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 — PU

Window: 30d · All 79 · AI 0 · Human 79

Jira Flow Lead Time (raw / wall-clock)
191hn=79AIno dataH191hn=79
Lead Time (active, ÷ pauses)
143hn=79AIno dataH143hn=79
Time to Ready
126hn=33AIno dataH126hn=33
Cycle Time (raw / wall-clock)
63hn=63AIno dataH63hn=63
Lead Time for Changes
Not enough data in this window
Cycle Time (active, ÷ pauses)
36hn=63AIno dataH36hn=63
Time to First PR
150hn=1AIno dataH150hn=1 · directional
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%). Δ% lower-is-better — 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):

  • ·Jira Flow Lead Time (raw / wall-clock) — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·Lead Time (active, ÷ pauses) — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·Time to Ready — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·Cycle Time (raw / wall-clock) — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·Cycle Time (active, ÷ pauses) — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·Time to First PR — no AI cohort samples (no completed tickets with an AI assignee, or no PRs by AI authors)
  • ·PR Review Duration — no tickets / PRs measurable in this window
  • ·Lead Time for Changes — no tickets / PRs measurable in this window

Cohort breakdown

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

MetricAll p50nAI p50nHuman p50nΔ (AI vs Human)
Jira Flow Lead Time (raw / wall-clock)191h79—0 ⚠191h79—
Lead Time (active, ÷ pauses)143h79—0 ⚠143h79—
Time to Ready126h33—0 ⚠126h33—
Cycle Time (raw / wall-clock)63h63—0 ⚠63h63—
Cycle Time (active, ÷ pauses)36h63—0 ⚠36h63—
Time to First PR150h1—0 ⚠150h1 ⚠—
PR Review Duration—0—0 ⚠—0 ⚠—
Lead Time for Changes—0—0 ⚠—0 ⚠—

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). Δ compares AI vs Human p50 — negative = AI faster.

Side metrics

Throughput / week
18.4
AI 0.0 · H 18.4
WIP — Active now
127
Blocked 32
Bug rate / week
9.3
AI participation
0%
AI 0 / 79
Top bottleneck
New
median 21.7d
Deploys / week
—
no ADO mapping
Change failure rate
—
no ADO mapping
PR acceptance
—
no PRs in window

🧠 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 — the value is still shown for context but trust it less.

15 auto-filtered zombies (8 idle · 11 direct · 9 old) — Rules