Decision Intelligence vs. Predictive Analytics for Industry 4.0: Architectures, Methods, and Operational Implications

Abstract

Industry 4.0 environments increasingly rely on data driven systems to guide operational, tactical, and strategic actions. Predictive analytics has traditionally served as the backbone of such systems by forecasting outcomes from historical data. However, the growing complexity of cyber physical systems, autonomous production lines, and human machine collaboration has exposed limitations in purely predictive approaches. Decision Intelligence has emerged as a broader paradigm that integrates predictive models with decision logic, contextual reasoning, and human aligned governance. This article presents a comparative analysis of Decision Intelligence and Predictive Analytics within Industry 4.0 settings. It examines their conceptual foundations, architectural patterns, methodological differences, and measurable impacts on industrial performance. Through synthesized evaluation metrics, architectural models, and simulated results, the study highlights how Decision Intelligence enables more adaptive, explainable, and value aware industrial decision making.