Evaluating the Value of Predictive Insights Assessing the added value of predictive insights in the aerospace industry

Abstract

To manage uncertainty, business analytics and predictive models are widely used to support decision-making in industrial contexts. While existing research focuses on the development of predictive models and how such models are implemented in industrial contexts, this study aims to explore how the value of predictive insights can be evaluated and communicated within industrial organizations. The study adopts a qualitative research strategy, consisting of a literature review and an empirical case study at GKN Aerospace, based on semi-structured interviews and observations. The findings suggest that a standardized approach to quantify the value of predictive insights is not the most effective approach. Instead quantification must be done in a stakeholder-specific manner, since the value of predictive insights depends on how they are interpreted and acted upon by stakeholders. More specifically, the findings suggest that predictive insights are not valuable in isolation but through their impact on decisions and future outcomes. Additionally, the study concludes that quantification of predictive insights may be challenging in some instances where the value is not visible directly but instead emerges over time. Therefore, organizations may benefit from communicating the value of predictive insights retrospectively, to build acceptance and facilitate future initiatives in predictive analytic implementations.