--- title: Is there a relationship between cycle time and PR... description: An analysis of PR cycle time versus PR throughput data from 500+ DX customers (January-July 2026) finds that cycle time is not a reliable standalone predictor... canonical: https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Is there a relationship between cycle time and PR throughput? | daily.dev og:description: An analysis of PR cycle time versus PR throughput data from 500+ DX customers (January-July 2026) finds that cycle time is not a reliable standalone predictor... og:url: https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b og:image: https://api.daily.dev/og/posts/oTSUpUc7B.png og:image:alt: Is there a relationship between cycle time and PR throughput? og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Is there a relationship between cycle time and PR throughput? **[Engineering Enablement](https://daily.dev/sources/engineering_enablement)** · 5 min read · 4 upvotes · 0 comments ## Summary An analysis of PR cycle time versus PR throughput data from 500+ DX customers (January-July 2026) finds that cycle time is not a reliable standalone predictor of throughput overall. Using quantile regression, the relationship is negligible for low-throughput organizations (25th percentile) but becomes progressively stronger and statistically significant at the median, 75th, and 90th percentiles. Around a 17-hour cycle time, median throughput begins to decline more sharply, suggesting this as a useful inflection point rather than a universal target. The takeaway is that high-throughput teams are most sensitive to cycle time slowdowns, while low-throughput teams likely face bottlenecks elsewhere, such as PR size, reviewer availability, or organizational context. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Is there a statistically significant relationship between PR cycle time and PR throughput? It depends on the organization's throughput level. Analysis of data from over 500 organizations found no significant relationship at the 25th percentile of throughput (p=0.366), but a significant negative relationship at the median (p=0.0008, β=-4.0) and much stronger negative relationships at the 75th and 90th percentiles (β=-11.7 and β=-12.8, both p=0.000). High-throughput teams are far more sensitive to slow cycle times than low-throughput teams. _daily.dev surfaces developer productivity research like this for teams deciding which metrics actually predict throughput._ ### At what PR cycle time does throughput start to decline? Around 17 hours is the inflection point where median throughput begins to decline as cycle time increases further. Below that mark, throughput stays fairly steady regardless of cycle time, meaning reducing cycle time may not meaningfully boost output for most teams. Beyond 17 hours, longer review cycles start limiting output for teams that otherwise have the capacity to deliver more. _teams tuning PR review workflows can track findings like this 17-hour threshold on daily.dev._ ### What is Little's Law and how does it apply to software team pull request workflows? Little's Law is a queuing theory theorem relating work in progress, throughput, and cycle time, showing that when work volume and type stay consistent, faster-moving work through a process can raise throughput. For software teams, this maps to open pull requests as WIP, merged PRs per period as throughput, and time from development to merge as cycle time. _engineers reasoning about workflow bottlenecks can follow deeper dives on metrics like these via daily.dev._ ## Similar posts on daily.dev - [The gap between code velocity and trust is growing](https://daily.dev/posts/the-gap-between-code-velocity-and-trust-is-growing-3s1bg92sd) · Engineering Enablement · 0 upvotes · 0 comments - [5 key takeaways from the 2026 State of Software Delivery: Why AI isn’t shipping faster](https://daily.dev/posts/5-key-takeaways-from-the-2026-state-of-software-delivery-why-ai-isn-t-shipping-faster-oktnhjrhb) · CircleCI · 4 upvotes · 0 comments - [EP186: Latency vs. Throughput](https://daily.dev/posts/ep186-latency-vs-throughput-4gkjqtoy1) · ByteByteGo · 10 upvotes · 0 comments - [When Impressive Performance Gains Do Not Matter](https://daily.dev/posts/when-impressive-performance-gains-do-not-matter-cxqe3fpey) · Lobsters · 0 upvotes · 0 comments - [Is Your CI/CD Tool Helping or Hindering Performance?](https://daily.dev/posts/is-your-ci-cd-tool-helping-or-hindering-performance--ukvg1azph) · JetBrains · 1 upvotes · 0 comments --- Tags: [#productivity](https://daily.dev/tags/productivity), [#leadership](https://daily.dev/tags/leadership), [#code-review](https://daily.dev/tags/code-review), [#dora-metrics](https://daily.dev/tags/dora-metrics) [View this post on daily.dev](https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Is there a relationship between cycle time and PR throughput?","url":"https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b"},"datePublished":"2026-08-19T10:05:44.020Z","dateModified":"2026-09-14T06:30:31.387Z","description":"An analysis of PR cycle time versus PR throughput data from 500+ DX customers (January-July 2026) finds that cycle time is not a reliable standalone predictor...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/5cfe3801efd9761cc6f6f339e541eac2?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/5cfe3801efd9761cc6f6f339e541eac2?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Engineering Enablement","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Engineering Enablement","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/3c8216b036d34c1cbe1678385355f35d","url":"https://daily.dev/sources/engineering_enablement"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":4},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"productivity,leadership,code-review,dora-metrics","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Engineering Enablement","item":"https://daily.dev/sources/engineering_enablement"},{"@type":"ListItem","position":3,"name":"Is there a relationship between cycle time and PR throughput?"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/is-there-a-relationship-between-cycle-time-and-pr-throughput--otsupuc7b#faq","mainEntity":[{"@type":"Question","name":"Is there a statistically significant relationship between PR cycle time and PR throughput?","acceptedAnswer":{"@type":"Answer","text":"It depends on the organization's throughput level. Analysis of data from over 500 organizations found no significant relationship at the 25th percentile of throughput (p=0.366), but a significant negative relationship at the median (p=0.0008, β=-4.0) and much stronger negative relationships at the 75th and 90th percentiles (β=-11.7 and β=-12.8, both p=0.000). High-throughput teams are far more sensitive to slow cycle times than low-throughput teams. daily.dev surfaces developer productivity research like this for teams deciding which metrics actually predict throughput."}},{"@type":"Question","name":"At what PR cycle time does throughput start to decline?","acceptedAnswer":{"@type":"Answer","text":"Around 17 hours is the inflection point where median throughput begins to decline as cycle time increases further. Below that mark, throughput stays fairly steady regardless of cycle time, meaning reducing cycle time may not meaningfully boost output for most teams. Beyond 17 hours, longer review cycles start limiting output for teams that otherwise have the capacity to deliver more. teams tuning PR review workflows can track findings like this 17-hour threshold on daily.dev."}},{"@type":"Question","name":"What is Little's Law and how does it apply to software team pull request workflows?","acceptedAnswer":{"@type":"Answer","text":"Little's Law is a queuing theory theorem relating work in progress, throughput, and cycle time, showing that when work volume and type stay consistent, faster-moving work through a process can raise throughput. For software teams, this maps to open pull requests as WIP, merged PRs per period as throughput, and time from development to merge as cycle time. engineers reasoning about workflow bottlenecks can follow deeper dives on metrics like these via daily.dev."}}]} ```