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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A high first-pass rate measures gate performance, not end-to-end delivery. First-pass rate counts changes that pass their first recorded attempt at a named gate; delivered share asks how many changes in a defined started-work cohort reached delivery by a stated observation date. Because the measures use different outcomes and may use different populations, one cannot stand in for the other.
What first-pass rate measures
First-pass rate is a gate-specific measure: the number of changes that pass their first recorded attempt at that gate divided by the number of changes with a recorded first attempt there. The gate and attempt definition matter. A rate for implementation checks does not mean the same thing as a rate for code review or production readiness.
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For example, a team should specify whether “first attempt” means the first review submission, the first automated test run, or another recorded event, and whether a pass requires every blocking check to succeed. Without those rules and the denominator, the percentage is difficult to interpret or reproduce.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsWhat delivered share measures
Delivered share measures a cohort outcome: changes that reached a defined delivery event divided by all started changes in a specified cohort. The cohort can include work that never reached the first-pass gate. State the cohort dates and inclusion rules, what acceptance event counts as delivery, and the date at which the cohort is observed.
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The distinction is practical: a change can pass a gate and later fail to reach delivery, while another can miss its first pass, be repaired, and then ship. A gate result describes one point in the lifecycle; delivered share describes where the cohort ended up by the cut-off.
Report lifecycle outcomes separately
At the observation cut-off, show delivered, superseded, abandoned, and pending work as separate states. Pending work has no terminal disposition yet; classifying every open item as a failure would understate observed delivery without showing whether it will later ship. Conversely, calling all open work successful would overstate delivery.
For a hypothetical cohort of 100 changes, an earlier cut-off might show 40 delivered and 45 pending; a later cut-off might show 58 delivered and 17 pending. These illustrative counts demonstrate why the observation date matters; they are not measured results or a maturity threshold. No particular time-to-delivery method or threshold is established here.
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Useful companion measures keep different outcomes distinct:
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- Repair cycles per started change: recorded repair cycles divided by started changes, with the repair event defined.
- Terminal non-delivery share: superseded or abandoned changes divided by started changes.
- Pending share: changes without a terminal state at the cut-off divided by started changes.
Build a traceable lifecycle record
Reliable interpretation depends on being able to follow each change from start through disposition. A baseline event record should include:
- A stable change identifier and timestamps for lifecycle events.
- Stage, work or risk class, and the named gate.
- Gate attempts and their outcomes, plus repair transitions and revisions.
- Final disposition at the observation cut-off: delivered, superseded, abandoned, or pending.
- For each finding, its disposition and any revision associated with resolving it.
Treat any proposed lifecycle as a starting point, not a universal workflow. Check how it handles rollback after delivery, rejection after approval, partial deployment, reopened work, and work that leaves the tracked system; add transitions if those cases occur locally.
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Why findings and repair counts need traceability
A reported combination of blocking review findings and zero recorded repair cycles does not establish whether repairs did or did not happen. A correction might have occurred before the measured gate, a change might have continued without a recorded repair event, or it might still be pending, superseded, abandoned, outside the tracked workflow, or delivered. Link each finding to its disposition and any relevant revision before drawing conclusions about repair demand or engineering capacity.
How to treat the reported percentages
James Smith’s AFT Group article, posted August 28, 2026, describes figures from an unavailable measurement draft: 91.7% first-pass rate, 52.2% delivered share of started work, and 63.3% blocking review findings. It also reports 0% requiring a second pass, zero repair cycles per started change, and 34.8% approved-plan coverage. The article says the underlying draft and raw counts were unavailable; gate definitions, cohort rules, observation window, delivery definition, collection methods, and source systems were not supplied.
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These are unaudited reported observations, not verified results or benchmarks. The evidence does not establish the numerators and denominators needed to reproduce them, so they should not be used to compare teams or periods. The figures also cannot resolve whether findings led to repairs or what happened to each affected change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use broader delivery metrics as context
DORA’s software delivery performance guidance describes five metrics grouped around throughput and instability, and cautions against treating any one metric as the sole goal. Such measures can give a broader performance frame, but they do not define a team’s local gate, started cohort, lifecycle states, or delivery-acceptance event.
Tools can help collect or visualize events, but they do not settle those definitions automatically. DORA lists source-available delivery-metrics tools; Atlassian Jira documentation also describes work-item and delivery metrics, some of which require development or deployment integrations. Choose instrumentation only after deciding which events and cohort rules the team needs to capture.
Quick Recap
A practical reporting checklist
- Name the first-pass gate and define exactly what counts as an attempt and a pass.
- Publish its numerator and denominator: passed first attempts divided by changes with a recorded first attempt at that gate.
- Define the started-work cohort, its inclusion rules and dates, and the event that qualifies as delivery.
- Set and report the observation cut-off; break out delivered, superseded, abandoned, and pending counts.
- Keep repair cycles, terminal non-delivery, and pending share separate, with their own definitions and denominators.
- Retain linked change, finding, revision, transition, and disposition records so reported values can be audited.
- Compare teams or periods only when the underlying data and definitions are stable and available.
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