, or MTTR, is a key performance indicator (KPI) and maintenance metric used in IT operations and incident management to measure the average time it takes to resolve an issue from the moment it is detected until it is fully resolved, such as repairing a system or equipment breakdown.

MTTR is used in various industries, particularly in IT and manufacturing, to measure the average time required to repair a system or device and restore it to full functionality after a failure. A lower MTTR indicates that an organization can quickly address and fix unplanned issues, which is crucial for minimizing outages and maintaining system reliability.

To help you better understand the role MTTR plays in measuring and improving the success of your incident response efforts, we’ll explore the definition of MTTR in more depth.

We’ll also highlight how MTTR and other common “mean time to” metrics differ, show how MTTR is calculated, when MTTR is useful and when it’s not, and why MTTR is such an important metric for gauging how well IT investments support an organization.
 

• MTTR definition
• Other “MTTRs” to know
• What’s the difference between MTTR and similar metrics?
• How is mean time to repair calculated?
• Common challenges using MTTR
• Can improving MTTR benefit business operations?
• How Tanium helps organizations improve MTTR

MTTR definition

MTTR stands for mean time to repair. Technically speaking, MTTR encompasses the entire process from when an issue is detected to when the system is back in operation — including the time taken to detect, diagnose, repair, and verify the fix.

This doesn’t mean that the root cause of the failure has necessarily been eliminated. It typically means the system is back up and running, allowing normal operations to continue. DevOps teams or cybersecurity specialists might still be investigating the root cause and ensuring that the system can be protected from this type of failure in the future.

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Other “MTTRs” to know

While MTTR most commonly stands for mean time to repair, MTTR can also stand for mean time to respond. In this case, MTTR measures how long in takes teams to respond to an alert, measuring how quickly teams can address issues once they realize there’s a problem to resolve.

MTTR can also describe mean time to recovery — in other words, how long it takes to get a system back up and running after a failure is detected.

Mean time to resolve is another measurement that goes by the same acronym of MTTR. Mean time resolve is the time frame needed not simply to repair the system but to address the root cause of the failure so that the system is unlikely to fail from that root cause again. Resolving an issue this way helps improve the overall uptime of the system and ensures the system can meet service-level agreements (SLAs) for performance.

As you can see, MTTR is an important metric, but it’s just one of several metrics for analyzing system failures and repairs. Understanding these metrics and their insights is essential to take advantage of different ways of analyzing your organization’s ability to respond to system failures, whether due to cybersecurity incidents, software misconfigurations, or some other root cause.

[Read also: What is incident response? Latest strategies and trends]

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What’s the difference between MTTR and similar metrics?

Several key metrics are involved in understanding system reliability and efficiency. MTTR is a crucial indicator that measures the average time required to repair and restore a system to full functionality after a failure.

However, MTTR is just one piece of the puzzle. To gain a comprehensive view of system performance, it’s also essential to consider other related metrics such as Mean Time to Detect (MTTD), Mean Time to Acknowledge (MTTA), Mean Time Between Failures (MTBF), and Mean Time to Failure (MTTF):

• MTTD means mean time to detect. By understanding MTTD, organizations can confidently answer how long it takes for the failure or incident to be detected when a system failure or a cybersecurity incident occurs. Shortening MTTD is a great way to accelerate repairs and restore service, whether repairing an internal system or working with third-party service providers.
• MTTA stands for mean time to acknowledge. It measures the time between a system raising an alert and the IT or cybersecurity team beginning their work. MTTA is helpful because it highlights how quickly a team can get moving to fix a problem. If MTTA stretches too long, the overall response time will significantly slow. MTTA helps IT teams assess their tools, processes, and training by focusing on those critical moments at the beginning of a repair. MTTA is a similar metric to mean time to respond.
• MTBF stands for mean time between failures. This metric isn’t focused on repair times but rather on the overall reliability of systems. Ideally, MTBF should be as long as possible, indicating that a system can go for an extended period without failure. This will support the IT environment’s normal operations and increase system user customer satisfaction.
• MTTF stands for mean time to failure, the average time a particular system can operate before failing to a degree beyond repair. Think of MTTF as representing the average operating lifespan of a specific type of system. For example, if a particular type of disk drive has an MTTF of 35,000 hours, you can expect to run for about four years before failing for good.

