Reframing Business Strategy through Data: A Review of Data-Driven Strategic Thinking
Boxiong Li
Journal of Sustainability, Policy, and Practice, 2026, vol. 2, issue 1, 230-244
Abstract:
This review paper explores the evolving landscape of business strategy through the lens of data-driven strategic thinking. It examines how organizations are increasingly leveraging data analytics, machine learning, and other data-centric approaches to inform strategic decisions, gain competitive advantages, and adapt to dynamic market conditions. The paper provides a historical overview of the shift from traditional intuition-based strategy to data-informed strategy, highlighting key milestones and influential frameworks. It then delves into two core themes: (1) the application of data analytics for strategic insights, including market segmentation, customer behavior analysis, and competitive intelligence; and (2) the use of data-driven experimentation and learning to refine strategic choices and foster organizational agility. A comparative analysis of different data-driven strategy frameworks is presented, along with a discussion of the challenges associated with implementing and sustaining a data-driven strategic approach. Finally, the paper explores future perspectives, including the potential of artificial intelligence, blockchain, and other emerging technologies to further transform business strategy. The review synthesizes a wide range of academic literature and industry best practices, offering valuable insights for researchers and practitioners seeking to understand and implement data-driven strategic thinking.
Keywords: Data-driven strategy; Strategic thinking; Business analytics; Competitive advantage; Machine learning; Data science; Organizational Agility (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:dba:jsppaa:v:2:y:2026:i:1:p:230-244
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