Data Analytics, Innovation, and Firm Productivity

TLDR

The study investigates how data analytics capabilities relate to firm innovation using detailed firm-level data. Innovation was measured via a survey of 331 firms on process improvement and new technology development, supplemented by patent data for over 2,000 publicly traded firms. Data analytics are most beneficial for firms focused on process improvement and diverse recombination of existing technologies, while offering limited advantage for developing entirely new technologies or small-knowledge combinations. The paper was accepted by Chris Forman, Information Systems.

Abstract

We examine the relationship between data analytics capabilities and innovation using detailed firm-level data. To measure innovation, we first utilize a survey to capture two types of firm practices, process improvement and new technology development for 331 firms. We then use patent data to further analyze new technology development for a broader sample of more than 2,000 publicly traded firms. We find that data analytics capabilities are more likely to be present and are more valuable in firms that are oriented around process improvement and that create new technologies by combining a diverse set of existing technologies than they are in firms that are focused on generating entirely new technologies. These results are consistent with the theory that data analytics are complementary to certain types of innovation because they enable firms to expand the search space of existing knowledge to combine into new technologies, as well as the theoretical arguments that data analytics support incremental process improvements. Data analytics appears less effective for developing entirely new technologies or creating combinations involving a few areas of knowledge, innovative approaches where there is either limited data or limited value in integrating diverse knowledge. Overall, our results suggest that firms that have historically focused on specific types of innovation—process innovation and innovation by diverse recombination—may receive the most benefits from using data analytics. This paper was accepted by Chris Forman, information systems.