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 ā€” TAA

Window: 30d Ā· All 12 Ā· AI 9 Ā· Human 3

Jira Flow Lead Time (raw / wall-clock)
75hn=12AI75hn=9 Ā· directionalH90hn=3 Ā· directional
Lead Time (active, Ć· pauses)
75hn=12AI75hn=9 Ā· directionalH39hn=3 Ā· directional
Time to Ready
0.1hn=12AI0.1hn=9 Ā· directionalH0.1hn=3 Ā· directional
Cycle Time (raw / wall-clock)
56hn=12AI72hn=9 Ā· directionalH46hn=3 Ā· directional
Lead Time for Changes
Not enough data in this window
Cycle Time (active, Ć· pauses)
32hn=12AI72hn=9 Ā· directionalH11hn=3 Ā· directional
Time to First PR
17hn=1AI17hn=1 Ā· directionalHno data
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%). Ī”% lower-is-better ā€” green = AI faster.

Jira Flow Lead Time (raw / wall-clock)
Created ā†’ Done Ā· wall-clock hours including weekends and pauses
directionalView tickets (9/3) ā†’
AI
75h n=9 Ā· dir.
Human
90h n=3 Ā· dir.
Lead Time (active, Ć· pauses)
Created ā†’ Done Ā· business hours minus configured pause statuses
directionalView tickets (9/3) ā†’
AI
75h n=9 Ā· dir.
Human
39h n=3 Ā· dir.
Time to Ready
Created ā†’ first transition into a ready status (Selected / Approved / Ready)
directionalView tickets (9/3) ā†’
AI
0.1h n=9 Ā· dir.
Human
0.1h n=3 Ā· dir.
Cycle Time (raw / wall-clock)
First cycle-start status ā†’ Done Ā· wall-clock hours
directionalView tickets (9/3) ā†’
AI
72h n=9 Ā· dir.
Human
46h n=3 Ā· dir.
Cycle Time (active, Ć· pauses)
First cycle-start status ā†’ Done Ā· business hours minus pauses
directionalView tickets (9/3) ā†’
AI
72h n=9 Ā· dir.
Human
11h n=3 Ā· dir.

Not measurable (one cohort has zero samples):

  • Ā·Time to First PR ā€” no human cohort samples
  • Ā·PR Review Duration ā€” no tickets / PRs measurable in this window
  • Ā·Lead Time for Changes ā€” no tickets / PRs measurable in this window

Cohort breakdown

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

MetricAll p50nAI p50nHuman p50nĪ” (AI vs Human)
Jira Flow Lead Time (raw / wall-clock)75h1275h9 āš 90h3 āš ā€”
Lead Time (active, Ć· pauses)75h1275h9 āš 39h3 āš ā€”
Time to Ready0.1h120.1h9 āš 0.1h3 āš ā€”
Cycle Time (raw / wall-clock)56h1272h9 āš 46h3 āš ā€”
Cycle Time (active, Ć· pauses)32h1272h9 āš 11h3 āš ā€”
Time to First PR17h117h1 āš ā€”0 āš ā€”
PR Review Durationā€”0ā€”0 āš ā€”0 āš ā€”
Lead Time for Changesā€”0ā€”0 āš ā€”0 āš ā€”

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). Ī” compares AI vs Human p50 ā€” negative = AI faster.

Side metrics

Throughput / week
2.8
AI 2.1 Ā· H 0.7
WIP ā€” Active now
2
Blocked 0
Bug rate / week
0.7
AI participation
75%
AI 9 / 12
Top bottleneck
Ready For Review
median 8.3h
Deploys / week
ā€”
no ADO mapping
Change failure rate
ā€”
no ADO mapping
PR acceptance
ā€”
no PRs in window

šŸ§  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 ā€” the value is still shown for context but trust it less.