Technology & Innovation

Making the Most of Machine Learning

April 18, 2018

North America

April 18, 2018

North America
Kevin Plumberg

Contributor

Kevin was a member of The Economist Intelligence Unit’s Thought Leadership team in North America and is based in San Francisco. From 2014-2017, he was based in The Economist’s Singapore office and led multi-year integrated content programmes such as Growth Crossings, a series about the new rules of global trade, and the Producers of Tomorrow, an initiative about the future of manufacturing. Prior to joining the EIU, he spent two years as Vice President, Institutional Marketing at BlackRock, the world’s largest asset management company. In that role, he produced and edited white papers, website articles and newsletters aimed at some of Asia’s biggest institutional investors. Kevin also spent 10 years as a journalist covering financial markets, economics and policy for Reuters in Singapore, Hong Kong and New York. As a correspondent and editor, he covered the global financial crisis from Wall Street and its aftermath in Asia, where he led market-moving coverage of the region’s economic policymakers.

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ML is not just a technology; it is core to the business strategies that have led to the surging value of organizations that incorporate it into their operating models—think Amazon, Uber, and Airbnb. Fast Learner organizations get that. 

Fewer Fast Learners than other organizations suffer from a lack of strategic clarity about ML. And fewer are plagued by organizational resistance to change. The reason may be that ML is viewed as more than a tactical tool for simply automating away costs and people. 

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