BIG DATA FOR PRODUCTIVITY: A POLICY-TO-PRACTICE FRAMEWORK FOR FIRMS

Abstract

Technology generates optimal outcomes when employed wisely and comprehensively.   Big data as a technology tool converts raw, unstructured information into a strategic asset that can generate competitive advantage and measurable value for the organization. By addressing varied information and implementing advanced analytics, organizations can improve predictive models for consumer behavior and progress in medical, educational, commercial, scientific, and many other social sectors. Nonetheless, these benefits are unevenly distributed: productivity improvements are focused in technologically advanced nations, while many developing countries receive only a fraction of the potential.   This paper asserts that realizing the potential of big data requires interdisciplinary expertise—merging domain knowledge with statistics, computing, and data governance—alongside careful attention to confounders and outliers, rather than depending solely on single-domain intuition.   We propose a conceptual framework for converting data assets into sustainable advantages, founded on three pillars: (1) interoperable infrastructure and standards to enable dataset integration; (2) human capital and literacy for the design, validation, and implementation of models; and (3) governance frameworks that ensure quality, privacy, equity, and responsible use.   The document highlights essential research goals, including methods for secure data integration, metrics for productivity spillovers, and policy interventions that promote adoption in resource-constrained settings.   These components illustrate how businesses and nations can transform data capabilities into substantial economic growth.