Managing the Bots That Are Managing the Business

Editor’s Note: This article is one of a special series of 14 commissioned essays MIT Sloan Management Review is publishing to celebrate the launch of our new Frontiers initiative. Each essay gives the author’s response to this question:

“Within the next five years, how will technology change the practice of management in a way we have not yet witnessed?”

Science fiction writer William Gibson once said, “The future is already here. It’s just not very evenly distributed.” You don’t need to wait five years to see how technology will change the practice of management. You just need to study companies that are already living in the future that remains around the corner for everyone else.

You must also reframe what you see so that you aren’t blinded by what you already know. Consider Google, Facebook, Amazon.com, or a host of more recent Silicon Valley startups. They employ tens of thousands of workers. If you think with a 20th century factory mindset, those workers spend their days grinding out products, just like their industrial forebears; only today, they are producing software rather than physical goods. If, instead, you step back and view these organizations with a 21st century mindset, you realize that a large part of the work of these companies — delivering search results, news and information, social network status updates, and relevant products for purchase — is performed by software programs and algorithms. These programs are the workers, and the human software developers who create them are their managers.

Each day, these “managers” take in feedback about their electronic workers’ performance — as measured in real-time data from the marketplace — and they provide feedback to the workers in the form of minor tweaks and updates to their programs or algorithms. The human managers also have their own managers, but hierarchies are often flat, and multiple levels of management are aligned around a set of data-driven “objectives and key results” (OKRs) that are measurable in a way that allows even the electronic “workers” to be guided by these objectives.

And if your notion of management isn’t stretched enough, consider that the algorithms themselves are sometimes the managers — of human workers. Look at Uber Technologies Inc. and Lyft Inc. as compared to an old-school taxi service. Cars are dispatched not by a person but by a “management” program that collects passenger requests in real time and serves them to the closest available drivers. Humans are still in the loop both as workers delivering the actual service and as managers who set the rules of the algorithms, test whether they are working correctly, and adjust them when they are not. Human managers are called in to deal directly with the human workers, the drivers, only under rare circumstances.

While it is early in this process, you can make the case that the core function of management has gone from managing the business to managing the bots that are managing the business.

Some further implications of this insight include:

• A typical programmer in a 20th century IT shop was a worker building to a specification, not that different from a shop floor worker assembling a predefined product. A 21st century software developer is deeply engaged in product design and iterative, customer-focused development. For larger programs, this is a team exercise, and leadership means organizing a shared creative vision. Technology is not a back-office function. It is central to the management capability of the entire organization. And companies whose CEOs are also the chief product designers (think Larry Page of Alphabet Inc., Jeff Bezos of Amazon, or Apple under Steve Jobs) can outperform those whose leaders lack the capability to lead not just their human workers but their electronic workers as well.

• In 20th century organizations, you gained influence by gaining budget to hire more workers. In 21st century organizations, you gain effectiveness through your ability to create more workers — of the 21st century variety. Even in jobs that are not considered “programming jobs,” the ability to create and marshal electronic resources is key to advancement. A salesperson who can write a bot to “scrape” LinkedIn for leads has an edge over someone who has to do it manually. A marketer who can build an online survey or data-gathering app has an advantage over one who has to hire an outside company. A designer/developer who can build a working application prototype is more valuable than a designer who is only able to draw a picture.

• Managers must become product and experience designers, deeply engaged with customers and their needs, creating services that start out as a compelling promise and get better over time the more people use them, via a “build-measure-learn” process. A service like Uber is based on a deep rethinking of the fundamental work flows of on-demand transportation (what used to be called “taxis”) in light of what technology now makes possible. Before Uber, who would have thought that a passenger could summon a car to a specific spot and know just when they were going to be picked up? Yet that capability was already lying latent in smartphones.

• There is an arc to knowledge in which expertise becomes embodied in products. Workers can be “upskilled” not just by training but by software assistants that allow them to do jobs for which they were previously under-qualified. “The Knowledge,” the legendary test that London taxicab drivers must pass, requires years of study, yet with the aid of Waze, Google Maps, and the Uber or Lyft app, virtually anyone can become a driver for hire, even in a strange city. There is a lot of fear about technology replacing workers, but in what I call “Next Economy companies,” technology is used to create new opportunities by augmenting workers.

We are just at the beginning of the transformation from an economy dominated by human workers to one dominated by electronic workers. The great management challenge of the next few decades will be understanding how to get the best out of both humans and machines, and understanding the ins and outs of who manages whom.

This article was originally published on May 31, 2016. It has been updated to reflect edits made for its inclusion in our Fall 2016 print edition.