# Engineering Benchmarks

Engineering Benchmarks define how engineering performance is evaluated, compared, and improved within Oobeya.

They provide a shared reference for **best practices**, **areas that need focus**, and **risk zones** across the software development lifecycle.

This page explains:

* How benchmarks work
* How performance levels are interpreted
* Which metrics are benchmarked, and how they are grouped.

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### What are Engineering Benchmarks?

Engineering Benchmarks are standardized performance thresholds applied to key engineering metrics in Oobeya.

They help organizations:

* Compare teams fairly within a league
* Identify improvement opportunities early
* Create a shared language between engineering teams and leadership
* Power gamification, insights, and AI-driven recommendations

Benchmarks are designed to **highlight patterns and risks**, not to enforce rigid targets.

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### Performance Levels

Each benchmarked metric is evaluated using **three performance levels**.

#### 🏆 Elite

* Best-in-class performance
* Healthy, scalable, and sustainable engineering practices
* Serves as a benchmark for other teams

#### ⚠️ Needs Focus

* Acceptable performance with clear improvement potential
* Early signals of inefficiency or hidden risk
* Often the highest ROI area for improvement

#### 🚨 At Risk

* Below expected performance levels
* Indicates delivery, quality, reliability, or cost risk
* Requires immediate attention

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### Benchmark Categories

Benchmarks are grouped into the following categories:

* **Project Management**
* **Development**
* **Code Review**
* **Delivery (DORA)**
* **Code Quality**
* **Application Performance**

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#### Project Management

<table><thead><tr><th width="331.15557861328125">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>Actual Reaction Time</td><td>&#x3C; 5 days</td><td>5–10 days</td><td>> 10 days</td></tr><tr><td>Cycle Time</td><td>&#x3C; 3 days</td><td>3–10 days</td><td>> 10 days</td></tr><tr><td>Lead Time</td><td>&#x3C; 7 days</td><td>7–14 days</td><td>> 14 days</td></tr><tr><td>Productivity</td><td>> 150%</td><td>100–150%</td><td>&#x3C; 100%</td></tr><tr><td>Predictability</td><td>> 90%</td><td>70–90%</td><td>&#x3C; 70%</td></tr><tr><td>Innovation Rate</td><td>> 75%</td><td>60–75%</td><td>&#x3C; 60%</td></tr></tbody></table>

#### Development

<table><thead><tr><th width="327.9208984375">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>Coding Efficiency</td><td>> 98%</td><td>90–98%</td><td>&#x3C; 90%</td></tr><tr><td>Rework Rate</td><td>&#x3C; 2%</td><td>2–10%</td><td>> 10%</td></tr><tr><td>Coding Days per Week</td><td>≥ 5 days</td><td>3–5 days</td><td>&#x3C; 3 days</td></tr></tbody></table>

#### Code Review

<table><thead><tr><th width="328.09375">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>Code Review Cycle Time</td><td>&#x3C; 1 day</td><td>1–7 days</td><td>> 7 days</td></tr><tr><td>Time to Merge</td><td>&#x3C; 3 days</td><td>3–30 days</td><td>> 30 days</td></tr></tbody></table>

#### Delivery (DORA)

<table><thead><tr><th width="327.017578125">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>Lead Time for Changes</td><td>&#x3C; 1 day</td><td>1–30 days</td><td>> 30 days</td></tr><tr><td>Deployment Frequency</td><td>Daily</td><td>Monthly or more</td><td>Less than monthly</td></tr><tr><td>Time to Restore Service</td><td>&#x3C; 1 day</td><td>1–30 days</td><td>> 30 days</td></tr><tr><td>Change Failure Rate</td><td>&#x3C; 15%</td><td>15–30%</td><td>> 30%</td></tr></tbody></table>

#### Code Quality

<table><thead><tr><th width="328.1072998046875">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>Technical Debt (New Period)</td><td>&#x3C; 3 days</td><td>3–30 days</td><td>> 30 days</td></tr><tr><td>Test Coverage (New Period)</td><td>> 80%</td><td>60–80%</td><td>&#x3C; 60%</td></tr><tr><td>Security Severity Blocker (Overall)</td><td>0 issues</td><td>1–5 issues</td><td>> 5 issues</td></tr><tr><td>Security Severity High (Overall)</td><td>0 issues</td><td>1–5 issues</td><td>> 5 issues</td></tr><tr><td>Security Severity Blocker (New Period)</td><td>0 issues</td><td>1–5 issues</td><td>> 5 issues</td></tr><tr><td>Security Severity High (New Period)</td><td>0 issues</td><td>1–5 issues</td><td>> 5 issues</td></tr><tr><td>Security Score (Overall)</td><td>A</td><td>B–C</td><td>D–E</td></tr><tr><td>Reliability Score (Overall)</td><td>A</td><td>B–C</td><td>D–E</td></tr><tr><td>Maintainability Score (Overall)</td><td>A</td><td>B–C</td><td>D–E</td></tr></tbody></table>

#### App Performance

<table><thead><tr><th width="327.80059814453125">Metric</th><th>Elite</th><th>Needs Focus</th><th>At Risk</th></tr></thead><tbody><tr><td>APDEX Score</td><td>> 0.85</td><td>0.70–0.85</td><td>&#x3C; 0.70</td></tr><tr><td>Error Rate</td><td>&#x3C; 1%</td><td>1–5%</td><td>> 5%</td></tr><tr><td>Avg. Response Time</td><td>&#x3C; 300 ms</td><td>300–1000 ms</td><td>> 1000 ms</td></tr></tbody></table>

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### How to Use Engineering Benchmarks

Engineering Benchmarks are most effective when used to:

* Detect risks **early**
* Guide conversations instead of enforcing targets
* Trigger insights and AI-driven recommendations.

Always interpret benchmarks in context, considering:

* Team maturity
* Product complexity
* Organizational constraints.

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### Related Topics

* [Gamification for Engineering KPIs](https://docs.oobeya.io/use-cases/gamification-for-engineering-kpis)
* AI Coach Insights
* [Engineering Metrics List](https://docs.oobeya.io/getting-started/metrics)
* [Delivery & DORA Metrics](https://docs.oobeya.io/deployment-analytics/dora-metrics-introduction)