Benchmarks
Engineering benchmarks help teams understand how their performance compares to broader industry patterns across delivery speed, code quality, and development throughput. LinearB benchmarks are based…
Engineering benchmarks help teams understand how their performance compares to broader industry patterns across delivery speed, code quality, and development throughput.
LinearB benchmarks are based on large-scale analysis of engineering activity across thousands of development teams. These benchmarks provide useful context when interpreting metrics such as Cycle Time, PR Size, Review Depth, Deployment Frequency, and Change Failure Rate.
Benchmarks should not be treated as rigid targets. Instead, they provide reference points that help engineering leaders evaluate trends, identify outliers, and guide improvement efforts.
Available benchmarks
- LinearB Engineering Metrics Benchmarks – Industry benchmark data derived from analysis of millions of pull requests across thousands of development teams.
How benchmarks are typically used
- Contextualize performance – Understand whether metrics fall within typical industry ranges.
- Identify improvement opportunities – Spot workflow bottlenecks or quality risks.
- Support engineering leadership decisions – Use benchmark comparisons to guide planning and investment strategies.
Related resources
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