The new wave of scientific and industrial revolutions has positioned data as a critical production factor that empowers corporate innovation quality. At present, systematic evidence remains limited regarding how firms achieve high innovation quality through alternative configurations of internal and external data factors, and whether heterogeneous configuration paths lead to differentiated outcomes. Drawing on the resource-based theory and the open innovation theory, this paper employs balanced panel data of Shanghai and Shenzhen A-share listed firms from 2017 to 2023 and adopts dynamic qualitative comparative analysis (QCA) to systematically analyze the configurational effects of internal data factors (data stock, data development capability, data-driven business applications, and data monetization) and external data factors (public data openness, data marketization, and data agglomeration) on innovation quality. Furthermore, it uses the PSM method to examine the heterogeneous effects of high innovation quality on resource allocation efficiency. The results reveal that firms can achieve high innovation quality through three paths: an “internal–external data resource synergy” path, an “internal data resource dominant” path, and an “internal data capability driven with external data resource compensation” path, exhibiting a clear characteristic of “different paths to the same destination”. Further analysis reveals that the impact of these paths on resource allocation efficiency vary significantly, characterized by “different paths to the same destination but with different effects”. Firms that form an internal value closed loop or acquire external data resources on demand can effectively reduce resource redundancy and allocation frictions, and thus significantly improve resource allocation efficiency after achieving high innovation quality. The study helps firms identify, select, and implement appropriate data factor configuration schemes to achieve high-quality innovation, thereby enhancing their resource allocation efficiency.