Customer Service Glossary - Mean Time to Resolution

Mean Time To Resolution

Mean Time to Resolution (MTTR) is the average time between a customer reporting a problem incident and when that interaction is marked “resolved.”

sanjana

September 26, 2022

7 mins read

90% of customers rate an “immediate” response as “important” or extremely essential when they have a question about a product, with more than two-thirds of the buyers’ population considering “immediate” to mean 10 minutes or less.

As is evident above, time is of the essence here—and it is crucial to track and measure the time it takes for customer service requests to be resolved through quantifying metrics. One such metric is the Mean (or average) Time to Resolution or MTTR.

In this entry, you’ll learn:

  • What Mean Time to Resolution is.
  • Why it is essential, how to calculate it.
  • Ways to reduce it.
  • The relevance of the other MTTR terms.

With an adequate understanding of these service desk metrics, you can expect to ace servicing your customers for your company.

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What is mean time to resolution (MTTR)?

Mean Time to Resolution (MTTR) is the average time between a customer reporting a problem incident, commonly annotated as “customer interaction,” and when that interaction is marked “resolved.”

This comprises the time needed to identify the failure, accurately determine the problem, and “resolve” it, as well as the time required to ensure the failure won’t occur again.

This metric measures the customer servicing team’s long-term performance and correlates it strongly with customer satisfaction. This leads to improved customer lifetime value and retained business revenue generation.

Why is it essential to measure mean time to resolution (MTTR)?

90% of customers consider issue resolution their most significant reason for contention with customer service personnels. Hence, the faster you resolve their queries, the better it is for improving customer experience and instilling brand loyalty.

With complex processes governing the majority of systems, especially in the tech, financial, security, or healthcare sectors, downtime or glitch incidents can cost your customers time, money, and other resources, which can negatively affect your reputation.

Time to Resolve helps you to categorize complex issues and put multiple personnels on them, spot lags in resolving simple issues and monitor internal processes responsible for longer resolution durations.

Incident management within the minimum time can streamline your strategic and operational initiatives and enable you to serve your customers with the best experience, ensuring that you retain their business.

MTTR is a valuable metric that accounts for the entire customer experience because it measures the time it takes to get an acceptable resolution (rather than just the time it takes for customer service reps to come up with the preliminary response).

A quick incorrect or insufficient response still results in a bad customer experience, therefore, you should include the time it takes your service reps to establish first contact with your aggrieved customer and waiting durations in between searching for appropriate solutions to resolve the issue. This will help you get a better idea of the complete picture and measure your MTTR more accurately.

How to calculate mean time to resolution (MTTR)?

Mean time to resolve is, simply put, the average sum of all incident resolution times in a given period of time.

Here is the mean time to resolution formula:

  • MTTR = sum of all time to resolve periods / number of incidents.

Example:

If you spend a total of 24 hours (from receiving a problem alert to finding a correct fix that resolves the issue for the customer) on three separate incidents in a week, your mean time to resolution would be 8 hours.

Note: MTTR is often computed using business hours, so if you recover from a problem at closing time one day, then work to resolve the root cause the next morning, those 16 hours would not be included in your MTTR. It’s vital to decide how you will track time for this metric if you have teams across several sites working around the clock or on-call staff working after hours.

It is helpful to measure your mean time to resolve in comparison with your mean time to recovery since the difference demonstrates how quickly the team works to improve the system’s reliability and stop similar issues from occurring in the future. This comparison also sheds light on how the post-incident fixes and post-mortem processes operate and accurately identifies which node in the process is ripe for improvement.

Mean time to resolution is most applicable in unplanned customer service requests and typically not the ones mentioned in the service manuals.

Understanding other MTTR metrics — Mean Time to Respond, Repair, and Recovery

Mean Time to Respond

Mean Time to Respond (MTTR) measures how long it typically takes to recover from a product or service breakdown after receiving the initial failure signal.

How to Calculate:

  • Mean Time to Respond (MTTR) = sum of all time to respond periods / number of incidents

Example: 

If you spend an hour (from alert to resolution) on three different customer problems within a week, your mean time to respond would be 20 minutes.

How to Improve:

First, you can try to increase the pace of system repairs (by introducing incidence management playbooks or monitoring error analytics) and second, you can increase the efficiency in receiving customer problem alerts and accelerating the repair processes (essentially improving the mean time to acknowledge).

Mean Time to Repair

Mean Time to Repair (MTTR) measures how long it generally takes to repair a system and make it functional for the customer again.

How to Calculate:

MTTR = sum of all time to repair periods / number of incidents

Example:

If you spend an hour (to only repair) customer issues six times within a week, your mean time to repair would be 10 minutes.

