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Beyond the DORA Frameworks

In this report, 300+ CTOs, VPEs and Eng. Managers share their insights and step-by-step guidance for running a data-driven engineering practice. Inside you’ll find:
Real-life Use Cases: How leaders are driving Developer Productivity impact using engineering metrics.
Engineering Benchmarks: Data insights from a 2025 study of 6.1+ million PRs from 3,000+ organizations worldwide.
What Makes a Successful Eng. Team?: What elite engineering teams have in common and the role of metrics in their success.
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What's Inside?

Scope: We got 334 full responses, from people with a variety of roles in tech.

DevEx Survey Results

We polled 300+ CTOs, VPEs, and Engineering Managers – hailing from start-ups and Fortune 500 companies alike. Inside, you’ll find their answers to the following questions:
  • How often does your team deliver projects on time?
  • How much time does your team spend on maintenance / tech debt?
  • Do you use engineering metrics on your team (DORA, SPACE, etc)?
Ship Code Often: Shipping frequently displays solid correlations with time spent on maintenance.

6 Practices of Elite Engineering Teams

Elite engineering teams have 6 main habits in common. In this report, you’ll discover insights like:
  • Remote teams collaborate more seamlessly, and tend to wait for others 10% less.
  • Engineering teams that prioritize clear requirements have 34% more projects shipped on time.
  • Teams who ship multiple times a day vs. a few times per month are 19.4% happier with their dev practices.
LinearB Labs: We recommend using these categories and investment percentages as a starting point.

Investment Benchmarks Insights

See why intentionally allocating engineering time across various categories (e.g. KTLO vs Improvements vs New Features) has strong positive correlation with several traits:
  • +6.7% focus time (3.16 vs 2.96)
  • +22% time spent as planned (55% vs 45%)
  • +24% projects delivered on time (62% vs 50%)
  • +14.7% happiness about dev practices (3.57 vs 3.11)
The Pyramid of Engineering Maturity

Getting Started with Engineering Metrics

Inside, you’ll find step-by-step guidance on how to get started with data-driven engineering practices using the Pyramid of Engineering Maturity:
  • Transparency (foundation) — Being aware and creating feedback loops
  • Intent (middle) — Intentional allocation and clear direction
  • Speed (top) — Only valuable when built on the other two layers
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