Sprint retros based on what actually happened, not what people remember
Doe pulls Jira velocity and carry-over data, GitHub PR review turnaround by reviewer, and CI failure rates, then writes the retro to Confluence with multi-sprint trends, bottleneck analysis, and action items with suggested owners.
Sprint completion data from Jira, PR review metrics from GitHub, and CI pipeline stats analyzed for patterns like review bottlenecks, estimation drift, and flaky tests. The retrospective lands in Confluence with velocity trends, carry-over analysis, and specific action items.
What changes
| Dimension | Before | With Doe |
|---|---|---|
| Retro data source | Memory and whoever speaks up | Jira velocity, GitHub PR metrics, and CI pipeline data |
| Pattern identification | Same vague complaints sprint after sprint | Specific bottlenecks identified with numbers and trends |
| Action item quality | "Communicate better" and "plan more carefully" | "Redistribute PR load from Reviewer X" and "Fix flaky checkout test" |
| Prep time | 30-60 minutes pulling data manually | Retro doc ready in Confluence before the meeting starts |
How Doe builds the sprint retrospective
JiraSprint 14 closed with 34 of 42 story points completed (81% velocity). 8 tickets carried over. 3 tickets were in "In Review" for 4+ days. 2 tickets re-opened after QA. Average ticket cycle time: 4.2 days (up from 3.1 last sprint).
GitHub47 PRs merged during the sprint. Average review turnaround: 26 hours (up from 18 hours last sprint). 3 PRs waited 4+ days for first review (all assigned to the same reviewer). CI failure rate: 12% (8 of 67 pipeline runs). Most common failure: flaky integration test in checkout module.
3 patterns: review bottleneck on one team member (assigned 14 of 47 PRs), estimation accuracy declining (actual exceeded estimates by 34% vs 12% last sprint), and the flaky checkout test caused 6 CI re-runs costing ~3 hours. Recommended: redistribute PR review load, recalibrate estimation for backend tickets, fix or quarantine the flaky test.
ConfluenceSprint 14 retrospective written with velocity trends (3-sprint graph), carry-over analysis, review bottleneck data, and 3 specific action items with suggested owners.
Retros are driven by whoever talks loudest
Retros are driven by whoever talks loudest and whatever happened most recently. Nobody pulls actual velocity data. The same process problems persist quarter after quarter because the retro is based on feelings, not evidence.
Sprint 14 had 8 carry-over tickets. In the retro, the team blamed "scope creep." But the data shows 3 of those tickets were blocked on PR reviews that sat for 4+ days. The other 5 were estimated at 2 points but took 8. The actual problem is review bottlenecks and bad estimation, not scope creep.
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Describe what you need
“At the end of each sprint, pull completion and carry-over data from Jira, PR review turnaround and CI failure rates from GitHub, and write a retrospective to Confluence with velocity trends, identified patterns, and specific action items with owners.”
It runs on schedule
Runs at the end of each sprint (biweekly). Retro doc appears in Confluence before the meeting.
Sprint Retrospective from Real Data FAQ
No. It replaces the data-gathering and pattern-finding that usually happens (or doesn't happen) before the meeting. The team still discusses, but they start from evidence instead of memory.
Related workflows
Stop doing the work your tools should do for you.
Set it up once. Doe runs it every time.
