Deep Work: Rules for Focused Success in a Distracted World

by Cal Newport

Deep Work: Professional activities performed in a state of distraction-free concentration that push your cognitive capabilities to their limit. These efforts create new value, improve your skill, and are hard to replicate.

The ubiquity of deep work among influential individuals is important to emphasize because it stands in sharp contrast to the behavior of most modern knowledge workers—a group that’s rapidly forgetting the value of going deep. The reason knowledge workers are losing their familiarity with deep work is well established: network tools. This is a broad category that captures communication services like e-mail and SMS, social media networks like Twitter and Facebook, and the shiny tangle of infotainment sites like BuzzFeed and Reddit. In aggregate, the rise of these tools, combined with ubiquitous access to them through smartphones and networked office computers, has fragmented most knowledge workers’ attention into slivers.

Shallow Work: Noncognitively demanding, logistical-style tasks, often performed while distracted. These efforts tend to not create much new value in the world and are easy to replicate.

The Deep Work Hypothesis: The ability to perform deep work is becoming increasingly rare at exactly the same time it is becoming increasingly valuable in our economy. As a consequence, the few who cultivate this skill, and then make it the core of their working life, will thrive.

This compressed schedule is possible because I’ve invested significant effort to minimize the shallow in my life while making sure I get the most out of the time this frees up. I build my days around a core of carefully chosen deep work, with the shallow activities I absolutely cannot avoid batched into smaller bursts at the peripheries of my schedule. Three to four hours a day, five days a week, of uninterrupted and carefully directed concentration, it turns out, can produce a lot of valuable output.

“The key question will be: are you good at working with intelligent machines or not?” Nate Silver, of course, with his comfort in feeding data into large databases, then siphoning it out into his mysterious Monte Carlo simulations, is the epitome of the high-skilled worker. Intelligent machines are not an obstacle to Silver’s success, but instead provide its precondition.

A venture capitalist in today’s economy can fund a company like Instagram, which was eventually sold for a billion dollars, while employing only thirteen people. When else in history could such a small amount of labor be involved in such a large amount of value? With so little input from labor, the proportion of this wealth that flows back to the machine owners—in this case, the venture investors—is without precedent. It’s no wonder that a venture capitalist I interviewed for my last book admitted to me with some concern, “Everyone wants my job.”

Let’s pull together the threads spun so far: Current economic thinking, as I’ve surveyed, argues that the unprecedented growth and impact of technology are creating a massive restructuring of our economy. In this new economy, three groups will have a particular advantage: those who can work well and creatively with intelligent machines, those who are the best at what they do, and those with access to capital.

If you can join any of these groups, therefore, you’ll do well. If you cannot, you might still do well, but your position is more precarious. The question we must now face is the obvious one: How does one join these winners? At the risk of quelling your rising enthusiasm, I should first confess that I have no secret for quickly amassing capital and becoming the next John Doerr. (If I had such secrets, it’s unlikely I’d share them in a book.) The other two winning groups, however, are accessible. How to access them is the goal we tackle next.

Two Core Abilities for Thriving in the New Economy 1. The ability to quickly master hard things. 2. The ability to produce at an elite level, in terms of both quality and speed.

This ability to produce also applies to those looking to master intelligent machines. It wasn’t enough for Nate Silver to learn how to manipulate large data sets and run statistical analyses; he needed to then show that he could use this skill to tease information from these machines that a large audience cared about. Silver worked with many stats geeks during his days at Baseball Prospectus, but it was Silver alone who put in the effort to adapt these skills to the new and more lucrative territory of election forecasting. This provides another general observation for joining the ranks of winners in our economy: If you don’t produce, you won’t thrive—no matter how skilled or talented you are.

Deep Work Helps You Quickly Learn Hard Things “Let your mind become a lens, thanks to the converging rays of attention; let your soul be all intent on whatever it is that is established in your mind as a dominant, wholly absorbing idea.” This advice comes from Antonin-Dalmace Sertillanges, a Dominican friar and professor of moral philosophy, who during the early part of the twentieth century penned a slim but influential volume titled The Intellectual Life.

This task of formalization began in earnest in the 1970s, when a branch of psychology, sometimes called performance psychology, began to systematically explore what separates experts (in many different fields) from everyone else. In the early 1990s, K. Anders Ericsson, a professor at Florida State University, pulled together these strands into a single coherent answer, consistent with the growing research literature, that he gave a punchy name: deliberate practice. Ericsson opens his seminal paper on the topic with a powerful claim: “We deny that these differences [between expert performers and normal adults] are immutable… Instead, we argue that the differences between expert performers and normal adults reflect a life-long period of deliberate effort to improve performance in a specific domain.”

