Manager and machine: The new leadership equation

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McKinsey & Company | By Martin Dewhurst and Paul Willmott | Sep 2014

Man vs machine - Manager and machine: The new leadership equationAs artificial intelligence takes hold, what will it take to be an effective executive?

What would it take for algorithms to take over the C-suite? And what will be senior leaders’ most important contributions if they do? Our answers to these admittedly speculative questions rest on our work with senior leaders in a range of industries, particularly those on the vanguard of the big data and advanced-analytics revolution. We have also worked extensively alongside executives who have been experimenting most actively with opening up their companies and decision-making processes through crowdsourcing and social platforms within and across organizational boundaries.

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Our argument is simple: the advances of brilliant machines will astound us, but they will transform the lives of senior executives only if managerial advances enable them to. There’s still a great deal of work to be done to create data sets worthy of the most intelligent machines and their burgeoning decision-making potential. On top of that, there’s a need for senior leaders to “let go” in ways that run counter to a century of organizational development.

The contrast with the command-and-control era—when holding information close was a source of power, and information moved in one direction only, up the corporate hierarchy—could not be starker. Uncomfortable as this new world may be, the costs of the status quo are large and growing: information hoarders will slow the pace of their organizations and forsake the power of artificial intelligence while competitors exploit it.

The Human Edge

If senior leaders successfully fuel the insights of increasingly brilliant machines and devolve decision-making authority up and down the line, what will be left for top management to do?

Asking questions:  Asking the right questions of the right people at the right times is a skill set computers lack and may never acquire. Algorithms and artificial intelligence may broaden this kind of analytical complexity beyond the financial world, to a whole new set of decision areas—again placing a premium on the tough questions senior leaders can ask. Penetrating this new world of analytical complexity is likely to be difficult, and an increasingly important role for senior executives may be establishing a set of small, often improvisatory, experiments to get a better handle on the implications of emerging insights and decision rules, as well as their own managerial styles.

Attacking Exceptions:  Senior leaders will have to draw on a mixture of insight—examining exceptions to see if they require interventions, such as new credit limits for a big customer or an opportunity to start bundling a new service with an existing product—and inspiration, as leaders galvanize the organization to respond quickly and work in new ways. Exceptions may pave the way for innovation too, something we already see as leading-edge retailers and financial-services firms mine large sets of customer data.

Tolerating ambiguity:  While algorithms and supercomputers are designed to seek answers, they are likely to be most definitive on relatively small questions. The bigger and broader the inquiry, the more likely that human synthesis will be central to problem solving, because machines, though they learn rapidly, provide many pieces without assembling the puzzle. That process of assembly and synthesis can be messy and slow, placing a fresh premium on the senior leaders’ ability to tolerate ambiguity.

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Employing ‘soft’ skills:  Humans have and will continue to have a strong comparative advantage when it comes to inspiring the troops, empathizing with customers, developing talent, and the like. Sometimes, machines will provide invaluable input, as Laszlo Bock at Google has famously shown in a wide range of human-resource data-analytics efforts. But translating this insight into messages that resonate with organizations will require a human touch. No computer will ever manage by walking around. And no effective executive will try to galvanize action by saying, “we’re doing this because an algorithm told us to.”

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