Author: Jochen Möller (CEO and CoFounder of EcholoN)
Creation: 29.06.2024, last change: 27.08.2024
Table of contents
Mean time between failures - MTBF - mean time between failures
The MTTR's: What is the mean repair time or MTTR - Mean Time to Repair
Mean recovery time as MTTR - Mean Time to Recover
Mean time to resolve as MTTR - Mean Time to Resolve
Mean response time as MTTR - Mean Time to Respond
MTTA: Mean Time To Acknowledge or Mean Confirmation Time
MTTF: Mean Time To Failure - average operating time until failure
In conclusion and to summarise: MTBF, the MTTRs, MTTA and MTTF
Learn more about some of the most common incident metrics.
What do the fault or incident metrics MTBF, MTTR, MTTA and MTTF mean? Operating conditions should have a high MTBF, as a low value can lead to a failure. MTBF stands for mean time between failure, which indicates the average time between two failures of a system. The MTBF is calculated by dividing the operating time between two failures by the number of failures. A high MTBF is a measure of the reliability of a system within a certain period of time.
The MTBF together with the MTTR can be used to improve the MTBF. MTTR stands for mean time to repair and indicates the mean time to maintenance. MTBF and MTTR can be used to better assess the repairable components of a system.
The MTBF is calculated by dividing the period of operating time between two failures by the number of failures. A high MTBF is a measure of the reliability of a system and represents the average service life of a component. A high MTBF can be achieved by using a computerised maintenance management system (CMMS).
Explanation of MTTR - the mean time to recovery, repair, response or problem resolution
When we talk about MTTR, many people automatically think of a single thing. However, MTTR can actually mean four different things:
- Repair
- Restoration stands for recovery
- Reaction: here it stands for the English term Respond
- Problem solving: in this case, Resolve
Even though they sometimes overlap, they all have their own specific meanings.
So when your team talks about MTTR, it's best to clarify exactly which one is meant and how it is defined. Before you start evaluating your performance, make sure that everyone knows exactly what is being talked about.
Mean time between failures - MTBF - mean time between failures
Mean time between failures, what is that?
Okay, so you know this term that people throw around, right?
MTBF - Mean Time Between Failures - Basically, it's how long something can function before it fails.
For example, if you have a machine, component or system, MTBF is how long it takes on average for it to fail. So you can predict when you need to replace or repair something before it gives up the ghost / has the next failure.
So yes, MTBF is a pretty big deal when it comes to keeping things running smoothly.
How is MTBF calculated?
MTBF is calculated by using the average. This involves taking the data from a set period of time that is to be analysed (for example, six months, a year or even five years). The total operating time within this period is then divided by the number of failures.
To calculate the average operating time between failures, proceed as follows. In the simplest case, you take the total operating time of a system and divide it by the number of failures.
MTBF = operating time / number of failures
If a system is operated for a total of 1000 hours and it fails 10 times during this time, then the MTBF is 100 hours. The MTBF should be subject to regular calculation to ensure that the system has a ‘normal MTBF’.
This metric focuses on unexpected failures, i.e. reliability. Failures due to planned maintenance are not taken into account here.
The MTTR's - What is the mean repair time or MTTR - Mean Time to Repair
Average repair time, what is it?
The mean repair time is a key figure for measuring the efficiency of a maintenance process. It indicates how long it takes on average to repair a system or machine after a failure.
The MTTR is calculated by dividing the total repair time of all failures by the number of failures.
The shorter the MTTR, the faster production can be resumed and the lower the downtime.
Use of mean time to repair - what is MTTR not?
The mean time to repair rarely corresponds to the total downtime of a system. It can happen that the repair is initiated after just a few minutes. In other cases, there are delays between the detection of the fault and the start of the repair.
This value is helpful in understanding how quickly the maintenance team can resolve an incident . However, it is not intended to identify problems in the detection of faults or delays in the actual repair. These aspects are also important factors in assessing whether your incident process is successful or not.
How is mean time to repair calculated?
The MTTR is calculated by adding the total time of repairs in a period and then dividing this time by the number of repairs.
MTTR = sum of repair times / number of repairs
As an example, there were 5 repairs in one month. Each repair took one hour, i.e. 60 minutes. If you now divide 60 minutes by 5 repairs, the average repair time in our case is 12 minutes.
Mean recovery time as MTTR - Mean Time to Recover
What does MTTR mean?
The mean time to recover, also known as mean time to repair, is the average time it takes to get a product or system fully functional again after a failure. It includes the entire downtime, from the occurrence of the problem to the complete restoration of operation.
How is MTTR calculated?
To calculate the mean time to recovery, you add up all the downtimes within a given period and divide them by the number of incidents. For example, if the systems were down for a total of 30 minutes in two separate incidents within 24 hours, divide 30 by two. This results in an MTTR of 15 minutes.
MTTR = sum of downtime / number of incidents
Using the mean time to recovery - what is MTTR not?
The MTTR provides information on how fast the recovery process is overall. Is the recovery time as fast as you would like it to be? How does your MTTR compare to those of your competitors?
Although MTTR is a helpful indicator to identify potential problems, it alone is often not enough to identify the exact cause of a problem. If you want to know more precisely where in the process difficulties occur (for example during alerting, diagnostics or the actual repair), additional data is required. A lot can happen between the occurrence of a failure and the final resolution.
