Data Architecture, Machine Learning and Firm Productivity

50 Pages Posted: 6 Jul 2021 Last revised: 21 Jun 2022

See all articles by Ruiqing Cao

Ruiqing Cao

Harvard Business School

Marco Iansiti

Harvard University - Business School (HBS)

Date Written: June 14, 2022

Abstract

As enterprise IT systems increasingly incorporate data-driven technologies, it is crucial to understand complementary organizational practices that allow firms to unleash productivity benefits from adoption. This study uses survey and prediction methods to measure the data architecture of 225 large corporations and finds that data fabric capability complements enterprise ML software adoption. While corporations without a coherent data fabric suffer productivity losses from enterprise ML software investments, such investments lead to significant productivity gains among corporations with fully-developed data fabric capability. When data fabric capability is particularly low, enterprise ML software standardization significantly improves firm productivity.

Suggested Citation

Cao, Ruiqing and Iansiti, Marco, Data Architecture, Machine Learning and Firm Productivity (June 14, 2022). Harvard Business School Research Paper Series No. 21-122, Available at SSRN: https://ssrn.com/abstract=3874116 or http://dx.doi.org/10.2139/ssrn.3874116

Ruiqing Cao (Contact Author)

Harvard Business School ( email )

Cambridge, MA 02138
United States

Marco Iansiti

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

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