Abstract:

At the intersection of information systems and strategic management, implementing closed-loop intelligent decision-making in complex organizations remains a pivotal theoretical and practical challenge. Addressing the “growth dilemma”—wherein software enterprises suffer from weak economies of scale due to labor-intensive customization—this study draws on the dual perspectives of software economics and knowledge governance to analyze Palantir, a pioneer in decision intelligence. Specifically, it systematically deconstructs the co-evolutionary mechanism between Palantir’s “Ontology”-driven technical architecture and its “Forward Deployed Engineer” (FDE) organizational model. The findings indicate that Palantir transforms bespoke, high-cost services into durable, modularized R&D assets through “on-site service assetization and productization,” thereby overcoming the diminishing returns inherent in traditional IT services. However, the scalable generalization of this model hinges on stringent boundary conditions: a concentrated tier-one client base (“super-anchor” accounts), a steady pipeline of interdisciplinary talent, deep organizational embeddedness enabled by administrative leverage, and sovereign-level trust mechanisms. Finally, grounded in the empirical context of digital transformation across China’s industrial and public sectors—and addressing core bottlenecks such as data quality heterogeneity, multi-level governance friction, and the structural undervaluation of software assets—this paper outlines localized evolutionary pathways and strategic recommendations for constructing indigenous intelligent decision-making systems.

Key words: Palantir, digitalization, data intelligence, technology and business paradigm