What is Feature Bloat Calculus?
Feature Bloat Calculus is a framework coined by Richard Ewing for determining when a feature's maintenance cost exceeds its value contribution. It quantifies the hidden tax of feature accumulation.
The formula factors in: direct maintenance hours, opportunity cost of those hours (what else the engineers could build), and the compounding effect on system complexity (each feature makes every other feature harder to maintain).
The key insight: every feature you add makes every future feature harder. This compounding effect is invisible in sprint-level metrics but devastating at the portfolio level. Feature Bloat Calculus makes this hidden cost visible so product teams can make rational keep/kill decisions.
Why It Matters
Feature Bloat Calculus quantifies what every experienced engineer feels intuitively: the system is getting harder to work with. It provides the economic argument for subtraction over addition.
Frequently Asked Questions
What is Feature Bloat Calculus?
A framework by Richard Ewing that calculates when a feature's maintenance cost exceeds its value contribution, factoring in direct costs, opportunity costs, and complexity compounding.
How do you use Feature Bloat Calculus?
For each feature: calculate maintenance hours × cost per hour, add opportunity cost of those hours, multiply by complexity factor. Compare to feature's revenue contribution. If cost > value, apply the Kill Switch Protocol.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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