Hi Atlassian Community! đź‘‹
I’m excited to share a small but powerful automation improvement we recently implemented to enhance sprint logging calculations within Jira. This method ensures that time tracking stays accurate and up-to-date — even as worklogs evolve throughout the sprint.
đź’ˇ The Challenge
When managing Agile teams, it’s common to rely on custom fields to represent calculated metrics — such as total logged hours per sprint. However, Jira’s default behavior doesn’t always automatically recalculate custom field values when a new worklog is added.
This meant we needed a dynamic way to keep the “Current Sprint Logging” value accurate in real-time — reflecting both the previously logged time and the latest worklog entry.
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⚙️ The Solution: Smart Value Calculation
To achieve this, we designed a simple yet effective calculation using Jira Automation’s smart values and expressions.
Here’s the logic we used:
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<code><span>{
"fields": {
"customfield_12345": "{{#=}} ({{issue.customfield_12345|0}} / 3600) + ({{issue.worklog.last.timeSpentSeconds}} / 3600) {{/}}h"
}
}<br><br>The customfield type is Epic Sum up.<br><br>The automation works in the following logic.<br><br>Trigger - Worklog Created<br>Action - Edit our Customfield, and adding logged time into it.<br><br>And via another automation we clear the field value, as soon as the new sprint starts.<br><br></span>
This small improvement made a big difference in our workflow — simplifying time tracking and ensuring data reliability throughout the sprint.
If you’re managing sprints and rely heavily on logged hours, I highly recommend implementing this pattern. It’s clean, efficient, and fully native to Jira’s automation engine.
🗣️ Have you tried similar time-tracking automations in your Jira projects?
I’d love to hear your feedback and alternative approaches in the comments below!
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