The Role of Noise in a Mutual Selection and Learning Model

Abstract

In the organizational learning and search literature, conventional wisdom holds that a moderate degree of noise helps organizations improve their performance by introducing more variation. We note, however, that portrayals of most organizational structures in this line of inquiry are overly simplified. We contribute to this literature by suggesting that the beneficial role of moderate noise is dependent on its relational presence in a mutual selection and learning system. By extending March’s (1991) mutual learning model, we examine the role of noise in an organization as an adaptive system where both the organizational code and individuals can select and learn from others. We demonstrate that, while a small amount of noise on the learning stage is beneficial, noise on the selection stage monotonically decreases performance. Our results indicate a need for re-examination of the role of noise in various organizational settings and structures.