HBR’s 10 Must Reads 2018: The Definitive Management Ideas of the Year from Harvard Business Review
Various contributors and HBR Editors
Harvard Business Review Press (October 2017)

Another annual harvest of timeless and timely business wisdom

This is the latest in a series of the “HBR 10 Must Read” anthologies that are published annually in autumn. Each consists of ten articles plus a “bonus” article, all previously published in Harvard Business Review. The contents are selected by HBR editors. In the Note that introduces the 2018 edition, they say this: “Every year, as we build each issue of Harvard Business Review, we examine the most important challenges facing business leaders today…The standout articles of the year collected here, for example, explain emerging phenomena like blockchain, dataviz literacy, and algorithms in practical terms. They also offer new perspectives on long-term issues such as boosting employee engagement, increasing diversity, and fixing the U.S. health care system. We showcase these and other critical themes highlighted by our authors from the past year [or so] of Harvard Business Review in this volume.”

For each of my reviews, I first decide which approach to the material would be most informative to those who read the given review. In this instance, I have selected the “Farmer’s Market Strategy.” Rather than slices of fresh fruit, I offer a selection of brief excerpts (i.e. samples) that are representative of the quality of the material in this volume.

In “Customer Loyalty Is Overrated,” A.G. Lafley and Roger L. Martin observe: “If customers are slaves of habit, it’s hard to argue that they are ‘loyal’ customers in the sense that they consciously attach themselves to a brand on the assumption that it meets rational or emotional needs. In fact, customers are much more fickle than many marketers assume: Often the brands that are believed to depend on loyal customers have the lowest loyalty scores.”

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“You don’t need outcome data to create useful algorithms. For example, you can build a reasoned rule that predicts loan defaults quite effectively without knowing what happened to past loans; all you need is a small set of recent loan applications. Here are the [first three of five] next steps:

“1. Select six to eight variables that are distinct and obviously related to the predicted outcome. Assets and revenues (weighted positively) and liabilities (weighted negatively) would surely be included, along with a few other features of loan applications.

“2. Take the data from your set of cases (all the loan applications from the past year) and compute the mean and standard deviation of each variable in the set.

“3. For every case in the set, compute a ‘standard score’ for each variable: the difference between the value in the case and the mean of the whole set, divided by the standard deviation. With standard scores, all variables are expressed on the same scale and can be compared and leveraged.”

“Noise: How to Overcome the High, Hidden Cost of Inconsistent Decision Making,” Daniel Kahneman, Andrew M. Rosenfeld, Linnea Gandhi, and Tom Blaser

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“Executives favor a classic command-and-control approach to diversity because it boils behaviors down to dos and don’ts that are easy to understand and defend. Yet this approach also flues in the face of nearly everything we know about how to motivate people [or inspire/activate self-motivation in people] to make changes. Decades of social science research point to a simple truth: You won’t get managers on board by blaming and shaming them with rules and reeducation. Let’s look at how the most common top-down efforts typically go wrong.”

Frank Dobbin and Alexandra Kalev focus on four, then suggest several tools that are much more effective, in “Why Diversity Fails,”

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I highly recommend all of annual “HBR’s 10 Must Read” volumes in this series that began in 2015.

Note: If each of the articles in the 2018 edition were purchased separately, the total cost would be $98.45. Amazon US now sells the paperbound edition for only $16.98. That’s not a bargain; that’s a steal. In fact, all four volumes are.