Assessing the Strategic Value of Data-Driven Innovation in Competitive Advantage Creation

Abstract

This study investigates the strategic value of data-driven innovation in creating competitive advantage within contemporary organizational ecosystems. As businesses increasingly leverage data analytics, digital platforms, and advanced algorithms, data-driven innovation has emerged as a core capability for strategic differentiation. Despite its widespread adoption, there is limited empirical consensus on how data-driven innovation translates into measurable competitive advantage and what internal organizational factors moderate this relationship. This research addresses this gap by developing and validating a theoretical model linking data acquisition and analytics capabilities to innovation outcomes and, ultimately, to competitive advantage. Drawing on dynamic capabilities theory, the study hypothesizes that data acquisition capability, analytics capability, and data governance positively influence innovation performance and competitive advantage. Data were collected from 350 senior managers and data professionals across technology, finance, and manufacturing firms through a structured survey. Structural equation modeling using SmartPLS was employed to assess the relationships among constructs. The results indicate that data analytics capability significantly predicts innovation performance (β = .45, p < .001) and that both innovation performance and data governance significantly mediate the relationship between data acquisition capability and competitive advantage (β = .32, p < .01; β = .28, p < .05). Notably, data governance emerged as a stronger predictor of competitive advantage than raw data acquisition alone, suggesting that organizational processes and governance structures enable firms to extract strategic insight from data assets. Empirical findings underscore the role of internal alignment, technological infrastructure, and managerial commitment in realizing the strategic value of data-driven initiatives. This research enriches both academic and practitioner understanding by articulating a comprehensive framework that links data capabilities to sustainable competitive advantage. The findings offer actionable implications for managers seeking to allocate resources toward data-centric innovation and highlight areas for policy refinement and strategic investment. Key recommendations include strengthening cross-functional data governance, investing in analytics talent, and aligning data strategy with broader business objectives. This study contributes to the literature on strategic management, innovation studies, and information systems by clarifying the mechanisms through which data-driven innovation fosters competitive differentiation