Jira Metrics

Anatomy of a ticket

Range:
Validation & drill-down view. Use this page to understand exactly how each flow metric is computed for one project, and where the AI cohort differs from the human cohort. Headline numbers on /flow and /overview roll up the same formulas across all projects. Hover any lane label for the formula and a sample-size note.

Anatomy of a ticket โ€” PDO

Window: 30d ยท All 10 ยท AI 0 ยท Human 10

Jira Flow Lead Time (raw / wall-clock)
193hn=10AIno dataH193hn=10
Lead Time (active, รท pauses)
145hn=10AIno dataH145hn=10
Time to Ready
0.0hn=10AIno dataH0.0hn=10
Cycle Time (raw / wall-clock)
117hn=9AIno dataH117hn=9 ยท directional
Lead Time for Changes
Not enough data in this window
Cycle Time (active, รท pauses)
69hn=9AIno dataH69hn=9 ยท directional
Time to First PR
Not enough data in this window
PR Review Duration
Not enough data in this window
Created
Ready
In Progress
In Review
Done
Deployed

AI vs Human comparison

Bars proportional within each row (max = 100%). ฮ”% lower-is-better โ€” green = AI faster.

No lane has both AI and Human samples in this window. Try a longer range, or check that this project has AI-assigned tickets.

Not measurable (one cohort has zero samples):

  • ยทJira Flow Lead Time (raw / wall-clock) โ€” no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ยทLead Time (active, รท pauses) โ€” no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ยทTime to Ready โ€” no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ยทCycle Time (raw / wall-clock) โ€” no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ยทCycle Time (active, รท pauses) โ€” no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ยทTime to First PR โ€” no tickets / PRs measurable in this window
  • ยทPR Review Duration โ€” no tickets / PRs measurable in this window
  • ยทLead Time for Changes โ€” no tickets / PRs measurable in this window

Cohort breakdown

โš  marker when AI or Human cohort sample size is below 10.

MetricAll p50nAI p50nHuman p50nฮ” (AI vs Human)
Jira Flow Lead Time (raw / wall-clock)193h10โ€”0 โš 193h10โ€”
Lead Time (active, รท pauses)145h10โ€”0 โš 145h10โ€”
Time to Ready0.0h10โ€”0 โš 0.0h10โ€”
Cycle Time (raw / wall-clock)117h9โ€”0 โš 117h9 โš โ€”
Cycle Time (active, รท pauses)69h9โ€”0 โš 69h9 โš โ€”
Time to First PRโ€”0โ€”0 โš โ€”0 โš โ€”
PR Review Durationโ€”0โ€”0 โš โ€”0 โš โ€”
Lead Time for Changesโ€”0โ€”0 โš โ€”0 โš โ€”

All = every measurable ticket / PR in the window. AI = agent-owned cohort (ticket assignee or PR author is an active agent at completion). H = human cohort (everyone else, including unassigned). ฮ” compares AI vs Human p50 โ€” negative = AI faster.

Side metrics

Throughput / week
2.3
AI 0.0 ยท H 2.3
WIP โ€” Active now
10
Blocked 6
Bug rate / week
0.2
AI participation
0%
AI 0 / 10
Top bottleneck
In Progress
median 117h
Deploys / week
0.0
ADO-style
Change failure rate
โ€”
no ADO mapping
PR acceptance
โ€”
no PRs in window

๐Ÿง  AI deep analysis

Generate an LLM-driven explanation of WHY the AI cohort is faster / slower on each lane. Cites specific tickets from the evidence pack, suggests next steps.

Active variants use business hours minus pause statuses (same formula as the per-project Cycle / Lead pages). Raw variants are pure wall-clock. AI cohort = ticket assignee (or PR author) is an active agent at completion time. Sample-size suppression marks values directional only when AI or Human cohort drops below 10 โ€” the value is still shown for context but trust it less.

2 auto-filtered zombies (2 direct ยท 2 old) โ€” Rules