<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel>
    <title>DEV Community: Efe Kaya</title>
    <description>The latest articles on DEV Community by Efe Kaya (@efekaya).</description>
    <link>https://dev.to/efekaya</link>
    <image>
      <url>https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4091300%2F4e576102-6ac0-4a1a-b03c-d930d5a7175e.png</url>
      <title>DEV Community: Efe Kaya</title>
      <link>https://dev.to/efekaya</link>
    </image>
    <atom:link rel="self" type="application/rss+xml" href="https://dev.to/feed/efekaya"/>
    <language>en</language>
    <item>
      <title>DORA metrics explained — the four keys executives actually care about</title>
      <dc:creator>Efe Kaya</dc:creator>
      <pubDate>Sun, 23 Aug 2026 22:19:22 +0000</pubDate>
      <link>https://dev.to/efekaya/dora-metrics-explained-the-four-keys-executives-actually-care-about-lcf</link>
      <guid>https://dev.to/efekaya/dora-metrics-explained-the-four-keys-executives-actually-care-about-lcf</guid>
      <description>&lt;p&gt;Every engineering org measures something. Most measure the wrong thing — story points,&lt;br&gt;
velocity, lines of code — because those numbers are easy to collect and mean almost&lt;br&gt;
nothing to the person signing off on a platform investment. DORA's four keys are the&lt;br&gt;
closest the industry has to a standard instrument panel, and they're worth&lt;br&gt;
understanding properly because they're the vocabulary an executive already trusts,&lt;br&gt;
even if they've never heard the acronym.&lt;/p&gt;

&lt;h2&gt;
  
  
  The four keys
&lt;/h2&gt;

&lt;ul&gt;
&lt;li&gt;
&lt;strong&gt;Deployment frequency&lt;/strong&gt; — how often code ships to production.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Lead time for changes&lt;/strong&gt; — how long from commit to running in production.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Change failure rate&lt;/strong&gt; — what percentage of changes cause a failure in production.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Time to restore service&lt;/strong&gt; — how long an incident takes to resolve.&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Group them and a pattern appears: the first two measure &lt;strong&gt;throughput&lt;/strong&gt;, the last two&lt;br&gt;
measure &lt;strong&gt;stability&lt;/strong&gt;. That grouping is the entire point of the framework.&lt;/p&gt;

&lt;h2&gt;
  
  
  The finding that surprises people
&lt;/h2&gt;

&lt;p&gt;The intuitive assumption is that throughput and stability trade off — ship faster, break&lt;br&gt;
more things. DORA's research says the opposite: elite performers are strong on &lt;em&gt;both&lt;/em&gt;&lt;br&gt;
throughput and stability at the same time. Speed and safety aren't in tension; they're&lt;br&gt;
correlated, because the same practices that make deployment fast and frequent — small&lt;br&gt;
batches, automation, fast feedback — are the practices that make each individual&lt;br&gt;
change lower-risk.&lt;/p&gt;

&lt;p&gt;This matters enormously for how you pitch a platform internally. "We want to move&lt;br&gt;
faster" sounds like it's asking leadership to accept more risk. "We want to move&lt;br&gt;
faster &lt;em&gt;and&lt;/em&gt; reduce change failure rate" is a different conversation, and it's the&lt;br&gt;
honest one — a platform that only improves deployment frequency while degrading&lt;br&gt;
stability isn't actually elite by this model, it's just fast and fragile.&lt;/p&gt;

&lt;h2&gt;
  
  
  Translating the four keys into dollars
&lt;/h2&gt;

&lt;p&gt;Executives fund outcomes, not metrics, so the translation matters as much as the&lt;br&gt;
measurement:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;
&lt;strong&gt;Lead time reduction&lt;/strong&gt; → faster time-to-revenue for new features. A feature that
ships two weeks earlier starts earning two weeks earlier.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Change failure rate reduction&lt;/strong&gt; → fewer incident-hours and less firefighting cost,
which is real payroll spent on unplanned work instead of the roadmap.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Deployment frequency increase&lt;/strong&gt; → more experiments run per quarter. This one has
option value even before anyone monetizes it directly — the org that can ship ten
small tests learns faster than the org that can ship two big bets.&lt;/li&gt;
&lt;/ul&gt;

&lt;h2&gt;
  
  
  SPACE is the counterweight
&lt;/h2&gt;

&lt;p&gt;DORA measures the delivery pipeline. It says nothing about the humans running it,&lt;br&gt;
which is where the &lt;a href="https://queue.acm.org/detail.cfm?id=3454124" rel="noopener noreferrer"&gt;SPACE framework&lt;/a&gt; —&lt;br&gt;
Satisfaction, Performance, Activity, Communication, Collaboration — earns its place&lt;br&gt;
alongside it. A platform that improves DORA numbers while tanking developer&lt;br&gt;
satisfaction is buying short-term throughput with long-term attrition, and attrition&lt;br&gt;
is one of the most expensive line items an engineering org has. If you're only&lt;br&gt;
reporting DORA to leadership, you have half the picture — and it's the half that&lt;br&gt;
looks great right up until the team that made it look great starts leaving.&lt;/p&gt;

&lt;h2&gt;
  
  
  Start here, not with a custom scorecard
&lt;/h2&gt;

&lt;p&gt;Before building a bespoke productivity dashboard, get a DORA baseline. It's a known&lt;br&gt;
framework, it's already legible to whoever approves the platform budget, and it gives&lt;br&gt;
the before/after story a platform investment needs — "lead time went from 11 days to&lt;br&gt;
3" lands with an executive in a way that an internal happiness score never quite does&lt;br&gt;
on its own.&lt;/p&gt;

</description>
      <category>dora</category>
      <category>engineeringeconomics</category>
      <category>metrics</category>
    </item>
  </channel>
</rss>
