Integrating Scientific Data Analytics into Digital Business Strategy - Kursih Sulastriningsih; Imella Annisah; Lista Meria; Alexander Chou Kiboy (Pandawan Sejahtera Indonesia, 2026)
Amid the increasing complexity of the contemporary digital economy, organizations face growing challenges in transforming large volumes of data into actionable strategic insights. While data analytics has become an essential component of digital business operations, the integration of scientific analytical principles into strategic decision-making remains insufficiently explored. This study aims to develop a conceptual framework for integrating Scientific Data Analytics (SDA) into digital business strategy by synthesizing insights from strategic management and data analytics literature. Using a qualitative approach based on literature review and thematic content analysis, this study examines how analytical methods such as causal inference, predictive analytics, and evidence-based management can support strategic planning and organizational decision-making. The analysis identifies several key themes, including organizational alignment, analytical capability development, data governance, and the role of evidence-based decision-making in enhancing strategic adaptability. The study further highlights potential challenges related to organizational resistance, data quality, and algorithmic bias that may affect analytics adoption. Theoretically, this research contributes by proposing an integrated conceptual framework that connects data analytics capabilities with strategic management processes. Practically, the study offers conceptual guidance for managers and decision-makers seeking to strengthen data-informed strategic planning in digital business environments. The findings provide a foundation for future empirical research examining the relationship between scientific analytics integration and organizational performance.