Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsiTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
No. First-pass rate can show how often a defined task or check succeeds without another attempt, but it cannot by itself measure how quickly engineering delivers changes, how safely they reach production, or whether they create value. Use it as a local process signal alongside delivery and operational measures.
What first-pass rate tells you
“First-pass rate” has no single universal software-engineering definition established by the sources cited here. Its meaning depends on what is counted and what qualifies as a pass. A team might use it for work items accepted without revision, builds that pass a check on the first run, or another defined step. Those measures describe different things, so the unit and pass condition must be explicit before interpreting the result.
Even when consistently defined, the rate is narrow: it records whether a particular step succeeds without another attempt. It does not tell you how long a change takes to reach production or what happens after deployment.
Recommended Free Tools
What to measure for engineering delivery
DORA’s current software delivery performance guidance groups five measures into throughput and instability. It recommends applying them to one application or service at a time and interpreting them in context. Nathen Harvey, author of the guide, describes their focus as “a team’s ability to deliver software safely, quickly, and efficiently.” DORA’s guide to software delivery performance metrics defines them as follows:
#1 Best Overall
| Dimension | Metric | What it measures |
|---|---|---|
| Throughput | Change lead time | Elapsed time from a change being committed to version control until it is deployed to production. |
| Throughput | Deployment frequency | How often deployments happen over a chosen period, or the time between deployments. |
| Throughput | Failed deployment recovery time | Time to recover from a deployment failure that requires immediate intervention. |
| Instability | Change fail rate | The ratio of deployments requiring immediate intervention after deployment, such as a rollback or hotfix. |
| Instability | Deployment rework rate | The ratio of unplanned deployments made because of a production incident. |
DORA’s measures have evolved over time; its history of the metrics explains that development. The names and definitions above reflect its current guide, rather than treating an older set of measures as timeless.
Why a strong first-pass rate can still hide delivery problems
A team could raise a narrowly defined first-pass rate while deployments remain infrequent, changes take a long time to reach production, or failures take a long time to recover from. Production incidents might also lead to unplanned remedial deployments. These are possible mismatches in scope, not a claim that first-pass rate causes or predicts those outcomes: a local process signal and delivery outcomes answer different questions.
Likewise, DORA delivery measures describe delivery mechanics, not whether the shipped work produced customer or business value. A technical overview of the DORA metrics framework makes this distinction. Delivery measures can help explain how software moves to production; judging whether the work mattered requires separate evidence about its intended outcomes.
Free tools Windows power users keep installed
One-click scans. No signup required.
How to use first-pass rate alongside delivery metrics
- Define the measure. State the unit being counted, the event that qualifies as a pass, and what counts as a second attempt. Keep the definition stable when comparing periods.
- Pair it with flow measures. Use change lead time and deployment frequency to understand how quickly changes move through delivery and how often they reach production.
- Pair it with stability measures. Use change fail rate, deployment rework rate, and failed deployment recovery time to examine intervention, remedial work, and recovery.
- Set the measurement context. Identify the application or service, define what counts as a deployment and a failure, and name the time window. DORA’s 2024 report, for example, asked respondents about unplanned deployments made to address a user-facing bug during the six months before they answered. That was the survey’s reporting window, not a required universal window for teams measuring rework rate. The 2024 DORA report describes that survey measure.
- Interpret trends in context. Look at changes over time rather than treating one score as a universal ranking of teams. Consider what changed in the work or measurement conditions before drawing conclusions.
- Assess outcomes separately. To understand whether delivery produced value, relate shipped work to the customer or business outcome it was meant to affect; the delivery metrics alone cannot establish that result.
What the evidence does—and does not—establish
The cited sources provide no named, dated statistic validating first-pass rate as a measure of overall engineering delivery. DORA’s six-month survey wording is a timeframe for a particular question, not a performance statistic or a recommended measurement period for every organization. The defensible conclusion is about scope: first-pass rate describes a defined local step, while delivery performance requires measures of throughput and instability, interpreted in context.
Quick Recap
Best Value
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
