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SPOTLIGHT

Rethinking Efficiency

Beginning with Adam Smith, business thinkers have steadfastly regarded the elimination of waste as management’s holy grail. But what if the negative effects from the pursuit of efficiency eclipse the rewards?

page 049

The High Price of Efficiency

The managerial belief in the unalloyed virtue of efficiency is as strong as ever. It is embodied in multilateral organizations aimed at making trade more efficient; ensconced in foreign direct-investment liberalization, deregulation, privatization, and waste-fighting governments; and promoted in the classrooms of every business school on the planet. But, argues Roger Martin, director of the Martin Prosperity Institute, an excessive focus on efficiency produces startlingly negative effects and creates the potential for social disorder, as rewards go to an increasingly limited number of efficient competitors. The remedy, he says, is a stronger focus on a less immediate source of competitive advantage: resilience. To this end, organizations can limit scale, introduce productive friction, promote patient capital, create good jobs, and change the way we teach.

Success Breeds Inequality: What the Data Shows

Graphical depictions of the state of play since the Great Recession, showing that the wealthiest individuals and companies are pulling further and further away from the rest.

“The Costs of Complexity Are Hard to See”Jim Hackett, CEO of Ford Motor Company, talks with HBR about what he calls

corporate fitness and how he has applied it at Ford and, previously, at the office

furniture company Steelcase.

HBR Reprint R1901B

The Hard Truth About Innovative Cultures

Gary P. Pisano | page 086

Innovative cultures are generally depicted as pretty fun. They’re characterized by a tolerance for failure and a willingness to experiment. They’re seen as being psychologically safe, highly collaborative, and nonhierarchical. And research suggests that these behaviors translate into better innovative performance. But despite the fact that innovative cultures are desirable, and that most leaders claim to understand what they entail, they are hard to create and sustain.

That’s because the easy-to-like behaviors that get so much attention are only one side of the coin. They must be counterbalanced by some tougher and frankly less fun behaviors: an intolerance for incompetence, rigorous discipline, brutal candor, a high level of individual accountability, and strong leadership.Unless the tensions created by this paradox are carefully managed, attempts to create an innovative culture will fail.

HBR Reprint R1901C

Calculating the value of impact investing

Chris Addy et al. | page 096

Impact investing—directing capital to ventures that are expected to yield social and environmental benefits as well as profits—provides investors with a way to “do well by doing good.” But whereas the business world has tools for estimating a potential investment’s financial yield, it lacks them for estimating social rewards in dollar terms. Now the Rise Fund and the Bridgespan Group have developed what they call the impact multiple of money (IMM) to demonstrate the value of putting impact underwriting on the same footing as financial underwriting. In this article they explain their six-step process for calculating it: (1) Assess the relevance and scale of a potential product, service, or project. (2) Identify target social or environmental outcomes. (3) Estimate the economic value of those outcomes to society. (4) Adjust for risks. (5) Estimate terminal value. (6) Calculate the social return on every dollar spent. The IMM, they write, “offers a rigorous methodology to advance the art of allocating capital to achieve social benefit.”

HBR Reprint R1901G

Data science and the art of persuasion

Scott Berinato | page 106

Despite heavy investments to acquire talented data scientists and take advantage of the analytics boom, many companies have been disappointed in the results. The problem is that those scientists are trained to ask smart questions, wrangle the relevant data, and uncover insights—but not to communicate what those insights mean for the business. To be successful, the author writes, a data science team needs six talents: project management, data wrangling, data analysis, subject expertise, design, and storytelling. He outlines four steps for achieving that success: (1) Define talents, not team members. (2) Hire to create a portfolio of necessary talents. (3) Expose team members to talents they don’t have. (4) Structure projects around talents.

HBR Reprint R1901K