Jira is one of the most powerful tools for managing software development and delivery. But when teams start asking deeper questions:
Where exactly are we losing time?
Why do bugs get stuck?
How predictable is our delivery?
Jira’s native reports often don’t go far enough.
That’s where time-based dashboards come in.
In this article, we’ll explore:
What Time Metrics Tracker is and why it exists
Why time-based metrics matter more than ever
How custom dashboards help teams see real bottlenecks
What makes Time Metrics Tracker different from Jira’s built-in reports
How teams use it in real workflows
And why installing a trial is often the fastest “aha” moment
If you want Jira dashboards that show how work really flows — not just where it ends up, this guide is for you.
Most Jira dashboards focus on counts:
Number of open issues
Issues resolved per sprint
Backlog size
Velocity
These metrics answer “how much”, but not “how long”.
Time-based questions sound more like this:
How long do bugs stay in In Progress before moving to QA?
Where do issues wait the longest?
How much time is spent actively working vs. waiting?
Which workflow stage is slowing releases down?
Are we improving cycle time or just moving tickets faster?
Without time in status and time between statuses, these questions are almost impossible to answer accurately.
Time Metrics Tracker (Time Between Statuses) is a Jira Cloud app that measures how long work items spend in each stage of your workflow and how long transitions actually take.
Instead of guessing or exporting data to spreadsheets, Time Metrics Tracker automatically calculates:
Time in Status
Time Between Statuses
Cycle Time
Lead Time
Wait Time
Resolution Time
…and makes those metrics available in reports, dashboards, and issue-level views.
In short:
Time Metrics Tracker turns Jira status changes into actionable time insights.
Before we dive into dashboards, let’s clarify some core concepts.
The total amount of time an issue spends in a specific status (e.g., In Progress, QA, Blocked).
You can measure:
First time in status
Last time in status
Total time across all transitions
The duration between two workflow statuses (e.g., In Progress → QA).
This helps teams understand handoffs, delays, and workflow friction.
Time from when work starts (often In Progress) to when it’s completed (Done).
Time from issue creation to completion.
Time when work is not actively progressing — often hidden in statuses like Waiting, Blocked, or Backlog.
Jira offers useful reports like:
Control Charts
Cumulative Flow Diagrams
Basic dashboards and filters
They’re great for high-level trends, but they have limitations:
❌ Limited visibility into individual workflow stages
❌ No flexible “first / last / total time” logic
❌ No clear breakdown of waiting vs. active time
❌ Hard to customize for different teams or workflows
❌ No real-time, status-to-status duration insights
For operational decisions — especially around bugs, delivery, and flow efficiency — teams need more precise time metrics.
This is where Time Metrics Tracker truly shines.
Time Metrics Tracker lets you calculate metrics based on:
Calendar time
Business hours
Custom work schedules (including holidays)
This ensures your dashboards reflect how your team actually works, not just clock time.
You can configure reports and dashboards to track:
Time in specific statuses (e.g., QA, Review, Blocked)
Time between key transitions
Cycle time per issue type
Lead time per project
First vs. last time in status (great for rework analysis)
This flexibility is critical for accurate dashboards.
Time Metrics Tracker provides dedicated dashboard gadgets, including:
Scatter plots are one of the most underrated — yet powerful — visualization tools for time-based analytics.
Each dot represents a Jira issue, plotted against:
Time in Status
Cycle Time
Lead Time
This immediately reveals:
outliers
unusually slow issues
hidden bottlenecks that averages don’t show
Average metrics can be misleading. One or two extremely slow bugs can:
block releases
inflate cycle time
hide systemic problems
Scatter plots make those issues impossible to ignore.
Identify bugs stuck in QA far longer than others
Detect tickets that break SLA expectations
Find rework patterns (issues bouncing back and forth)
Focus retrospectives on specific problematic issues
👉 Instead of asking “Why is our average cycle time high?”, teams ask:
“Why are these exact 5 issues so slow?”
That’s a huge shift.
Work-in-progress (WIP) is one of the strongest predictors of delivery speed — and also one of the hardest things to visualize properly.
The WIP Run Chart tracks:
how many issues are in progress
how WIP changes over time
how WIP correlates with delays and bottlenecks
High WIP almost always leads to:
longer cycle times
context switching
more waiting and rework
But without visualization, teams often feel the pain without understanding the cause.
Validate WIP limits
Compare sprint-to-sprint flow
Identify overload periods
Support data-driven process improvements
Instead of debating opinions in retrospectives, teams can say:
“Every time WIP goes above X, cycle time increases.”
That’s actionable insight.
The Agile Metrics Dashboard brings multiple time-based metrics together into a single, coherent flow view.
Cycle Time trends
Lead Time trends
Time in Status breakdowns
Distribution charts (not just averages)
Most dashboards focus on output (how much was done).
This one focuses on flow (how work moves through the system).
That distinction is critical.
Engineering managers
Product managers
Delivery leads
Agile coaches
This dashboard answers questions like:
Are we becoming more predictable?
Which workflow stages slow us down the most?
Are recent process changes actually helping?
Color-coded warning and critical thresholds make delays instantly visible — no spreadsheet required.
Time in In Progress
Time in QA
Time between Open → Done
Highlight bugs exceeding SLA thresholds
👉 Perfect for QA leads and engineering managers.
Average and median cycle time
Trend of lead time over time
Outliers that break predictability
👉 Ideal for product managers and delivery teams.
Compare time spent in each workflow stage
Identify where issues wait the longest
Validate whether process changes actually help
👉 Great for continuous improvement and retrospectives.
Teams often start with manual tracking or exports to Excel. But as projects grow, that approach breaks down.
With Time Metrics Tracker, teams gain:
✅ Real-time insights — no manual exports
✅ Accuracy — metrics based on actual Jira transitions
✅ Scalability — works across teams and projects
✅ Transparency — dashboards anyone can understand
✅ Actionability — spot problems before deadlines slip
Or put simply:
Less reporting. More understanding. Faster improvement.
Dashboards aren’t just about visibility — they’re about behavior.
When teams can see:
where work slows down,
how long bugs really wait,
and which stages cause delays,
they stop guessing and start improving.
Time Metrics Tracker doesn’t replace Jira — it unlocks its hidden time dimension.
If you’ve ever asked:
Why are our bugs taking so long?
Where is work actually getting stuck?
Are we really improving delivery time?
…then it’s time to try Time Metrics Tracker
👉 Install the free trial from the Atlassian Marketplace, build your first time-based dashboard, and see your workflow in a completely new way.
Sometimes, one clear dashboard is all it takes to change how a team works.
Valeriia_Havrylenko_SaaSJet
Product Marketer
SaaSJet
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