The Future Role of Business Intelligence Applications in Reducing Organizational Risks

Abstract

This article examines how experts evaluate the future role of business intelligence (BI) applications in reducing organizational risks. The article is grounded in organizational information-processing logic and in the decision-quality and data-quality literature. The proposed model assumes that predictive analytics capability, data quality and governance, real-time visualization capability, and analytical decision culture shape experts’ perceptions of future risk reduction. A quantitative cross-sectional design is specified, and the statistical section is demonstrated on an illustrative sample of 236 experts distributed across BI and analytics, risk management, internal audit and finance, digital transformation, and academia. Five-point Likert measures are used to operationalize the constructs. The illustrative findings show acceptable internal consistency for all scales (alpha = .798-.873), significant positive correlations among all main variables, and a statistically significant regression model explaining 45.1% of the variance in perceived future risk reduction, F(4, 231) = 47.45, p < .001. Data quality and governance (beta = .273) and analytical decision culture (beta = .272) emerge as the strongest predictors, followed by predictive analytics capability (beta = .203) and real-time visualization capability (beta = .127). Additional analyses show no statistically significant differences in perceived future risk reduction across experience groups or disciplinary groups, suggesting a broad expert consensus on the future value of BI for risk reduction. The article concludes that future BI value will depend less on technology acquisition alone and more on the integration of trustworthy data, evidence-based decision routines, and fast interpretive interfaces that convert data into preventive action.