"As Big Data and AI Take Hold, What Will It Take to Be an Effective Executive?" or Keeping the C-suite With Algos at the Gate

From Irving Wladawsky-Berger:

Big data, powerful analytics and AI are everywhere.  After years of promise and hype, technology is now being applied to activities that not long ago were viewed as the exclusive domain of humans.  Our digital revolution had led to amazing applications, but also to considerable pain for many workers who’ve been experiencing declining employment and wages.  Mid-skill jobs have been particularly threatened.  Many of these jobs, - which include blue-collar production activities as well as information-based white-collar ones, - are based on well understood procedures that can be described by a set of rules that machines can then follow. 

But, what will be the impact of our increasingly intelligent machines on senior management positions?  In principle, such jobs deal with non-routine, cognitive tasks requiring high human skills, including expert problem solving, complex decision-making and sophisticated communications for which there are no rule-based solutions.  “As artificial intelligence takes hold, what will it take to be an effective executive?” asks a recent McKinsey article - Manager and Machine: The new leadership equation.  “What would it take for algorithms to take over the C-suite?  And what will be senior leaders’ most important contributions if they do?” 

After asking these questions to senior managers across a broad range of industries, McKinsey  concluded that two key things need to happen for technology to more deeply transform their jobs.  First, much still needs to be done to create the proper data sets that would enable intelligent computers to assist in decision-making.  Garbage in, garbage out applies as much to data analysis today as it has to computing in general since its early years.  Organizations must have a data-analytics strategy that cuts across internal informational silos and properly incorporates external information sources like social media. 

And most important, senior managers must learn to let go, something which is quite difficult because it runs counter to decades of organizational practices.  Given our rapidly rising oceans of data, the command-and-control approach to management, where information flows up the organization and decisions are made at high levels, would sink the senior executive teams.  As data science and AI permeate the organization, it’s important to delegate more autonomy to the business units that hopefully have the proper skills, the advanced tools and the necessary information to make better decisions on their own.

While difficult, these changes will eventually happen, providing leading-edge companies with a competitive advantage that others will emulate.  But, if top managers do their job, - enabling data-driven decision-making and devolving decision-making authority across the organization, - what will be left for them to do?  “A great deal,” notes the article, suggesting that “ironically enough, executives in the era of brilliant machines will be able to make the biggest difference through the human touch,” including:

Asking questions.  “Asking the right questions of the right people at the right times is a skill set computers lack and may never acquire…  In fact, there’s a case for using an executive’s domain expertise to frame the upfront questions that need asking and then turning the machines loose to answer those questions.  That’s a role for the people with an organization’s strongest judgment: the senior leaders.”

Attacking exceptions.  “An increasingly important element of each leader’s management tool kit is likely to be the ability to attack problematic exceptions vigorously.  Smart machines should get better and better at telling managers when they have a problem…  Executives can therefore spend less time on day-to-day management issues, but when the exception report signals a difficulty, the ability to spring into action will help executives differentiate themselves and the health of their organizations."...

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