Machine and the manager - changing leadership equation

Banking Frontiers|February 2020

Machine and the manager - changing leadership equation
CEOs are maturing to become ‘chief experimentation officers’, argues a report by McKinsey and Co:

Can there be a decision-making algorithm? Or as a step ahead, can such a decision-making algorithm assume the position of a board member in a corporate?

Yes, according to a new report by McKinsey and Co. It says Deep Knowledge Ventures, a Hong Kong VC firm, has ‘appointed’ such a decision-making algorithm on its board of directors.

Citing this as an instance of how leadership equations are changing with technology inching ahead to take over critical functions, the authors of the report, Martin Dewhurst and Paul Willmott, who are directors in McKinsey’s London office, argue: “...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.”

HUMAN TOUCH CRUCIAL

The two are, however, confident that if these two things happen - and they are sure they’re likely to - the role of the senior leader will evolve. “We’d suggest that, ironically enough, executives in the era of brilliant machines will be able to make the biggest difference through the human touch. By this we mean the questions they frame, their vigor in attacking exceptional circumstances highlighted by increasingly intelligent algorithms, and their ability to do things machines can’t. That includes tolerating ambiguity and focusing on the ‘softer’ side of management to engage the organization and build its capacity for self-renewal,” they say.

The report points out to instances of IBM supercomputer Watson, which has the potential to predict oncological outcomes more accurately than physicians by reviewing, storing and learning from reams of medical journal articles. In contrast, many organizations may have access to big data, but “the executives in these companies often find themselves beset by ‘polluted’ or difficult-to-parse data, whose validity is subject to vigorous internal debates,” avers the report.

Stressing that ‘garbage in/garbage out’ applies as much to supercomputers as it did 50 years ago to the IBM System/360.2, the report maintains that this management problem, which transcends CIOs and the IT organization, speaks of the “need for a turbocharged data analytics strategy, a new top-team mind-set, fresh talent approaches, and a concerted effort to break down information silos. These issues also transcend number crunching; ‘weak signals’ from social media and other sources also contain powerful insights and should be part of the data-creation process”.

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February 2020