The Impact of Predictive Analytics on Business Decision Effectiveness: Evidence from Data-Driven Organizations

Shezan Ashilah Vandana (Faculty of Business, Department of Business Administration, Amman Arab University, Jordan)

Journal on Economics, Management and Business Technology
Vol. 4 No. 2 (2026): March: Economics, Management and Business Technology

The rapid growth of big data, artificial intelligence (AI), and digital transformation has accelerated the adoption of predictive analytics across organizations, enabling businesses to extract valuable insights from large volumes of structured and unstructured data. Organizations increasingly utilize predictive analytics to forecast future market trends, optimize operational processes, improve customer relationship management, and support evidence-based decision-making in highly competitive business environments. Consequently, understanding the influence of predictive analytics on business decision effectiveness has become increasingly important for enhancing organizational competitiveness and long-term performance. This study aims to analyze the impact of predictive analytics on the effectiveness of business decisions and examine how predictive capabilities improve managerial decision-making. A quantitative explanatory research design was employed using data collected through structured questionnaires administered to 250 business managers, executives, and data analysts from various industries. The collected data were analyzed using Structural Equation Modeling based on Partial Least Squares (SEM-PLS) to examine the relationships between predictive analytics and business decision effectiveness. The findings reveal that predictive analytics has a positive and statistically significant effect on business decision effectiveness. Specifically, higher predictive capability improves decision quality, decision speed, decision accuracy, resource optimization, and organizational performance while reducing uncertainty and operational risks. The study concludes that predictive analytics represents a strategic organizational capability that enables more accurate, timely, and data-driven decision-making. Strengthening data quality, analytical capabilities, technological infrastructure, and the integration of predictive insights into business processes can significantly improve organizational competitiveness and support sustainable business performance in an increasingly data-driven economy.