Growth, Transformation and Digital Capital: The Importance of Technological and Organizational Architecture

Abstract

The benefits to data analytics and machine learning have been distributed unevenly across firms around the world. Research on IT productivity points to intangible capital as a crucial driver of value creation from innovation in computing. We argue that an important component of intangible capital is organization-wide technological architecture, which is idiosyncratic and difficult to measure. We use a novel survey instrument to quantify large corporations’ data architecture capabilities by their closeness to “best practices” of frontier digital companies. Using the pre-2016 server third-party maintenance as a proxy for legacy systems and an instrument for data architecture coherence, we find that improving data architecture coherence leads to more intensive machine learning capabilities and substantially higher productivity growth in the subsequent three-year period. Legacy server technology reduces ML-driven capabilities and productivity growth particularly at corporations where software systems are more complex, suggesting that data architecture coherence complements software system complexity by lowering the costs and frictions to technical user co-invention.