A Managerial Early Warning System

Abstract

The purpose of this research is to determine how managers could influence the results generated by a managerial early warning system, based on an artificial neural network. In order to achieve this goal, a multiple case-study strategy is employed which combines the qualitative with the quantitative perspective. The results prove that 78.10% of the variability of the managerial early warning system reliability can be explained by managers' influence and company's size; the first one is negatively correlated with system's reliability while the latest is positively correlated with system's reliability. These findings have both theoretical and practical implications. On the one hand, they extend the literature regarding managers' participation in the process of developing the future corporate strategy. On the other hand, they offer a better understanding on how managers may influence not only the identification of the weak signals but also the development of scenarios and forecasted business results.