author(s)
Simon Suwanzy Dzreke and Semefa Elikplim Dzreke

abstract
In an era of hypercompetition and seismic digital upheaval, enterprises must negotiate a volatile landscape in which traditional profit models crumble and data-driven strategic pivots become existential requirements. This meta-analysis addresses a fundamental gap in strategic management: the elusive relationship between the sophistication of competitive intelligence approaches and real, long-term profitability. This study, which synthesizes empirical evidence from over 120 high-quality papers published between 2020 and 2025, uses systematic review and robust meta-regression approaches to estimate the financial impact of evolving analytical practices. The findings provide a compelling narrative: firms that use AI-driven competitive intelligence which includes predictive analytics, real-time behavioral signal processing, and ecosystem-level sensing consistently achieve 12% to 18% higher returns on investment (ROI), transforming data into a powerful source of compounding advantage. However, the research reveals an important and costly limitation. When sophisticated analytical capabilities are misaligned with an organization's dynamic capabilities the ability to rapidly sense, seize, and reconfigure resources potential profitability gains are reduced by up to 40%, demonstrating the dangers of analytical sophistication without organizational agility. Consider the dramatic contrast: algorithmic pricing engines that dynamically respond to rival moves result in instant margin increases, whereas isolated market reports gathering dust provide no benefit. This study goes beyond mere correlation, presenting an applicable Dynamic Positioning Framework. This framework lays out a plan for seamlessly combining real-time competitive intelligence with strategy execution, allowing leaders to close the foresight-execution gap. It reveals that sustained profitability in digital marketplaces necessitates not only analytical strength, but also careful orchestration within a responsive, learning-oriented strategy architecture.