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All Journal International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS)
Gugun Sodik
Universitas Adhirajasa Reswara Sanjaya
Economics, Econometrics & Finance

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DATA-DRIVEN LEADERSHIP: A CONCEPTUAL REVIEW OF EVIDENCE-BASED MANAGEMENT AND DIGITAL TRANSFORMATION Gugun Sodik
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 5 No. 6 (2025): December
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21784834

Abstract

Data-driven leadership has become a strategic requirement as organizations face increasing data volume, technological disruption, and pressure for transparent decision-making. This article aims to synthesize the conceptual foundations, core pillars, implementation strategies, practical applications, and principal challenges of data-driven leadership. A narrative conceptual review was conducted using foundational works on evidence-based management, digital leadership, data literacy, analytics, and technology-enabled organizational transformation. The analysis integrates three complementary perspectives: Evidence-Based Management, the Digital Leadership Framework, and Data-Driven Decision-Making. The synthesis identifies five essential pillars: accurate data collection, data analysis and visualization, evidence-based decisions, cross-functional collaboration, and data ethics and security. Effective implementation follows a continuous pathway comprising data culture development, investment in analytical technology, data literacy training, security governance, and monitoring and evaluation. Illustrative cases involving Google, Amazon, Gojek, and Telkom Indonesia demonstrate how leaders can convert data into improvements in workforce management, supply chains, platform operations, and service personalization. The article concludes that data-driven leadership does not replace managerial judgment; it strengthens judgment through valid evidence, technological capability, ethical governance, and organizational learning.
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