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⚡ TL;DR — Jira shows you what your team is working on. These 6 reports reveal where work is slowing down, who is holding it, and whether your sprints are realistic — all grounded in workflow data Jira already captures. |
As a project manager, knowing what your team is working on is only half the picture. The harder questions are: How long is each issue actually taking? Where is work piling up? Are your delivery timelines based on data or optimism?
Jira already captures a timestamped record of every status transition your issues go through. Pair that workflow history with the right Jira time tracking reports, and those questions become answerable in seconds — without spreadsheets, exports, or guesswork.
This article covers:
A Jira time tracking report or time in status report is a data view that measures how long issues spend at each stage of your workflow. Rather than showing the current state of your board, it looks at the history of your issues — specifically, the timestamped record of every status transition Jira captures automatically as your team works.
This gives project managers a quantified picture of:
These are the numbers behind every decision a project manager makes:
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💡 Without a time tracking report, those decisions rest on judgment and experience. With one, they are grounded in actual data from your team's real workflow. |
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🔧 Time in Status Reports by RVS Softek (Atlassian Marketplace) provides 20+ report types built on the workflow history Jira already captures. All data stays inside your Jira instance — no external exports, no third-party data handling. Works on Jira Cloud and Jira Data Center. |
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📊 Report 1: Time in Status Report |
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Purpose |
Shows the total time each issue spent in every workflow status across its lifecycle. For every issue in your filtered set, you get a complete, status-by-status time breakdown — so you can see whether a ticket moved quickly through development but stalled in review, or has been sitting in QA far longer than expected. |
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Use Cases |
• Bottleneck detection — pinpoint exactly which status caused a delay before entering a retrospective • Pre-sprint review — filter to your last sprint and see which statuses consumed the most collective time • SLA monitoring — check whether critical issue types consistently exceed time thresholds in specific stages • Stakeholder communication — walk into escalation calls with a factual status-by-status breakdown, not an apology |
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📈 Report 2: Average Time in Status |
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Purpose |
Aggregates individual issue data to calculate the average time issues spend in each status across your entire filtered set. Gives you a team-level or project-level benchmark for how long each workflow stage typically takes. |
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Use Cases |
• Weekly or monthly process reviews — benchmark current sprint performance against last month • Sprint commitment sizing — base estimates on real average durations, not optimistic guesses • Cross-team comparison — compare workflow health across teams running similar work types • Definition of Done health checks — verify that each stage is completing within expected thresholds |
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📅 Report 3: Time in Status per Time Grain |
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Purpose |
Shows total status time within a defined date range, grouped by Day, Week, or Month. The trend view that answers whether your workflow improvements are working — or whether things are quietly getting slower. |
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Use Cases |
• Post-change measurement — did time in 'In Progress' actually drop after you introduced a clearer Definition of Ready? • Quarterly stakeholder reporting — show leadership how delivery velocity has trended over time • Seasonal pattern identification — spot recurring slowdowns that correlate with holidays, releases, or planning cycles • Continuous improvement evidence — demonstrate sprint-over-sprint workflow improvements with hard data |
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⏱️ Report 4: Time between Status Transitions |
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Purpose |
Measures how long issues take to move from one specific status to another. You define both the start and end status — set it from 'In Progress' to 'Done' for true cycle time, or from ticket creation to 'Done' for full lead time. |
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Use Cases |
• Sprint planning — ground commitments in real cycle time data from the last three sprints • Handoff delay measurement — run from 'In Review' to 'In QA' to quantify time wasted between team handoffs • Delivery variance analysis — if cycle times range from 2 days to 14 days, your estimates are unreliable regardless of the average • Lead time SLA reporting — measure the full customer-facing delivery duration end-to-end |
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👤 Report 5: Time with Assignee |
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Purpose |
Shows the total time each issue spent with each assignee during its lifecycle. If an issue was reassigned, time is split accurately across every assignee who held it — giving a clear picture of how work moves between people, not just statuses. |
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Use Cases |
• Workload balancing — identify team members who are consistently holding issues significantly longer than peers • Reassignment pattern analysis — understand where in the workflow issues are getting handed off and what each handoff costs • Capacity planning — use actual assignee throughput data to size the next sprint more accurately • Individual coaching — surface data-backed observations for 1-on-1 conversations |
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🔍 Report 6: Time in Status per Assignee |
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Purpose |
Combines both dimensions — showing how long each issue spent in each specific status, broken down by who held the issue at that point. The intersection view that helps distinguish between a workflow problem affecting everyone and a pattern specific to one person or role. |
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Use Cases |
• Retrospectives with data — determine whether a bottleneck is team-wide or concentrated in one person or role • Role-based process analysis — are senior engineers getting stuck in approval stages more than others? That points to a process dependency, not a performance issue • Team comparison — compare workflow behaviour across team members working on similar issue types • Manager-level reporting — present evidence-based workflow health to leadership |
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PM Situation |
Best Report to Use |
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Explaining why a specific ticket is delayed |
Time in Status Report |
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Weekly workflow health check |
Average Time in Status |
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Proving a process change worked |
Time in Status per Time Grain |
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Building reliable sprint estimates |
Time between Status Transitions |
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Reviewing workload distribution |
Time with Assignee |
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Diagnosing a repeated bottleneck |
Time in Status per Assignee |
When you know your team's average cycle time and status duration from the last three sprints, sprint commitments stop being optimistic guesses and start being data-backed forecasts. The Time between Status Transitions report is the single best input for this.
When a delivery date slips, open a time tracking report, find exactly which status caused the delay, and walk into that conversation with a clear explanation. No apology — just data.
Instead of 'it felt like QA was slow this sprint,' you can show the team that QA averaged 3.1 days per issue, up from 1.8 days last sprint — and open a focused conversation about why.
The Time in Status per Time Grain report lets you track whether process changes are actually working across weeks and months, not just sprint to sprint. This is the report that turns improvement conversations into evidence.
The Time with Assignee and Time in Status per Assignee reports together give you actual throughput data per team member — far more useful for capacity planning than estimated points or gut instinct.
The Time in Status Reports plugin includes a Jira Dashboard Gadget that surfaces live workflow metrics without opening any report screen. Here is how to add it:
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✅ Works on Jira Cloud and Jira Data Center. All data remains inside your Jira instance — no external exports, no third-party data handling required. |
Rahul_RVS
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