Framework for Measuring Engineering Capacity

This paper addresses a fundamental challenge for CTOs: how to accurately measure and forecast the productive capacity of a distributed engineering team. Traditional headcount-based planning is flawed, as it fails to account for critical variables that impact real-world output.

We propose a new quantitative model that incorporates not only team size but also psychometric data (from our AxiomCortex™ engine), operational friction (e.g., time-zone latency), and economic factors (like the 'Vacancy Tax'). The framework provides a more accurate, multi-dimensional view of team capacity, enabling leaders to make data-driven decisions about team composition, resource allocation, and strategic investments for predictable delivery.