Tom Cochran’s experiment yielded an interesting result about the literal cost of a seemingly harmless behavior. But the real importance of this story is the experiment itself, and in particular, its complexity. It turns out to be really difficult to answer a simple question such as: What’s the impact of our current e-mail habits on the bottom line? Cochran had to conduct a company-wide survey and gather statistics from the IT infrastructure. He also had to pull together salary data and information on typing and reading speed, and run the whole thing through a statistical model to spit out his final result. And even then, the outcome is fungible, as it’s not able to separate out, for example, how much value was produced by this frequent, expensive e-mail use to offset some of its cost.
This example generalizes to most behaviors that potentially impede or improve deep work. Even though we abstractly accept that distraction has costs and depth has value, these impacts, as Tom Cochran discovered, are difficult to measure. This isn’t a trait unique to habits related to distraction and depth: Generally speaking, as knowledge work makes more complex demands of the labor force, it becomes harder to measure the value of an individual’s efforts. The French economist Thomas Piketty made this point explicit in his study of the extreme growth of executive salaries. The enabling assumption driving his argument is that “it is objectively difficult to measure individual contributions to a firm’s output.” In the absence of such measures, irrational outcomes, such as executive salaries way out of proportion to the executive’s marginal productivity, can occur. Even though some details of Piketty’s theory are controversial, the underlying assumption that it’s increasingly difficult to measure individuals’ contributions is generally considered, to quote one of his critics, “undoubtedly true.”
We should not, therefore, expect the bottom-line impact of depth-destroying behaviors to be easily detected. As Tom Cochran discovered, such metrics fall into an opaque region resistant to easy measurement—a region I call the metric black hole. Of course, just because it’s hard to measure metrics related to deep work doesn’t automatically lead to the conclusion that businesses will dismiss it. We have many examples of behaviors for which it’s hard to measure their bottom-line impact but that nevertheless flourish in our business culture; think, for example, of the three trends that opened this chapter, or the outsize executive salaries that puzzled Thomas Piketty. But without clear metrics to support it, any business behavior is vulnerable to unstable whim and shifting forces, and in this volatile scrum deep work has fared particularly poorly.
The reality of this metric black hole is the backdrop for the arguments that follow in this chapter. In these upcoming sections, I’ll describe various mind-sets and biases that have pushed business away from deep work and toward more distracting alternatives. None of these behaviors would survive long if it was clear that they were hurting the bottom line, but the metric black hole prevents this clarity and allows the shift toward distraction we increasingly encounter in the professional world.
The Principle of Least Resistance
When it comes to distracting behaviors embraced in the workplace, we must give a position of dominance to the now ubiquitous culture of connectivity, where one is expected to read and respond to e-mails (and related communication) quickly. In researching this topic, Harvard Business School professor Leslie Perlow found that the professionals she surveyed spent around twenty to twenty-five hours a week outside the office monitoring e-mail—believing it important to answer any e-mail (internal or external) within an hour of its arrival.
You might argue—as many do—that this behavior is necessary in many fast-paced businesses. But here’s where things get interesting: Perlow tested this claim. In more detail, she convinced executives at the Boston Consulting Group, a high-pressure management consulting firm with an ingrained culture of connectivity, to let her fiddle with the work habits of one of their teams. She wanted to test a simple question: Does it really help your work to be constantly connected? To do so, she did something extreme: She forced each member of the team to take one day out of the workweek completely off—no connectivity to anyone inside or outside the company.
“At first, the team resisted the experiment,” she recalled about one of the trials. “The partner in charge, who had been very supportive of the basic idea, was suddenly nervous about having to tell her client that each member of her team would be off one day a week.” The consultants were equally nervous and worried that they were “putting their careers in jeopardy.” But the team didn’t lose their clients and its members did not lose their jobs. Instead, the consultants found more enjoyment in their work, better communication among themselves, more learning (as we might have predicted, given the connection between depth and skill development highlighted in the last chapter), and perhaps most important, “a better product delivered to the client.”
This motivates an interesting question: Why do so many follow the lead of the Boston Consulting Group and foster a culture of connectivity even though it’s likely, as Perlow found in her study, that it hurts employees’ well-being and productivity, and probably doesn’t help the bottom line? I think the answer can be found in the following reality of workplace behavior.
The Principle of Least Resistance: In a business setting, without clear feedback on the impact of various behaviors to the bottom line, we will tend toward behaviors that are easiest in the moment.
To return to our question about why cultures of connectivity persist, the answer, according to our principle, is because it’s easier. There are at least two big reasons why this is true. The first concerns responsiveness to your needs. If you work in an environment where you can get an answer to a question or a specific piece of information immediately when the need arises, this makes your life easier—at least, in the moment. If you couldn’t count on this quick response time you’d instead have to do more advance planning for your work, be more organized, and be prepared to put things aside for a while and turn your attention elsewhere while waiting for what you requested. All of this would make the day to day of your working life harder (even if it produced more satisfaction and a better outcome in the long term). The rise of professional instant messaging, mentioned earlier in this chapter, can be seen as this mind-set pushed toward an extreme. If receiving an e-mail reply within an hour makes your day easier, then getting an answer via instant message in under a minute would improve this gain by an order of magnitude.
The second reason that a culture of connectivity makes life easier is that it creates an environment where it becomes acceptable to run your day out of your inbox—responding to the latest missive with alacrity while others pile up behind it, all the while feeling satisfyingly productive (more on this soon). If e-mail were to move to the periphery of your workday, you’d be required to deploy a more thoughtful approach to figuring out what you should be working on and for how long. This type of planning is hard. Consider, for example, David Allen’s Getting Things Done task-management methodology, which is a well-respected system for intelligently managing competing workplace obligations. This system proposes a fifteen-element flowchart for making a decision on what to do next! It’s significantly easier to simply chime in on the latest cc’d e-mail thread.
I’m picking on constant connectivity as a case study in this discussion, but it’s just one of many examples of business behaviors that are antithetical to depth, and likely reducing the bottom-line value produced by the company, that nonetheless thrive because, in the absence of metrics, most people fall back on what’s easiest.