Emergence of algorithmic management challenges the role of many human managers.
Joyce is a head of a large team of consultants at a global IT services company. In her role, Joyce has direct responsibility of more than 100 employees who are in charge of pricing, market research, designing advertising and promotions. Joyce is responsible for facilitating growth, sales and marketing strategy which requires her to quickly react to changing circumstances, and coordinating many different styles of thinking in a single team.
“That’s too many for anyone to manage well per today’s models of management,” says Helen Poitevin, research director at Gartner. “Managers in that position cannot effectively coach and develop workers or have a strong-enough working relationships with them to provide good support at times of personal crisis, involving, for example, illness, family problems and ‘burn-out’.”
Beyond a certain span of control, managers cannot coach effectively.
Learn from Robobosses
Managers in such environments who cannot yet be replaced by algorithms can use some emerging machine-learning technologies to coach resources for their employees. Gartner predicts that by 2018, the first virtual career coach will emerge, providing just-in-time advice to employees to improve performance.
Artificial intelligence will enable increasing spans of control for managers who are not replaced. The pervasiveness of the Internet of Things, including the increasing number of sensors, leads to ample opportunity to monitor, predict, and support worker performance, negating the need for direct manager support. UPS drivers, for example, use on-road integrated optimization and navigation (ORION). ORION uses expansive fleet telematics and advanced algorithms to gather and calculate large amounts of data to provide UPS drivers with optimized routes.
A Roboboss Can Manage Thousands of Workers
As well as executing on her strategic duties Joyce has a multitude of additional typical management tasks to perform ranging from hiring staff, assigning work, sanctioning underperformers, coaching and developing workers to name a few. Business executives will need to rely on AI or smart machines to be able to manage a very large number of workers, or a combination of workers and bots – far more than a human could manage.
Where activities can be easily defined and assigned, and where performance can be monitored in an automated way, a single platform and algorithm can manage thousands of workers and eliminate layers or management. Such situations already exist with ride-sharing platforms like those of Uber and Lyft. Automated systems already manage task assignment, incentivize certain driver behaviors, monitor performance and sanction poor performers.
Gartner predicts that by 2018, over 3 million workers globally will be supervised by a roboboss.
Robobosses can function only in certain contexts. They are most suitable where work assignment and performance monitoring can be fully automated, and where workers are relatively autonomous.
Today, AI-supported technologies are already helping human managers and workers make better decisions. They provide automated recommendations as it relates to hiring, rewarding, supporting career development, providing performance feedback, and listening to employee sentiment.
“On its own, a roboboss cannot support all people management tasks, and are effective only as long as it can rely on networks of peer mentors and other means of social support for staff members,” Poitevin concludes.
Gartner clients can learn more about the impact of AI in the enterprise in the report “Plan to Use Smart Machines as Robobosses” by Helen Poitevin.
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