A simple automatable metric for dev-time savings

WHAT THIS TESTS This checks whether you can identify a lean, automatable metric rather than an elaborate study, while still being defensible as a time-savings signal.

A GOOD ANSWER COVERS Pick a metric a script can compute from existing artifacts. A strong option is component coverage: scan each feature team's codebase for imports and usage of design-system components versus bespoke ones, and report the percentage built from the system. Higher coverage means more reuse and less custom UI code written, a direct proxy for saved development time. You can compute it nightly via static analysis with no manual input. Reasonable alternatives include cycle time from ticket start to merge for UI work, or the volume of new UI code written per feature, both lower when teams reuse components. Strengthen the story by comparing high-adoption teams against low-adoption ones, or the same team before and after adoption, and translate reuse into rough hours saved. Keep it simple, automatable, and repeatable so it can be tracked over time without manual effort.

COMMON WRONG ANSWERS Choosing a metric that quietly needs surveys or manual tagging. Using npm download counts as proof of productivity. Picking something not actually automatable. Confusing activity with saved time.

LIKELY FOLLOW-UPS How do you convert coverage into hours saved? Why is coverage better than downloads? What confounders affect cycle time?

ONE CONCRETE EXAMPLE A nightly script scans a feature team's repo and finds 65 percent of UI components come from the design system, up from 30 percent last quarter. Since reused components need no rebuilding, you estimate the avoided custom work and present rising coverage as evidence the system is cutting development time.