Why You Can’t Manage Humans Like They’re Software
Early on at Amazon, CEO Jeff Bezos famously issued a memo about how software was to be built at the company. Teams would share their data through service interfaces, or APIs, the same way that they would share it with an outside customer. That meant that a developer on one team didn’t need to know anything about how another team operated in order to integrate the product it made—he or she could follow the documentation and use that product as though it were an external service. Ultimately, this ease of cooperation became extremely efficient and is what paved the way for Amazon Web Services—a $6.7 billion business that powers huge parts of the web (including Netflix).
Georgetown University computer science professor Cal Newport recently argued that a similar idea could be applied to humans, or the way that leaders put together teams. By defining each person’s work as a collection of inputs and outputs, leaders could define communication protocols to reduce the overhead of collaboration (often measured in meetings) and allow for greater efficiency in communication across teams and more “deep work.”
This is the kind of extreme stance that Newport is known for—the kind of thing that makes him well known and successful as a theoretical computer science academic and author. I learn a lot from what he writes; I never apply it to the same extent.
