The Peter Principle Revisited: An Agent-Based Model of Promotions, Efficiency, and Mitigation Policies

TL;DR

This paper uses an agent-based model to analyze the Peter Principle, revealing how different promotion policies impact organizational efficiency and proposing mitigation strategies like training and demotion.

Contribution

It introduces a large-scale ABM to study the Peter Principle and evaluates promotion and mitigation policies in hierarchical organizations.

Findings

Merit promotion amplifies the Peter effect when role requirements change greatly.

Seniority and random promotions show weaker Peter effects.

Training and demotion strategies effectively mitigate efficiency loss.

Abstract

The Peter Principle posits that organizations promoting their best performers risk elevating employees to roles where their competence no longer translates, thereby degrading overall efficiency. We investigate when this dynamic emerges and how to mitigate it using a large-scale agent-based model (ABM) of a five-level hierarchy. Results show the Peter Principle is most pronounced under merit promotion when role requirements change substantially between levels; seniority and random exhibit the weakest Peter effects. Both interventions mitigate performance declines, with merit-with-training particularly effective when skill transfer is limited, and selective demotion restoring agents whose 'true' peak performance is at lower levels.