Using the Collective Wisdom of Frontline Employees in Strategic Issue Management

The field of strategic management has long alluded to the idea that lower-level employees immersed in the day-to-day business have experiential insights of potential strategic value. This line of thought has predominantly been supported by anecdotal evidence and explored in meticulous case studies to uncover the evolutionary traits of autonomous ventures. In a related vein, studies of ‘strategic issue management’ (SIM) tried to uncover organizational processes to identify emerging issues in volatile environments and devise proper strategic responses. These conceptual models were introduced in the very first volume of ‘Strategic Management Journal’, but little empirical research has since tried to develop the conception of SIM. An underlying research aim of this dissertation is to address and bridge these two literature streams, honing the idea of utilizing the collective wisdom possessed by frontline employees about ongoing changes in the internal and external environments as a unique information source to extend and advance SIM. In view of this, the dissertation tries to answer the following research question: “To what extent can frontline employees and customers predict firm performance – and how can it be utilized in SIM?” In order to answer this question, the dissertation was divided into three different papers, each with a distinct research focus. The first paper is a conceptual study that reviews and builds theory, by arguing that the collective wisdom of frontline employees and customers can be utilized to predict firm performance and identify emerging issues in SIM. The second paper is a qualitative study that looks into how intended and emergent strategy processes interact over time in a particularly hostile industry context. The third paper is a quantitative study that seeks to measure the predictive accuracy, or collective wisdom, of frontline employees and customers in predicting firm performance. The study includes more than 150,000 individual forecasts based on 13,531 survey responses which is subsequently compared to measures of actual firm performance.