How to Improve:

Since this metric solely focuses on your team’s capability to perform repairs as quickly as they can, the only way to improve on this is by supplying your team with accurate information in the form of playbooks and previous use cases and adequate technical support that helps them diagnose and sort out a problem more productively and efficiently.

Mean Time to Recovery

Mean Time to Recovery (MTTR) is the average amount of time needed to recover from a system or product failure. This spans the entire period of the outage, from the moment the system or product malfunctions until it resumes regular operation in its entirety.

How to Calculate:

MTTR = Sum of downtimes in a specific time period / number of incidents

Example:

If your system is down twice in 24 hours, for 30 minutes each, your mean time to recovery would be 15 minutes.

How to Improve:

Mean time to recovery is a high-level metric that measures the time it takes for your team to recover from a particular incident problem. Now, the specificity of the problem is not made clear during its calculations, and the issue could be any part of the process, whether with your diagnostics or repairs.

Therefore, you need to check your whole schema for chances of improvement. In this case, you need to dig deeper into your other MTTR metrics but mean time to repair is an excellent umbrella annotation that indicates whether you have a problem with your recovery process or not.

How to reduce mean time to resolution (MTTR)?

Mean Time to resolution is not a metric you essentially need to improve beyond a point. If your customers are satisfied with your servicing durations, you need not be worried or invest in bettering the process.

That said, if you need to work on your MTTR, the first thing you need to do is identify the problem—this means you need to detect the process that takes the most time for your customer service team to resolve.

Go through your reports, examining the specific discussions that ended quickly, in about the average amount of time, and those that ended very slowly.

Most help desk systems will time stamp various conversational exchanges, and using those timestamps, you may create a timeline of the conversation’s course. While you may have a general idea of where time is spent most, the facts could still be a surprise.

Investigating more than a dozen chats will usually give you an idea of how the time utilization typically divides unless you have large volumes. List the areas where time is slipping away, and then arrange the list according to the most prominent causes and simplest solutions.

Here are some of the most common issues your customer service team may be facing while resolving queries and issues:

External Factors and Solutions:

If your initial response time is slow:

You can:

  • Take a look at your triage procedures;
  • Automate your workflows into organizing resources and labor; and,
  • Have some of your team members concentrate on the chats that just arrived.

If there is a lot of back-and-forth:

You can:

  • Guide your staff to Improve their analytical reading abilities; and,
  • Pay attention to any follow-up queries and prepare responses for them in advance.
  • If your customers’ problems are complex, you should focus on communicating better to understand their perspective and what they expect you to solve.

If your internal processes are cumbersome, you should discuss resources, delegation, and workflows with them.

Internal Factors and Issues:

If large data volumes are messing with your averages:

You can:

  • Modify your reporting to exclude certain circumstances; and,
  • Instead of focusing on the average, consider the mean.

If completed conversations are not leading to “resolution”:

You can:

  • Think about marking discussions as “resolved” automatically after a certain period of time; and,
  • Discuss communications with your customer service staff to modify strategies as required.

If issues that were previously sorted out are being reopened with new inquiries:

You can:

  • Check to see if chats may be locked at your help desk, after resolution; and,
  • Tag recently reopened conversations appropriately to keep them separate from new inquiries.

Deciding your MTTR Benchmarks

It is obvious that shorter MTTR durations are ideal, but how short should they be? To establish MTTR benchmarks for your organizations, consider these questions:

  • What timeframe are your customers expecting from you?
  • How much time does it take for your team to resolve a query?
  • What does your SLA agreement say?
  • What is the MTTR like for your competitors?
  • Do your customers have enough self-help resources?

Based on the answers you’ll be able to set an appropriate benchmark for MTTR for your customer support team. This benchmark will be reasonable—making it easy to achieve.

Final Thoughts

You cannot afford to miss even 30 minutes owing to an unresolved issue in today’s highly competitive global corporate environment. That is why mean time to resolution (MTTR) may be the most crucial metric your company needs to measure and monitor.

However, the customer should always come first. In your quest for “right” reporting, do not devalue customer experiences. Remember that the goal of measuring your MTTR is to ensure that your customers face problems as infrequently as possible while using your products or services, enabling them to make their lives easier and, in turn, attest to your brand value and credibility.

sanjana

Sanjana Sankhyan is a freelance writer who specializes in delivering data-driven blog posts for B2B SaaS brands. She helps businesses attract more audience and sales with her writing. If not writing, you’ll find her helping other freelancers improve their work. Find her on LinkedIn or Twitter.

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