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  • 2022
  • Working Paper
  • HBS Working Paper Series

Data Architecture, Machine Learning and Firm Productivity

By: Sam (Ruiqing) Cao and Marco Iansiti
  • Format:Print
  • | Language:English
  • | Pages:51
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Abstract

As enterprise IT systems increasingly incorporate machine learning technology, it is crucial to understand complementary organizational practices that allow firms to unleash productivity benefits from adoption. This study examines the relationship between machine learning adoption and data architecture capabilities using detailed corporation-level data. We utilize a survey to measure two clusters of data architecture practices--data fabric and ML infrastructure, for 82 large corporations. We use data on legacy systems and software varieties to produce out-of-sample predictions of data architecture capabilities for an additional 143 large corporations on the Fortune 500 list. We find that corporations with higher data fabric capability adopt machine learning more intensively. A one-standard-deviation increase in machine learning adoption is associated with a 1.5% increase in productivity among corporations with above-median data fabric capability. However, machine learning adoption can negatively affect firm productivity without a sufficiently developed data fabric. These results suggest that data fabric capability is complementary to machine learning adoption. Data fabric facilitates more coordinated and less fragmented adoption of ML software products across the organization because it allows organizations to integrate large data streams across diverse sources and locations.

Keywords

Organizations; Information Technology; Performance Productivity; Growth and Development; Transformation

Citation

Cao, Sam (Ruiqing), and Marco Iansiti. "Data Architecture, Machine Learning and Firm Productivity." Harvard Business School Working Paper, No. 21-122, May 2021. (Revised May 2022.)
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About The Author

Marco Iansiti

Technology and Operations Management
→More Publications

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More from the Authors
  • Network Interconnectivity and Entry into Platform Markets By: Feng Zhu, Xinxin Li, Ehsan Valavi and Marco Iansiti
  • Orchadio’s First Two Split Experiments By: Iavor I. Bojinov, Marco Iansiti and David Lane
  • Moderna (A) By: Marco Iansiti, Karim R. Lakhani, Kerry Herman and Amy Klopfenstein
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