Data Analytics Skills, Innovation and Firm Productivity

Management Science Forthcoming

48 Pages Posted: 8 Mar 2016 Last revised: 19 Feb 2020

See all articles by Lynn Wu

Lynn Wu

University of Pennsylvania - The Wharton School

Lorin M. Hitt

University of Pennsylvania - Operations & Information Management Department

Bowen Lou

University of Connecticut - Operations & Information Management Department

Date Written: October 28, 2018

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 appear 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 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.

Keywords: data analytics, novel innovation, recombination, productivity, big data, AI, automation, economics of IS

Suggested Citation

Wu, Lynn and Hitt, Lorin M. and Lou, Bowen, Data Analytics Skills, Innovation and Firm Productivity (October 28, 2018). Management Science Forthcoming, Available at SSRN: https://ssrn.com/abstract=2744789 or http://dx.doi.org/10.2139/ssrn.2744789

Lynn Wu (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3733 Spruce Street
Philadelphia, PA 19104-6374
United States

Lorin M. Hitt

University of Pennsylvania - Operations & Information Management Department ( email )

571 Jon M. Huntsman Hall
Philadelphia, PA 19104
United States
215-898-7730 (Phone)
215-898-3664 (Fax)

Bowen Lou

University of Connecticut - Operations & Information Management Department ( email )

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