Predictive Analytics – Examining the Effects on Decision Making in Organizations

Predictive analytics is a type of business analytics which enables predictions to be made, about occurrence of particular events in the future, based on data of the past. The predictive analytics is widely incorporated among the most successful organizations where it supports their decision-making process. The aim of our study is to examine the effects on decision making in organizations caused by predictive analytics. We perform a qualitative study to investigate the effects by using Simon’s model to break down the decision-making process and analyse how the predictive analytics affects each stage. Additionally we test the propositions from Huber’s theory of the effects of advanced information technology on organizational design, intelligence and decision making, in the context of predictive analytics as an advanced information technology. Our contribution to IS knowledge is derived from our findings which show that the predictive analytics offers strong support in the intelligence and design phase of the decision-making process, while having no effect on the choice phase. Furthermore, through the prism of Huber’s theory, we find that the predictive analytics generates effects on the organizational intelligence and decision making, while also having effects at subunit level, organizational level and the organizational memory