Feature Bloat Calculus

Feature Bloat Calculus is the economic formula for determining when a feature's maintenance cost exceeds its value contribution. It quantifies the hidden tax of feature accumulation — the compounding cost that makes every new feature harder and more expensive to build. The formula considers three cost components: 1. **Direct Maintenance Cost**: The engineering hours spent maintaining the feature (bug fixes, compatibility updates, dependency management, test maintenance). This is typically 2-5% of original development cost per quarter. 2. **Opportunity Cost**: What else could those maintenance engineers be building? If 3 engineers spend 20% of their time maintaining a low-value feature, that's 0.6 FTE that could be building high-value new capabilities. 3. **Complexity Tax**: This is the compounding factor that most organizations miss entirely. Every feature in the codebase makes every other feature harder to maintain and every new feature harder to build. Adding feature #101 to a system doesn't just add feature #101's maintenance cost — it increases the maintenance cost of features #1-100. The Complexity Tax follows a roughly quadratic curve. A system with 50 features has approximately 1,225 potential interaction points (n × (n-1) / 2). A system with 100 features has 4,950 potential interaction points. Doubling features doesn't double complexity — it quadruples it. Feature Bloat Calculus quantifies this by comparing a feature's total cost (direct + opportunity + complexity) against its value contribution (revenue attribution, user engagement, strategic importance). When total cost exceeds value, the feature has "negative carry" — it's costing more to keep than it's worth. Features with negative carry should be evaluated through the Kill Switch Protocol for potential deprecation. The highest-negative-carry features should be killed first, as they free up the most capacity per removal.