Time Dependency, Data Flow, and Competitive Advantage

22 Pages Posted: 27 Apr 2021

See all articles by Ehsan Valavi

Ehsan Valavi

Harvard Business School

Joel Hestness

Cerebras Systems

Marco Iansiti

Harvard University - Business School (HBS)

Newsha Ardalani

Baidu - Baidu Research

Feng Zhu

Harvard University - Harvard Business School

Karim R. Lakhani

Harvard Business School - Technology and Operations Management Group; Harvard Institute for Quantitative Social Science; Harvard University - Berkman Klein Center for Internet & Society

Date Written: February 15, 2021

Abstract

Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government agencies and programs, and even industries) scales with the volume of available data. What is often less appreciated is that the data value in making useful organizational predictions will range widely and is prominently a function of data characteristics and underlying algorithms.

In this research, our goal is to study how the value of data changes over time and how this change varies across contexts and business areas (e.g. next word prediction in the context of history, sports, politics). We focus on data from Reddit.com and compare the value’s time-dependency across various Reddit topics (Subreddits). We make this comparison by measuring the rate at which user-generated text data loses its relevance to the algorithmic prediction of conversations. We show that different subreddits have different rates of relevance decline over time.

Relating the text topics to various business areas of interest, we argue that competing in a business area in which data value decays rapidly alters strategies to acquire competitive advantage. When data value decays rapidly, access to a continuous flow of data will be more valuable than access to a fixed stock of data. In this kind of setting, improving user engagement and increasing user-base help creating and maintaining a competitive advantage.

Keywords: Economics of AI; Value of data; Perishability; Time dependency; Flow of data; Competitive advantage; Data strategy

Suggested Citation

Valavi, Ehsan and Hestness, Joel and Iansiti, Marco and Ardalani, Newsha and Zhu, Feng and Lakhani, Karim R., Time Dependency, Data Flow, and Competitive Advantage (February 15, 2021). Available at SSRN: https://ssrn.com/abstract=3828623 or http://dx.doi.org/10.2139/ssrn.3828623

Ehsan Valavi (Contact Author)

Harvard Business School ( email )

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

Joel Hestness

Cerebras Systems ( email )

Marco Iansiti

Harvard University - Business School (HBS) ( email )

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

Newsha Ardalani

Baidu - Baidu Research ( email )

China

Feng Zhu

Harvard University - Harvard Business School ( email )

Soldiers Field Road
Morgan 431
Boston, MA 02163
United States

HOME PAGE: http://www.hbs.edu/faculty/Pages/profile.aspx?facId=14938

Karim R. Lakhani

Harvard Business School - Technology and Operations Management Group ( email )

Boston, MA 02163
United States
617-495-6741 (Phone)

Harvard Institute for Quantitative Social Science ( email )

1737 Cambridge St.
Cambridge, MA 02138
United States

Harvard University - Berkman Klein Center for Internet & Society ( email )

Harvard Law School
23 Everett, 2nd Floor
Cambridge, MA 02138
United States

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