- There may be delays in alerting: does it take too long for an alert to be triggered or forwarded to the right person after a failure?
- Or does the problem lie in the diagnosis: can the cause of the failure be determined quickly enough?
- Perhaps it is the repair process itself: Are the maintenance teams working as efficiently as possible? Why does it sometimes take a particularly long time for repairs to be completed?
A global view of the processes and use cases under consideration provides clarification here.
The average recovery time can be a good starting point to determine whether your recovery process needs closer scrutiny.
This metric is also important in the area of Development and Operations (DevOps). It is used to assess the stability and performance of a DevOps team according to DevOps Research and Assessment.
Mean problem resolution time as MTTR - Mean Time to Resolve
In this context, MTTR stands for the average time it takes to fully resolve a fault. This refers to the entire process of fault management - from the moment the problem is recognised to the complete restoration and operational readiness of the affected systems. A low MTTR value is a good sign: It shows that problems are being solved quickly and efficiently.
Mean time to resolution - How is MTTR calculated?
The calculation is based on the sum of all times spent resolving faults divided by the number of faults that occurred. The formula is
MTTR = total time to resolve problems / number of problems
This calculation produces an average value that serves as a benchmark for future faults.
Mean time to resolution Documentation and follow-up
Documentation and detailed records of problem resolution are the basis for continuous improvement. Service management tools and monitoring software support this. They enable the automated recording of times and the creation of reports. Regular reviews and optimisation of processes help to continuously reduce the MTTR.
Where is the mean time to resolution used?
The MTTR is used in a wide variety of industries and areas where the uptime and availability of systems and equipment play a role. It helps to evaluate the efficiency of repair and recovery processes and to identify weak points in fault management. Used in service level management to monitor and review service level agreements (SLAs).
Mean response time as MTTR - Mean Time to Respond
What is mean time to respond?
The mean time to response measures the time between the occurrence of faults and the start of active troubleshooting. This period covers the time from when the problem is recognised to the initiation of a repair process or the start of troubleshooting. A low value is better and indicates a fast response capability.
Calculation of the average response time
The calculation is based on the sum of all response times divided by the number of incidents. The formula is
MTTR (response time) = total time to response / number of incidents
This calculation of the average value serves as a benchmark for the efficiency of the response process.
Use of the mean response time
The mean response time is used in all sectors and areas in which people provide assistance. It is used in the emergency services of the police, fire brigade and emergency doctors, in IT (ITSM), emergency and security management and also in the manufacturing industry. Measurement and monitoring can help to optimise processes for problem detection and resolution. Use this metric to recognise whether your systems and teams are always ready to respond to incidents quickly and effectively.
MTTA: Mean Time To Acknowledge or Mean Confirmation Time
What is the mean time to acknowledge?
The MTTA reflects the average time it takes for a team or system to recognise a fault and ‘officially’ acknowledge it. This key figure begins at the time when the fault occurs and ends when the fault is logged in the system and assigned to the responsible department for processing.
How is MTTA calculated?
The calculation is based on the sum of all confirmation times divided by the number of faults. The formula is
MTTA = total time to confirmation / number of faults
Use of MTTA
MTTA is often used in IT and security management systems to measure the speed at which faults are recognised and delegated for processing. A low MTTA value is better and is a sign of an ‘alert’ monitoring system and a quick response capability of the team. Companies use this metric to optimise the effectiveness of their monitoring systems.
MTTF: Mean Time To Failure - average operating time until failure
Mean time to failure, what is it?
The mean time to failure is a metric used in maintenance and quality management. It provides the average fault-free functional life / service life of a component or product.
This metric is primarily used for products that do not need to be repaired after a failure but must be completely replaced, such as hard drives, light bulbs or batteries.
How is MTTF calculated?
The MTTF is calculated by dividing the sum of the operating times of all tested components by the number of components. The formula is
MTTF = total operating time of all components / number of components
This calculation produces an average value that indicates the expected service life of a product or component before a failure occurs.
Use of MTTF
It is used in product development and quality management to assess the reliability and service life of products. Manufacturers use it to forecast the durability of their products. Customers should receive reliable information about the service life. Particular attention should be paid to the MTTF and the evaluation of the reliability of devices that do not need to be repaired but have to be purchased again after a failure. A high MTTF value is better and signals a high reliability and longevity of the product.
Concluding and summarising: MTBF, MTTRs, MTTA and MTTF
When comparing the MTBF, MTTR, MTTA and MTTF metrics, it becomes clear that each of these key figures covers a specific aspect of system reliability and maintenance in the ticket system / case software.
While the MTBF (Mean Time Between Failures) measures the average time between two consecutive failures of a system and reflects the reliability over a longer period of time, the MTTR (Mean Time to Repair) focuses on the efficiency of the recovery process after a failure. The MTTA, on the other hand, shows how quickly a problem is recognised and confirmed, which is crucial for rapid problem handling.
However, MTTF (Mean Time To Failure) is fundamentally different as it measures the average operating time until the first failure of a non-repairable component or system. While MTBF, MTTR and MTTA are often used in systems that can be repaired after failures, MTTF is mainly applied to products that need to be replaced after a failure.
Together, these metrics provide a comprehensive picture of system reliability and the efficiency of response and repair processes, with each metric making a specific contribution to optimising system availability and minimising downtime.