Tournament-Based Performance Evaluation and Systematic Misallocation: Why Forced Ranking Systems Produce Random Outcomes

Abstract: Tournament-based compensation schemes with forced distributions represent a widely adopted class of relative performance evaluation mechanisms in technology and corporate environments. These systems mandate within-team ranking and fixed distributional requirements (e.g., bottom 15% terminated, top 15% promoted), ostensibly to resolve principal-agent problems through mandatory differentiation. We demonstrate through agent-based simulation that this mechanism produces systematic classification errors independent of implementation quality. With 994 engineers across 142 teams of 7, random team assignment yields 32% error in termination and promotion decisions, misclassifying employees purely through composition variance. Under realistic conditions reflecting differential managerial capability, error rates reach 53%, with false positives and false negatives each exceeding correct classifications. Cross-team calibration (often proposed as remedy) transforms evaluation into influence contests where persuasive managers secure promotions independent of merit. Multi-period dynamics produce adverse selection as employees observe random outcomes, driving risk-averse behavior and high-performer exit. The efficient solution (delegating judgment to managers with hierarchical accountability) cannot be formalized within the legal and coordination constraints that necessitated forced ranking. We conclude that this evaluation mechanism persists not through incentive alignment but through satisfying demands for demonstrable process despite producing outcomes indistinguishable from random allocation. This demonstrates how formalization intended to reduce agency costs structurally increases allocation error.