Data Analytics Supports Decentralized Innovation

TLDR

Data‑analytics technology can accelerate innovation by enabling knowledge reuse, but its benefits depend on complementary human capital and organizational capabilities, explaining a contemporary analytics‑innovation paradox. The study investigates whether analytics is more valuable in firms with decentralized versus centralized innovation groups. The authors analyze firm‑analytics capability using employee‑level data matched to intrafirm inventor network metrics that reveal centralized or decentralized innovation structures. Decentralized firms demand more analytics skills and gain greater productivity benefits, with analytics enabling new combinations and reuse of technologies mainly through non‑inventor employees, showing that analytics benefits depend on organizational structure. This paper was accepted by Anandhi Bharadwaj, information systems.

Abstract

Data-analytics technology can accelerate the innovation process by enabling existing knowledge to be identified, accessed, combined, and deployed to address new problem domains. However, like prior advances in information technology, the ability of firms to exploit these opportunities depends on a variety of complementary human capital and organizational capabilities. We focus on whether analytics is more valuable in firms where innovation within a firm has decentralized groups of inventors or centralized ones. Our analysis draws on prior work measuring firm-analytics capability using detailed employee-level data and matches these data to metrics on intrafirm inventor networks that reveal whether a firm’s innovation structure is centralized or decentralized. In a panel of 1,864 publicly traded firms from the years 1988–2013, we find that firms with a decentralized innovation structure have a greater demand for analytics skills and receive greater productivity benefits from their analytics capabilities, consistent with a complementarity between analytics and decentralized innovation. We also find that analytics helps decentralized structures to create new combinations and reuse of existing technologies, consistent with the ability of analytics to link knowledge across diverse domains and to integrate external knowledge into the firm. Furthermore, the effect primarily comes from the analytics capabilities of the noninventor employees as opposed to inventors themselves. These results show that the benefit of analytics on innovation depends on existing organizational structures. Similar to the IT–productivity paradox, these results can help explain a contemporary analytics–innovation paradox—the apparent slowdown in innovation despite the recent increase in analytics investments. This paper was accepted by Anandhi Bharadwaj, information systems.