This brings us to the question of what deliberate practice actually requires. Its core components are usually identified as follows: (1) your attention is focused tightly on a specific skill you’re trying to improve or an idea you’re trying to master; (2) you receive feedback so you can correct your approach to keep your attention exactly where it’s most productive. The first component is of particular importance to our discussion, as it emphasizes that deliberate practice cannot exist alongside distraction, and that it instead requires uninterrupted concentration. As Ericsson emphasizes, “Diffused attention is almost antithetical to the focused attention required by deliberate practice” (emphasis mine).

To be great at something is to be well myelinated.

The reason, therefore, why it’s important to focus intensely on the task at hand while avoiding distraction is because this is the only way to isolate the relevant neural circuit enough to trigger useful myelination. By contrast, if you’re trying to learn a complex new skill (say, SQL database management) in a state of low concentration (perhaps you also have your Facebook feed open), you’re firing too many circuits simultaneously and haphazardly to isolate the group of neurons you actually want to strengthen.

But this sequence of thinking about thinking points to an inescapable conclusion: To learn hard things quickly, you must focus intensely without distraction. To learn, in other words, is an act of deep work.

Adam Grant produces at an elite level. When I met Grant in 2013, he was the youngest professor to be awarded tenure at the Wharton School of Business at Penn. A year later, when I started writing this chapter (and was just beginning to think about my own tenure process), the claim was updated: He’s now the youngest full professor* at Wharton.

Something I noticed in these interviews is that the very best students often studied less than the group of students right below them on the GPA rankings. One of the explanations for this phenomenon turned out to be the formula detailed earlier: The best students understood the role intensity plays in productivity and therefore went out of their way to maximize their concentration—radically reducing the time required to prepare for tests or write papers, without diminishing the quality of their results.

Leroy introduced an effect she called attention residue. In the introduction to this paper, she noted that other researchers have studied the effect of multitasking—trying to accomplish multiple tasks simultaneously—on performance, but that in the modern knowledge work office, once you got to a high enough level, it was more common to find people working on multiple projects sequentially: “Going from one meeting to the next, starting to work on one project and soon after having to transition to another is just part of life in organizations,” Leroy explains.

The problem this research identifies with this work strategy is that when you switch from some Task A to another Task B, your attention doesn’t immediately follow—a residue of your attention remains stuck thinking about the original task. This residue gets especially thick if your work on Task A was unbounded and of low intensity before you switched, but even if you finish Task A before moving on, your attention remains divided for a while.

The results from this and her similar experiments were clear: “People experiencing attention residue after switching tasks are likely to demonstrate poor performance on that next task,” and the more intense the residue, the worse the performance.

The concept of attention residue helps explain why the intensity formula is true and therefore helps explain Grant’s productivity. By working on a single hard task for a long time without switching, Grant minimizes the negative impact of attention residue from his other obligations, allowing him to maximize performance on this one task. When Grant is working for days in isolation on a paper, in other words, he’s doing so at a higher level of effectiveness than the standard professor following a more distracted strategy in which the work is repeatedly interrupted by residue-slathering interruptions.

When we step back from these individual observations, we see a clear argument form: To produce at your peak level you need to work for extended periods with full concentration on a single task free from distraction. Put another way, the type of work that optimizes your performance is deep work.

This rule of specificity should be applied to similar counterexamples that come to mind while reading the rest of this book. There are, we must continually remember, certain corners of our economy where depth is not valued. In addition to executives, we can also include, for example, certain types of salesmen and lobbyists, for whom constant connection is their most valued currency. There are even those who manage to grind out distracted success in fields where depth would help.

Put another way: Deep work is not the only skill valuable in our economy, and it’s possible to do well without fostering this ability, but the niches where this is advisable are increasingly rare. Unless you have strong evidence that distraction is important for your specific profession, you’re best served, for the reasons argued earlier in this chapter, by giving serious consideration to depth.

In the last chapter, I argued that deep work is more valuable than ever before in our shifting economy. If this is true, however, you would expect to see this skill promoted not just by ambitious individuals but also by organizations hoping to get the most out of their employees. As the examples provided emphasize, this is not happening. Many other ideas are being prioritized as more important than deep work in the business world, including, as we just encountered, serendipitous collaboration, rapid communication, and an active presence on social media.

