No. First-pass rate can show how often a defined task or check succeeds on its first attempt, but it cannot establish whether engineering delivers valuable changes quickly, safely, or predictably. Use it as a local process signal, then assess delivery with measures of flow and operational stability, interpreted in the context of a specific application or service.
What first-pass rate tells you—and what it leaves out
First-pass rate has no universal software-engineering definition established by the sources cited here. Its meaning depends on what work is counted and what qualifies as a pass. For example, a team might track the share of a specified review, test, or workflow step that succeeds without another attempt. That can help identify friction or recurring defects in that step.
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But a local pass rate does not show how long a change takes to reach production, how often deployments happen, or what happens when a deployment causes a problem. A team could improve a narrowly defined first-pass rate while still having infrequent deployments, long delivery times, slow recovery, or unplanned work to address production incidents. This is a scope-based inference, not a finding that applies empirically to every team.
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DORA describes its software delivery performance metrics as focusing on “a team’s ability to deliver software safely, quickly, and efficiently.” Its measures cover delivery outcomes that a single first-pass score does not capture. DORA’s current metrics guide
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Which measures give a fuller picture of delivery?
DORA’s current guidance identifies five measures and groups them into throughput and instability. Use them together rather than treating any one measure as a complete score.
| What to understand | DORA measure | What it describes |
|---|---|---|
| Flow | Change lead time | Elapsed time from a change being committed to version control until it is deployed to production. |
| Flow | Deployment frequency | How often deployments happen over a chosen period, or the time between deployments. |
| Operational stability | Change fail rate | The ratio of deployments that require immediate intervention after deployment, such as a rollback or hotfix. |
| Operational stability | Deployment rework rate | The ratio of unplanned deployments made because of a production incident. |
| Operational stability | Failed deployment recovery time | How long it takes to recover from a deployment failure that requires immediate intervention. |
These definitions come from DORA’s software delivery performance metrics guide. The framework’s terminology has evolved; DORA’s history of its delivery metrics explains that development. When reporting results, use the current definitions rather than assuming that older labels or formulations are interchangeable.
How to use first-pass rate without mistaking it for delivery performance
- Define the unit. State exactly what counts as one item of work: for example, a specified check or workflow step. Do not compare rates whose underlying units differ.
- Define a pass. Explain the condition that makes an attempt successful and what counts as another attempt. Without that rule, the percentage is ambiguous.
- Pair it with delivery measures. Use change lead time and deployment frequency to examine flow; use change fail rate, deployment rework rate, and recovery time to examine stability.
- Name the scope and window. DORA recommends applying its measures to one application or service at a time and interpreting them in context. Specify what counts as a deployment or failure and the period being measured.
- Look at trends, not a universal ranking. Compare a team’s measures over time under consistent definitions. A single score cannot explain the work’s context or prove that one team delivers better than another.
Delivery metrics do not prove customer value
Delivery measures describe mechanics such as speed, frequency, and operational disruption. They do not, by themselves, establish whether shipped changes produced customer or business value. The Software Engineering Metrics overview of the DORA framework makes this scope limitation explicit; it is secondary context, not official DORA guidance. To understand outcomes, teams also need evidence tied to the goals and users of the work.
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If the question is whether a particular step is working smoothly, a clearly defined first-pass rate may be useful. If the question is whether engineering delivers changes quickly and safely, it is insufficient alone: combine flow and stability measures, specify the application or service and measurement window, and assess value separately. DORA’s 2024 report, for example, asked respondents how many deployments in the preceding six months were unplanned and made to address a user-facing bug. That six-month span describes the survey question; it is not a universal required measurement window. DORA’s 2024 report
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