A Strategic Framework for Leveraging Big Data in Decision-Making for Retail and Financial Sectors

Abstract

The exponential growth of digital data has created unprecedented opportunities for the retail and financial sectors to enhance decision-making processes. Big Data analytics enables organizations to derive actionable insights from vast and complex datasets, improving operational efficiency, customer experience, and competitive advantage. This paper proposes a strategic framework for leveraging Big Data in decision-making for retail and financial organizations, emphasizing data-driven strategies, technological infrastructure, and human capital development. The framework integrates predictive analytics, real-time decision support, and risk management tools to optimize business performance. The study explores sector-specific applications, including personalized marketing, fraud detection, credit risk assessment, and inventory optimization. Furthermore, challenges associated with data quality, privacy, and organizational readiness are addressed, with proposed mitigation strategies. Empirical and theoretical insights highlight the transformative potential of Big Data in enhancing operational and strategic decisions, driving innovation, and creating sustainable value. The proposed framework provides a roadmap for managers and policymakers to adopt a data-centric approach, ultimately fostering resilience and adaptability in rapidly evolving market environments.