Decision-making under uncertainty - The role of Descriptive, Predictive and Prescriptive Analytics - Stålhammar Holm,Olle; Segui,Felix; Weidler,Ingrid (2025)
This study examines how descriptive, predictive, and prescriptive analytics are applied in decision-making during stable operations and disruptive events, focusing on the Swedish food retail sector during the Covid-19 pandemic. Using a qualitative case study approach with semi-structured interviews and pattern-matching analysis, the research reveals key differences in analytics usage. During stable conditions, analytics tools provide reliable insights and forecasts, enabling efficient decision-making. However, during crises, their reliance on historical data and static models limits applicability, emphasizing the critical role of human expertise in recalibrating systems and interpreting incomplete data. The findings highlight the importance of balancing data-driven tools with human judgment to navigate disruptions effectively. This study contributes to understanding the interplay between analytics and human decision-making and offers practical recommendations for improving organizational resilience in volatile environments.
Keywords: Descriptive analytics; Predictive analytics; Prescriptive analytics; Decision-making; Disruptive events