Now that we’ve defined the differences between these key measurements, it’s time to calculate MTTR for your organization. The calculation process is crucial for accurately measuring and improving system repair efficiency. Let’s explore the steps to determine MTTR and how this metric can enhance operational strategies.

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How is mean time to repair calculated?

To calculate MTTR, you measure the total time spent on repairs over a given period divided by the number of repairs. The time spent on a repair begins when a system failure or outage is detected and continues until the repair is completed, including diagnosing the root cause and testing a solution to ensure that functionality has been fully restored.

For example, if a computer system had three failures in a month, and the repair times to resolve those failures were one hour, five hours, and six hours, respectively, then the MTTR would be four hours.

4 = (1 + 5 + 6) / 3

The formula is:  MTTR = (Total repair time) / Number of incidents

If the system had four failures in the following month and the time required to resolve them was two hours each, then we would calculate the MTTR as follows: (2 + 2 + 2 + 2)/4 = 2 hours. In this case, the MTTR would have improved even if the number of incidents had increased.

You can see from these examples how MTTR sheds light on resolution time itself, independent of the frequency of incidents or the overall number of failures to be resolved. It highlights the efficiency of IT repair processes and points to opportunities for applying real-time automation, checklists, and other tools and best practices to improve IT efficiency.

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Common challenges using MTTR

MTTR delivers the facts about just how long repairs are taking. However, it doesn’t provide the underlying details about the overall repair lifecycle and what’s making repairs go faster or slower.

Any repair or IT incident resolution depends on many factors, including data collected, the data quality, the tools used to analyze that data, the skill sets of the IT engineers or security analysts working to resolve the incident, and so on.

To properly analyze these other factors, you need visibility into endpoints, tools, and processes.

Instead, what MTTR provides is an important, unambiguous metric about IT responsiveness and impact on the organization.
 

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Can improving MTTR benefit business operations?

Today, every business depends on its IT systems. MTTR provides a meaningful, easily understood metric for benchmarking your IT and cybersecurity teams’ ability to diagnose and remediate system failures that can easily cost your organization thousands or millions of dollars.

MTTR is like a health indicator for IT operations and the business operations that depend on them. And like a health indicator, it shows when changes are called for.

For example, a high MTTR can indicate that investments in people, tools, and processes should be made.

By tracking MTTR and establishing a baseline, you can measure the effectiveness of your endpoint monitoring, patch management, threat detection, and other efforts to answer questions like:

• If you add automation or swap out a tool, does the MTTR improve?
• Do new tools and workflows shorten or lengthen MTTR?
• Does improving endpoint visibility help, and by how much?
• Can MTTR be reduced using a centralized, integrated toolset rather than an ad hoc collection of tools from multiple vendors?

Ultimately, MTTR can act as a valuable rubric for testing new tools and processes by providing a means to measure the effect of changes in remediation tactics and strategies used to improve the overall uptime of IT operations, which allows organizations to make more informed investments to enhance overall cyber resiliency.

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How Tanium helps organizations improve MTTR

Tanium Incident Response, a core solution available for our platform, gives you everything you need to investigate incidents thoroughly, discover the breadth of impact and root cause, easily collaborate with DevOps and security teams, and effectively remediate them at scale — all from one tool.

With Tanium Incident Response, you can rapidly resolve incidents as soon as they pop up — wherever they appear in your environment — and proactively detect, investigate, and resolve issues before they lead to downtime or helpdesk tickets.

Tanium enables you to:

• Reduce MTTR for incidents across the enterprise
• Minimize system downtime, lateral movement, and attacker dwell time (the length of time attackers remain in your network)
• Reduce IT helpdesk tickets and support calls that result from system failures and cybersecurity incidents
• Reduce the impact and cost of security and operational incidents
• Replace a collection of point tools with a single, unified platform
• Increase productivity and job satisfaction by optimizing digital employee experiences

Real-time monitoring and anomaly detection are essential for organizations to be immediately alerted to issues, resolve them quickly, and more easily maintain uptime. Tanium’s visibility makes a critical difference in the speed at which teams can detect, acknowledge, respond to, repair, and remediate system failures.

Watch Tanium customer Metropolitan Water District of Southern California describe its experience using the Tanium and Microsoft integration to reduce its response time to threats by 20% while also minimizing costs and efforts, effectively ensuring systems are active, and gaining a single view of all endpoints.

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Schedule a personalized demo of Tanium today to see how our platform can help you and your organization reduce MTTR.