Struggling to calculate mean time to resolution with JSM Cloud

[Kevin Rowe]

Hi Folks

In a BI tool I am struggling to calculate my mean time to resolution as I am unable to find the relevant fields/measures to do so.  If it was simply created time and resolved time it would not be a problem but I need to factor in the SLA pauses too.

Has anybody else been able to do this please?  There are many time to resolution fields/metrics behind the JSM scenes but none of them seem to give me the actual time it took for resolved incidents - all the fields are for on-going only 

Attached just some of the examples 

Cheers

Kev

[Gizem Gökçe _OBSS_]

Hello @Kevin Rowe ,

Welcome to the community!

Are you looking for a way to calculate this directly in your BI tool, or would you consider using a ready-to-go report with a third-party app like Timepiece - Time in Status for Jira?

Timepiece, which is built by my team at OBSS, provides a Duration Between Statuses report that lets you calculate the resolution time while excluding SLA pause statuses. You can define which statuses should be counted and which should be excluded, ensuring an accurate Mean Time to Resolution (MTTR). The app also integrates with BI tools like Power BI and eazyBI, so you can use the calculated data within your existing reporting setup.

For all numeric report types, you can calculate averages and sums of those durations grouped by the issue fields you select. For example, in the screenshots below, the Duration Between Status report shows the Mean/Average Time to Resolution grouped by issues created each month. 

The app calculates its reports using already existing Jira issue histories so when you install the app, you don't need to add anything to your issue workflows and you can get reports on your past issues as well. Reports are available via the reporting page, dashboard gadgets, and issue view screen tabs, with both data tables and charts. Timepiece also offers a REST API for seamless integration and supports CSV/XLS exports.

Timepiece is available for both Jira/JSM/JPD Cloud and Data Center. Let me know if you’d like more information or assistance with your reporting needs! If you wish, you can also schedule a live demo. We will provide a comprehensive overview of the application and address any inquiries you may have.

Best regards,
Gizem

[Alina Kurinna _SaaSJet_]

Hi @Kevin Rowe !

Could you clarify if you're looking for a way to calculate the Mean Time to Resolution (MTTR) directly within your current tool, or if you're open to exploring an add-on from the Atlassian Marketplace that could help simplify this process?

If the latter, I recommend trying SLA Time and Report for Jira, developed by my team. This add-on allows you to monitor SLA performance, including tracking the time between issue creation and resolution, directly within Jira. You can easily view real-time metrics, analyze SLA performance using visual reports, and track key indicators like Time to Resolution to optimize your team’s efficiency.

• Accurate problem resolution time tracking:
  Automatically calculates the time it takes to resolve each request, providing accurate metrics for your reports.
• Customizable SLA configurations:
  Define SLAs based on various criteria, ensuring they meet your business requirements.

• Detailed reporting and analytics:
  Generate comprehensive reports that offer insights into your SLA performance, helping you identify areas for improvement.

• Real-time monitoring:
  Use the SLA Grid feature to monitor your SLA in real-time, ensuring timely responses and actions.

By implementing this add-on, you can overcome the limitations of Jira’s native reporting and better understand your team’s problem resolution time performance.

If you’d like to explore how it works, feel free to check out the 30-day trial to see if it meets your needs. Let me know if you have any questions — I’d be happy to help! 😊

[Christopher Yen]

Hi @Kevin Rowe , welcome to the community!

I haven't found any ootb fields that I could use to calculate this either. I have been thinking about adding custom fields and rules to capture the metric going forward though. 

My rough idea is that when a ticket transitions to a status that pauses the SLA (customer response, pending approval, etc) it will track pause start date/time and then when it transitions out it will calculate the difference between pause start and current date/time and write it to a Time Paused field then clear the pause start date/time field, and when the ticket is resolved a rule will calculate ( Created Date Time - Resolve Date Time ) - Time Paused to get resolution time. 

But if anyone knows an easier way to get the same result please post!