Five Non‑Traditional Metrics CTOs Should Track for Development Efficiency

To maximize delivery speed, CTOs should look beyond traditional KPIs and consider five non‑traditional metrics: commit‑to‑deploy time (CDT), build time, queue time, how often the master branch is red, and overall engineering overhead.

These metrics give a clearer picture of the development pipeline and highlight bottlenecks that may slow progress.

Before using them, remember five key points: measurement changes behavior, data quality matters (garbage in, garbage out), metrics must be contextual, they incur costs, and raw data alone does not drive improvement.

1. Commit‑to‑Deploy Time (CDT) measures the elapsed time from a code commit to its deployment. It includes integration, testing, and pre‑production steps, and can be tracked via timestamps in version control systems like Git. Shorter CDT indicates faster feedback loops and smaller, more frequent releases.

2. Build Time encompasses the duration of the build process plus any test execution and preparation (e.g., test database setup). Reducing build time often requires parallelizing tests, avoiding unnecessary setup/teardown, and improving test stability.

3. Queue Time is the waiting period before a build starts. It grows with larger teams and more concurrent changes. Keeping queue time low prevents developers from losing context while waiting and avoids costly idle time.

4. Master‑Branch Red Frequency tracks how often the main branch fails CI. A red master blocks releases and forces developers to wait for fixes, increasing risk and slowing delivery. Monitoring the percentage of time the master is red (or average red‑to‑green recovery time) helps maintain a healthy pipeline.

5. Engineering Overhead includes personnel costs, software licenses, cloud services, and the time engineers spend maintaining tools instead of building features. High overhead signals a need to reassess tool value and streamline processes.

The article also provides a rough cost model for build time, showing how even a ten‑minute delay can translate into significant productivity loss when multiplied across developers and weeks.

Finally, it suggests additional questions CTOs should ask, such as daily merge frequency, time the codebase remains release‑ready, test coverage levels, tool optimization, and potential speed gains from alternative infrastructure solutions.