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 key driver of value creation from innovation in computing. We argue that a crucial 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 prevalence of third-party maintenance as a proxy for legacy servers before 2016 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 servers reduce data architecture coherence particularly at corporations with complex software systems, consistent with the hypothesis that costs of digital transformation are greater when workers need to develop more complicated co-invention processes to interact with technical systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
