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

TL;DR
Forced ranking systems in organizations, intended to differentiate performance, often produce random and systematically biased outcomes, leading to misclassification, adverse effects on employee behavior, and failing to effectively resolve principal-agent problems.
Contribution
This paper demonstrates through simulation that forced ranking systems cause significant classification errors and adverse organizational dynamics, challenging their effectiveness and underlying assumptions.
Findings
32% error rate in random team assignments
Error rates increase to 53% with managerial differences
Evaluation outcomes are indistinguishable from random allocation
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…
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Taxonomy
TopicsExperimental Behavioral Economics Studies · Sports Analytics and Performance · Game Theory and Voting Systems
