The Role of Business Analytics and Strategic Positioning in Corporate Digital Transformation
Abstract
In the era of the digital economy, digital transformation is an inevitable choice for enterprises to enhance their competitiveness; however, vague strategic positioning often leads to poor transformation results. Data-driven decision-making based on business analytics can solve the empirical dilemma of strategy positioning. This study focuses on how business analytics can help strategic positioning amid corporate digital transformation while clarifying its core mechanism and corresponding practice models. This study suggests that business analytics plays a crucial role throughout the whole process of data-driven decision-making: in the initial stage, it lays a strategic foundation by digital maturity assessment along with internal and external analysis; In the middle stage, the strategic positioning will be transformed into a set of quantifiable indicator systems; In the later stage, data-driven method is used to ensure the synchronization between strategy and environment. Regarding practice models of different enterprises, large enterprises can cooperate through unified analysis platforms, while small and medium-sized enterprises (SMEs) rely on lightweight tools to build advantages. To cope with key challenges during transition, including ambiguous strategic goals and insufficient digital foundation, enterprises are advised to acquire systematic and self-generated digital capabilities, such as strengthened data governance, improved organizational digital literacy, and an integrated decision loop. This research promotes business analytics from a mere tool to a strategic decision enabler, providing enterprises with a feasible path to convert their strategic positioning from experience-driven to data-driven, which is of guiding significance for reducing risks and optimizing allocation.
Fields of Study & Subjects
Big Data and Business Intelligence
Digital Innovation in Industries
Information Technology Governance and Strategy
Publication details
- Journal / source
- Mathematical Modeling and Algorithm Application
- Volume
- 9
- Issue
- 1
- Pages
- 387–394
- Publication date
- 15 March 2026
- Language
- EN