Data-Driven Decision-Making: Showcasing the Best from our Management Science Archive

Abstract

Data-driven decision-making (DDDM) has emerged as a pivotal approach in contemporary management practices, facilitating informed and efficient decision-making processes across various domains. This scholarly compilation presents a comprehensive overview of the best practices and insights gleaned from our Management Science Archive regarding DDDM. Drawing upon a diverse array of case studies, empirical research, and theoretical frameworks, this anthology explores the multifaceted dimensions of leveraging data for decision-making purposes. From exploring predictive analytics to optimizing operational efficiencies, the articles showcased herein offer valuable perspectives on harnessing the power of data to drive organizational success. Furthermore, the compilation delves into the challenges and opportunities inherent in implementing DDDM strategies, highlighting the importance of data quality, interpretability, and ethical considerations.