The Peter Principle Revisited: A Computational Study

TL;DR

This study uses agent-based simulations to analyze the Peter Principle, demonstrating its inevitability under certain organizational conditions and showing that random promotion strategies can mitigate efficiency loss.

Contribution

It provides a computational validation of the Peter Principle and explores promotion strategies to counteract its negative effects on organizational efficiency.

Findings

The Peter Principle is unavoidable under specific promotion mechanisms.

Random promotion strategies can improve overall organizational efficiency.

Promoting randomly among the best and worst members reduces efficiency loss.

Abstract

In the late sixties the Canadian psychologist Laurence J. Peter advanced an apparently paradoxical principle, named since then after him, which can be summarized as follows: {\it 'Every new member in a hierarchical organization climbs the hierarchy until he/she reaches his/her level of maximum incompetence'}. Despite its apparent unreasonableness, such a principle would realistically act in any organization where the mechanism of promotion rewards the best members and where the mechanism at their new level in the hierarchical structure does not depend on the competence they had at the previous level, usually because the tasks of the levels are very different to each other. Here we show, by means of agent based simulations, that if the latter two features actually hold in a given model of an organization with a hierarchical structure, then not only is the Peter principle unavoidable, but also it yields in turn a significant reduction of the global efficiency of the organization. Within a game theory-like approach, we explore different promotion strategies and we find, counterintuitively, that in order to avoid such an effect the best ways for improving the efficiency of a given organization are either to promote each time an agent at random or to promote randomly the best and the worst members in terms of competence.