Page 10 - HBR's 10 Must Reads 20180 - The Definitive Management Ideas of the Year from Harvard Business Review

EDITORS’ NOTE

Irrelevant factors, such as mood and the weather, can affect a per-
son’s decisions from one occasion to the next. This chance variabil-
ity of decisions is called noise. In “Noise: How to Overcome the High,
Hidden Cost of Inconsistent Decision Making,” Nobel laureate and
Princeton psychology professor Daniel Kahneman and data analy-
sis experts Andrew M. Rosenfield, Linnea Gandhi, and Tom Blaser
explain how organizations can perform a “noise audit” and use algo-
rithms and simple commonsense rules to guide employees toward
making more-consistent decisions.
Managers should all be relying more on data in their decision mak-
ing, but it arrives at such velocity, and in such volume, that many of
them don’t know quite what to do with it. A good first step is to cre-
ate a visualization or a chart. To do that well, however, you need to
understand the nature of your data and keep your purpose in mind,
according to Scott Berinato, an HBR senior editor and the author
of Good Charts: The HBR Guide to Making Smarter, More Persuasive
Data Visualizations. That strategic attitude will make your charts
and presentations much clearer and more effective. In “Visualiza-
tions That Really Work,” Berinato outlines categories of approach
and the tools and resources you’ll need for each.
Managers are pretty good at assessing whether a new technol-
ogy will overtake an existing one, but they haven’t quite figured out
how to know when that will happen. In “Right Tech, Wrong Time,”
professors Ron Adner and Rahul Kapoor say that not just your new
technology but also the ecosystem in which it will exist—the related
technologies, services, standards, and regulations—can influence
how quickly it’s adopted. They provide a framework to assess how
soon disruptive change is coming to your industry by analyzing the
dynamics of the context in which it will exist. If the new technology
doesn’t need a new ecosystem to support it—if it’s essentially plug-
and-play—adoption will be swift. But if complements are needed
(for example, electric cars require a network of charging stations),
the pace of substitution will slow until those challenges have been
resolved.
How to pay for health care is a problem the United States has
struggled with for a long time. Fee-for-service, the dominant model

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