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.”
- 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.”
- 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… 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’… simultaneous growth in the importance of softer management skills and technology savvy will boost the complexity and richness of the senior-executive role.”
Enabling innovation across the organization, - especially open, collaborative, multidisciplinary innovation, - is one of the key roles for senior leaders in a world of smart machines. A few years ago I read a very interesting book, Innovation - the Missing Dimension, by MIT professors Richard Lester and Michael Piore. The book explored the essence of innovation in new product development by examining a few truly novel products in different market areas. The authors concluded that innovation involves two fundamental processes: analysis and interpretation.
Analysis is essentially rational, quantitative, data-driven decision making and problem solving. Given its reliance on data, and algorithms, this is what data science and AI are particularly good at. It’s the standard approach underlying management and engineering practice. It involves a relatively linear set of steps and works quite well when you are looking for a solution to a relatively well defined problem.
But where do the problems come from in the first place? How do you decide what problems to work on and try to solve? This second kind of innovation, - which the book called interpretation - is very different in nature from analysis. You are not solving a problem but looking for a new insight about customers and the marketplace, a new idea for a product or a service, a new approach to producing and delivering them, a new business model.
Their research showed that interpretive innovation generally takes place through a process of conversations among people and organizations with different backgrounds and perspectives, until the problems can be identified and clarified to the point where a solution can be developed. It requires curiosity, imagination, and a business culture that encourages these conversations and removes the organizational barriers that might prevent them from taking place.
What can executives do to create such a culture? The authors offer a novel metaphor. They liken the role of the executive in encouraging such conversations to the role of a good hostess at a cocktail party “identifying the guests, bringing them to the party, suggesting who should talk to whom and what they might talk about, intervening as necessary to keep the conversations flowing, and generally navigating between the shoals of boredom and hostility, either of which would cause the party to break up and the participants to leave.” In the end, this is what collaborative innovation is all about.
Let me conclude with a few words about leadership, - the most important executive human touch, and one that’s particularly critical in our fast changing, unpredictable times. “Leadership is ultimately about creating a way for people to contribute to making something extraordinary happen,” notes its Wikipedia entry. People often use leadership and management interchangeably. The clearest distinction I've heard between the two terms was succinctly given a few years ago by former IBM CEO Lou Gerstner at a seminar in MIT: you manage business results and processes; you lead people.
Leadership cannot be delegated the way you can delegate management tasks. Management skills tend to be quantitative in nature, and are suitable to be significantly enhanced by technology. But leadership is about people and organizational culture. The key quality you need for good leadership is passion - instilling a sense of urgency in the people around you to attack and solve the complex problems that all organizations face.
Advanced technologies, data science and AI, - all wisely deployed across the organization, - should help executives better deal with the many tasks and decisions that consume so much of their time. “This will be liberating” notes the McKinsey article, “but also raises the bar for the executive’s ability to master the human dimensions that ultimately will provide the edge in the era of brilliant machines.”