which report is a accurate for time to resolution

Hi guys, I have a question. Which report is the best solution to show the time to resolution for all tickets? I don't need the resolution average. I am currently using the average, but it doesn't work well for me.

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Answer accepted

If you want resolution time for every ticket individually rather than a single average, use a report grid — one that shows one row per issue with the duration calculated for each, not an aggregate.

For this I'd recommend our app Time Metrics Tracker | Time Between Statuses. You create a Resolution Time metric: pick the status that starts the timer (e.g. when a ticket is opened) and the one that stops it (resolved or Done). You can exclude statuses that shouldn't count — like "Waiting for Customer" — and link a Work schedule so idle time over weekends or holidays doesn't count.

The grid then shows each ticket as its own row with its resolution time, so you can sort to find the slowest ones, filter by date or assignee, and export to CSV/Excel

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The same metric also feeds Flow Insights above the grid if you want a quick read on trends and which status contributes most — without exporting anything.

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Hope this helps!

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Hola Nugzari,

I dug into this a bit more, and @Varun Chillamcharla's comment is only partly useful for your specific JSM question.

The important part is that Jira Service Management’s built-in Time to resolution report is an SLA report, and Atlassian confirms that each data point is the average Time to resolution SLA for the requests resolved in that period. So if you need the actual SLA duration for every individual ticket, that report won’t provide it.

Simply exporting Created and Resolved and subtracting them gives you raw elapsed time, but that’s not necessarily the same as JSM’s Time to resolution SLA. The SLA can use business calendars, pause while waiting for a customer, and start or stop based on configured conditions. Atlassian explains that distinction here.

There is some native overlap with what Varun suggested, though. Atlassian now documents an Automation approach specifically for JSM that copies the elapsed time from each completed SLA cycle into a custom field. That value can then be shown on the request and exported from a queue to CSV. For Time to resolution, the smart value would use the completed cycle’s elapsedTime value. Atlassian’s current Cloud instructions are here.

That’s the option I’d use if your goal is a list of all requests with their actual Time-to-resolution SLA duration, rather than another average chart.

If you only need to identify tickets by their SLA state or elapsed SLA time, you may not need the extra field. JSM supports SLA-aware JQL such as completed(), breached(), elapsed(), remaining(), and running(), which can be useful for building queues around Time to resolution. Those queries help you find the right requests, but they still don’t turn the built-in report into a per-ticket duration report.

Thanks,

James.

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Thanks for the deeper dive, James — good catch on the SLA vs. raw elapsed time distinction, and the elapsedTime smart value approach is a cleaner native solution than what I suggested. Appreciate you filling in the SLA-aware JQL functions too, useful to know those exist for this kind of thing.

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Hi @Nugzari Turashvili,

Jira Service Management has a Time to Resolution column that you can add in your filter result screen. But the value it displays is actually "remaining time against the SLA goal". Is this what you need?

If you are looking for how long an issue actually took to be resolved, then that is a completely different metric. In this case, as already suggested, you could try adding a custom field or exporting the data and calculating the resolution time in Excel. Alternatively, an easier option would be to look for an app on the Atlassian Marketplace.

If you are willing to try an app, our Great Gadgets app offers several gadgets that can calculate the time to resolution. For example, the Control Chart gadget can be configured to calculate and display issues based on their resolution time.

In addition, its Data tab provides a detailed report listing all the issues along with their duration, representing the time to resolution. It highlights SLA breaches in red-color.

The app offers some other gadgets that can display issues by their time to resolution. See more details in this article: https://community.atlassian.com/forums/App-Central-articles/An-effective-dashboard-for-Service-Desk-and-Customer-Support/ba-p/2360369

Hope this helps.

Danut.

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Hey @Nugzari Turashvili

Relying solely on averages can be highly misleading because they mask the real story of your team's performance.

A single outlier ticket that was blocked or waiting on a customer for weeks can skew your average upward, making it look like your team is slow when in reality they resolved every other ticket instantly.

Timepiece - Time in Status for Jira solves this exact problem by letting you shift from high-level aggregates to detailed, issue-by-issue clarity in just one click.

How does Timepiece solve the problem?

Well, instead of showing you a single rolled-up number, Timepiece can track the full lifecycle of each issue. Here is how simple it is:

Define Your Scope: Choose your target project or sprint.

Use the Duration Between Statuses Report: Set your metric to count from "Issue Creation" to "Resolved/Closed".

Switch from Average to List: Next to your report type, locate the List / Aggregation menu and select List.

This instantly generates a clean table displaying every single ticket in its own row alongside its precise resolution time.

No complex JQL, no fragile automation rules, and no manual Excel exports required.

Not just generating a report, Timepiece also helps you with these features:

Custom Business Calendars: Native Jira reports count time 24/7, which unfairly inflates your resolution times over weekends, nights, and holidays. With Timepiece, you can configure custom calendars to ensure your resolution metrics only measure actual working hours.

Interactive Drill-Downs: If you ever decide to use average trend charts in the future, you don't have to guess why a number is high. Every number on a Timepiece report is interactive; simply click it to instantly pop up the exact list of issues behind that average so you can isolate outliers in seconds.

You can find Timepiece - Time in Status for Jira on the Atlassian Marketplace.

Full disclosure, I'm on the team that builds Timepiece. Hope this helps!

Best,
Birkan

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thanks a lot 🤝

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If you need per-ticket resolution time instead of an average, the built-in JSM reports won't really get you there — Time to resolution just shows the average for each period.

Simplest option: build a JQL filter for resolved tickets, export to CSV with Created and Resolved dates, and calculate the duration yourself in Excel or Sheets.

If you'd rather keep it all in Jira, you could set up a custom field and use Automation to calculate and store the resolution time per ticket when it's resolved, then pull that into your issue search or dashboard.

One thing worth flagging — if you need SLA-based time to resolution (accounting for business hours, pauses, etc.), that's a bit different from just Created to Resolved.

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which report is a accurate for time to resolution

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