The Role of Feedforward-Enabled Predictive Analytics in Changing Mental Models

Abstract

One of the key determinants of an organization’s success is its ability to adapt to marketplace change. Given this reality, how do organizations survive or even thrive in today’s dynamic markets? The answer to this question is highly related to the adaptability of one of the organization’s key resource: its employees. Indeed, the central component of an organization’s success will depend on its ability to drive changes in the mental models of individual employees. Moreover, a critical facilitator of that will be the development of decision support tools that support change of those mental models. In response to this need there has been a tremendous growth in business analytic decision support tools, estimated to reach almost $200 billion in sales by 2019. The premise of this research is that these decision support tools are ill-suited to support true mental model change because they have focused on a feedback-enabled view and generally lack a predictive (feedforward-enabled) view of the likely outcomes of the decision. The purpose of this research is to study how changes in mental models can be facilitated through this feedforward mechanisms within the DSS tool. This research used a mixed method approach, leveraging the strengths of quantitative and qualitative research methodologies, to study this research question. The research showed that the feedforward-enabled DSS tool did create more mental model change and alignment (versus an ideal solution) compared to the control. The feedforward enabled tool also produced better alignment than the feedback-enabled decision support tool. In fact, the feedback-enabled decision support was shown to result in a poorer alignment with the ideal solution. This paper concludes by suggesting five areas for future research.