Summary of Competing on the Rate of Learning

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Data – vast new volumes of it – and algorithms that analyze and act on that data are thrusting business learning into new territory. Speed becomes crucial and old decision-making approaches simply move too slowly. Organizations must become self-tuning and able to learn, and they must respond automatically. In this article, Boston Consulting Group’s strategy expert Martin Reeves and economist Kevin Whitaker draw clear conclusions from current developments in data gathering and analysis, artificial intelligence, and machine-human integration.

About the Authors

Strategy expert Martin Reeves is senior partner and managing director of the Boston Consulting Group Henderson Institute. Kevin Whitaker is an economist at BCG’s Center for Macroeconomics in New York.



The availability of vast new volumes of data in combination with algorithms for extracting insights is catapulting learning into new territories. Historically, companies first engaged in continual improvement to existing processes. First-generation learning pursued approaches like kaizen and Six Sigma, which aimed at constant reductions in marginal costs through organizational learning. Second-generation learning emerged when enterprises sought to apply the learning from previous products to new ones.

Third-generation learning’s focus is on generating and processing data...

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