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Firms have invested heavily in digital transformation through cloud infrastructure, process digitisation, data platforms, automation, and digitally enabled customer interfaces. Yet many organisations discover that becoming more digital does not automatically produce durable competitive advantage, stronger margins, or defensible market positions. The central problem is that digital transformation is often treated as a strategic endpoint rather than as a foundation for deeper business model change. Firms may modernise systems, accelerate operations, and improve data visibility while leaving their revenue logic, value proposition, customer relationship, and ecosystem role largely unchanged. This perspective argues that digital transformation becomes strategically meaningful only when it triggers business model reinvention. The article focuses on three critical dimensions of post-transformation business models: revenue logic, customer data as a strategic resource, and ecosystem positioning. The article develops an evidence-based perspective using peer-reviewed research on business model innovation, digital transformation, platform strategy, data-driven innovation, and ecosystem competition. It does not present new empirical data; instead, it offers a critical synthesis and strategic argument for managers and scholars. The perspective concludes that the central managerial challenge is no longer simply how to become digital, but how to reinvent the business after digital foundations are in place. Firms that fail to make this transition risk becoming digitally efficient but strategically stagnant.

Firms now collect vast quantities of customer, operational, and transactional data through digital platforms, enterprise systems, service encounters, logistics infrastructures, and payment architectures. Yet much of this data is used only for its immediate operational purpose and then stored, fragmented, or ignored. This creates a strategic paradox: data abundance does not automatically produce value abundance. Existing theories of digital business value have largely emphasised data collection, analytics capability, governance, and decision support. These perspectives explain how firms analyse data for predefined purposes, but they do not fully explain how firms systematically repurpose existing data assets for new uses. This leaves an important gap in understanding how data becomes renewable rather than merely accumulated. This article conceptualises enterprise data reuse as a distinct digital business capability. It defines data reuse as the organisational capacity to identify data already collected, prepare it for a new context, recombine it with other data assets, and apply it to new business problems, products, services, or strategic insights. The article develops a theory of how customer, operational, and transactional data can be repurposed to support value renewal. The article contributes by positioning data reuse as a higher-order capability rather than a secondary analytics activity. It argues that firms able to renew the value of existing data can generate new revenue opportunities, reduce the marginal cost of innovation, and strengthen strategic adaptability. Enterprise data reuse therefore transforms data from a one-time input into a renewable strategic asset.