“I was productive.” Everyone has heard those words before, and everyone knows what they mean: “Today I answered a lot of emails, I wrote some reports, and I didn’t get interrupted by meetings or inane banter from my coworkers.”
This is the cult of individual productivity. It’s appealing in its simplicity: focus only on your solo tasks, log lots of hours, and good results will follow. It’s also unmitigated bullshit.
In the vast majority of companies, it is groups and teams, not individuals, that create the important output. The code written by a software developer is not a fully functioning product. The retail store manager doesn’t market, sell, and stock the shelves. As we create more and more complex things, it becomes increasingly difficult to produce anything meaningful as an individual unit.
That’s why we’re in organizations: to do things together that we couldn’t do by ourselves. Outside the US and Europe, this is understood, although not necessarily explicitly rewarded.
In Japan, for example, you’re expected to eat lunch, and often dinner, with your coworkers. This is not viewed as wasting time. Rather, it’s viewed as a responsibility and investment in the cohesion of your team. Compare that mealtime expectation to that of the US workplace, where eating a sandwich while you’re working at your desk is often the norm.
Mathematically, it’s not hard to show the value of this group-oriented approach. Let’s take a hypothetical example. Imagine you figure out a new way to do something at work, saving you five hours each week. Over a year, you’ll save 260 hours.
Now suppose you spent 10 hours teaching this work hack to 10 of your colleagues. At the end of the year, your productivity would be 4% lower (you’d only save 250 hours in total). But your 10 coworkers would save a combined 2,600 hours. If you didn’t take the time to share that tip, the company would have lost out on a huge amount of increased productivity.
While this is a hypothetical example, we can examine data from the real world to prove the same effect. One of our customers, a major IT firm that configures multi-million dollar server systems, pays its employees based on individual performance. They measure how long it takes employees to complete tasks, which can take anywhere from 5 minutes to 8 hours, by capturing the exact start and end times. At the same time, using a combination of next-generation ID badges and digital communication metadata, we were able to analyze how people actually work.
The data revealed that there were a small number of people to whom almost everyone ended up speaking with during a task. After speaking with this informal expert, workers completed that task 66% more quickly. They were getting tips on how to complete their task.
In an average month, the efforts of an informal expert saved around 265 hours of work. That’s critical for the company. However, the informal experts’ individual productivity was statistically average. They were paid just as much as everyone else because they were only measured on individual output.
This example shows how individual performance can mask group effects, but let’s go a level higher. For complex engineering projects, an individual’s work depends on the work of hundreds, or thousands, of other people. If communication breaks down, it takes over 30% longer to complete that code. Rather than spending an extra 8 hours coding, software developers could invest a few hours in communicating with their colleagues and more than make up for the lost individual effort.
These results validate the intuition: group productivity is more important than individual output. Of course, figuring out the exact sweet spot between individual output and group effects is difficult to pin down for all job types. Measuring both group output and behaviors in each organization, and role, is critical. This data will lead us to change incentives and processes, measure the impact of management changes on these collaboration patterns, and change the meaning of “working hard.” In the future, an employee hanging out by the coffee machine for 4 hours on Monday chatting with coworkers, or taking a leisurely stroll with someone from another team, might fall into our definition of productivity.
Ben Waber is the president and CEO of Humanyze.