Data Analytics Strategies for Improving Organizational Performance

David Brougham

Data Analytics Strategies for Improving Organizational Performance

Author(s)	David Brougham
Country	New Zealand
Abstract	The increasing availability of digital information has transformed the way organizations evaluate operations, understand markets, allocate resources, and formulate strategic decisions. Organizations now generate large quantities of data through enterprise applications, customer interactions, financial transactions, supply chains, social platforms, sensors, and digital services. However, the availability of data alone does not guarantee organizational improvement. Data must be systematically collected, processed, analyzed, interpreted, and translated into actionable knowledge. This study examines data analytics strategies for improving organizational performance and proposes a conceptual framework that connects data acquisition, data preparation, descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, performance measurement, and strategic decision-making. A conceptual and descriptive research design is adopted through the synthesis of secondary scholarly literature concerning data analytics, business intelligence, organizational performance, predictive analytics, data-driven decision-making, and information systems. The analysis demonstrates that effective data analytics strategies can improve operational efficiency, decision quality, customer understanding, resource allocation, risk management, innovation, and strategic responsiveness. The study further emphasizes that analytical effectiveness depends on data quality, technological infrastructure, employee capabilities, leadership support, analytical culture, governance, and the alignment of analytics with organizational objectives. The proposed framework highlights the importance of integrating analytical capabilities across operational and strategic levels rather than treating data analytics as an isolated technological function. The study concludes that organizations can achieve stronger and more sustainable performance when data analytics is embedded within decision-making processes and supported by appropriate governance, skills, technology, and organizational commitment.
Keywords	Data Analytics, Organizational Performance, Business Intelligence, Predictive Analytics, Data-Driven Decision-Making, Organizational Efficiency, Strategic Analytics, Performance Management, Data Science.
Field	Engineering
Published In	Volume 1, Issue 6, November-December 2019
Published On	2019-12-31

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Data Analytics Strategies for Improving Organizational Performance

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