Big Data Analytics as a Strategic Decision Support for Policy Direction Determination and Business Projection in Organizations
Keywords:
decision making, big data analytics, policy making, business forecasting, organizational performanceAbstract
This study examines the application of big data analytics in strategic decision making for policy formulation and business forecasting within organizations. A qualitative literature review approach is employed to synthesize theoretical frameworks and empirical findings from various disciplinary perspectives. The analysis reveals that successful implementation of big data analytics requires balanced development of infrastructure, human resource capabilities, and managerial support. Strategic decisions supported by big data exhibit higher objectivity, accuracy, and responsiveness to environmental changes. Business forecasting derived from appropriate analytical methods provides a solid foundation for resource allocation and future planning. Leadership commitment, data governance, and the ability to bridge technical and managerial gaps emerge as critical success factors. Risks associated with data dependency, bias, security, and misinterpretation must be proactively managed through clear policies and continuous evaluation. The resulting conceptual model offers guidance for organizations to integrate big data analytics into their strategic decision making cycles sustainably. This study contributes to the theoretical understanding of how analytical capabilities translate into strategic outcomes. Practical implications include recommendations for readiness assessment, capability development, and performance measurement. Organizations are encouraged to adopt a phased approach prioritizing areas with the greatest strategic impact. Future research should empirically test the proposed model across various sectors and organizational contexts.
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