Predictive Analytics Adoption in Public Policy Decision-Making

doi:N/A

eISSN: 2202-4859 / ISSN: None

Revenue Law Journal

2026, Volume 32, ISSUE 1 : 1-5

Research Article

Predictive Analytics Adoption in Public Policy Decision-Making

Arvind Kumar

Laura Fernandez

Michael R. Hughes

Dept. of Public Policy & Governance, National Institute of Policy Science, New Delhi, India

Faculty of Data Sciences, University of Barcelona, Spain

School of Information Systems, Arizona State University, USA

Abstract

Predictive analytics is increasingly transforming the landscape of public policy by enabling governments to anticipate challenges, optimize resource allocation, and design data-driven interventions. Despite its benefits, adoption remains uneven across developing and developed nations. This paper examines the drivers, barriers, and frameworks for integrating predictive analytics into public policy decision-making. Using an interdisciplinary approach, the study synthesizes concepts from data science, governance theory, and behavioral public administration. The article also proposes a conceptual model for successful adoption and discusses ethical considerations such as transparency, accountability, and algorithmic fairness.

Keywords

Transparency

Conceptual

Synthesizes

Adoption

Examines

License

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