Harvard Business School

Working Paper: The Value of Data and Its Impact on Competition

By Marco Iansiti, Professor of Business Administration at Harvard Business School
July 10, 2021   /   1 Minute Read
The Value of Data by Marco Iansiti

Originally published in July 2021 as part of Harvard Business School’s Working Paper Series. Below is the abstract of the paper:

Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of “data network effects”, where more data leads to product improvements, which in turn leads to additional users and more data. In particular, this has raised concerns around incumbent data advantage creating an insurmountable barrier to entry and leading to winner-take-all outcomes in online platforms.

However, this perspective generally does not reflect the value of data in practical settings. More recent work across economics, management science, and engineering shows that there are a variety of factors that impact the value of data and that implications for competition are much more complex and subtle. The framework in this paper presents four key factors – data quality, scale and scope of data, and data uniqueness – that can influence the value that firms can derive from data.

Applying the framework to Netflix, Waymo, and the online advertising industry provides compelling evidence that incumbent data advantage, while generating value for innovation and for the consumer experience, does not necessarily lock out competitors and is not determinative of success. These examples illustrate that data can often serve as a catalyst for innovation that benefits both consumers and the broader ecosystem. The extent to which data accumulation can provide actual incremental value, and whether this is a cause for concern in enabling healthy competition, requires a case-by-case evaluation using the framework, as these factors depend significantly on the domain and context.

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