The rareness of deep work, I’ll argue, is not due to some fundamental weakness of the habit. When we look closer at why we embrace distraction in the workplace we’ll find the reasons are more arbitrary than we might expect—based on flawed thinking combined with the ambiguity and confusion that often define knowledge work. My objective is to convince you that although our current embrace of distraction is a real phenomenon, it’s built on an unstable foundation and can be easily dismissed once you decide to cultivate a deep work ethic.

Just how much time were employees of Atlantic Media spending moving around information instead of focusing on the specialized tasks they were hired to perform? Determined to answer this question, Cochran gathered company-wide statistics on e-mails sent per day and the average number of words per e-mail. He then combined these numbers with the employees’ average typing speed, reading speed, and salary. The result: He discovered that Atlantic Media was spending well over a million dollars a year to pay people to process e-mails, with every message sent or received tapping the company for around ninety-five cents of labor costs. “A ‘free and frictionless’ method of communication,” Cochran summarized, “had soft costs equivalent to procuring a small company Learjet.”

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.

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.

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.

To do real good physics work, you do need absolute solid lengths of time… it needs a lot of concentration… if you have a job administrating anything, you don’t have the time. So I have invented another myth for myself: that I’m irresponsible. I’m actively irresponsible. I tell everyone I don’t do anything. If anyone asks me to be on a committee for admissions, “no,” I tell them: I’m irresponsible. Feynman was adamant in avoiding administrative duties because he knew they would only decrease his ability to do the one thing that mattered most in his professional life: “to do real good physics work.” Feynman, we can assume, was probably bad at responding to e-mails and would likely switch universities if you had tried to move him into an open office or demand that he tweet. Clarity about what matters provides clarity about what does not.

Busyness as Proxy for Productivity: In the absence of clear indicators of what it means to be productive and valuable in their jobs, many knowledge workers turn back toward an industrial indicator of productivity: doing lots of stuff in a visible manner.

This mind-set is not necessarily irrational. For some, their jobs really do depend on such behavior. In 2013, for example, Yahoo’s new CEO Marissa Mayer banned employees from working at home. She made this decision after checking the server logs for the virtual private network that Yahoo employees use to remotely log in to company servers. Mayer was upset because the employees working from home didn’t sign in enough throughout the day. She was, in some sense, punishing her employees for not spending more time checking e-mail (one of the primary reasons to log in to the servers). “If you’re not visibly busy,” she signaled, “I’ll assume you’re not productive.”

After five years of science reporting, she came away convinced that she was witness to a “grand unified theory” of the mind: Like fingers pointing to the moon, other diverse disciplines from anthropology to education, behavioral economics to family counseling, similarly suggest that the skillful management of attention is the sine qua non of the good life and the key to improving virtually every aspect of your experience. This concept upends the way most people think about their subjective experience of life. We tend to place a lot of emphasis on our circumstances, assuming that what happens to us (or fails to happen) determines how we feel. From this perspective, the small-scale details of how you spend your day aren’t that important, because what matters are the large-scale outcomes, such as whether or not you get a promotion or move to that nicer apartment. According to Gallagher, decades of research contradict this understanding. Our brains instead construct our worldview based on what we pay attention to. If you focus on a cancer diagnosis, you and your life become unhappy and dark, but if you focus instead on an evening martini, you and your life become more pleasant—even though the circumstances in both scenarios are the same. As Gallagher summarizes: “Who you are, what you think, feel, and do, what you love—is the sum of what you focus on.”

Even if your colleagues are all genial and your interactions are always upbeat and positive, by allowing your attention to drift over the seductive landscape of the shallow, you run the risk of falling into another neurological trap identified by Gallagher: “Five years of reporting on attention have confirmed some home truths,” Gallagher reports. “[Among them is the notion that] ‘the idle mind is the devil’s workshop’… when you lose focus, your mind tends to fix on what could be wrong with your life instead of what’s right.” A workday driven by the shallow, from a neurological perspective, is likely to be a draining and upsetting day, even if most of the shallow things that capture your attention seem harmless or fun.

At the time, this finding pushed back against conventional wisdom. Most people assumed (and still do) that relaxation makes them happy. We want to work less and spend more time in the hammock. But the results from Csikszentmihalyi’s ESM studies reveal that most people have this wrong: Ironically, jobs are actually easier to enjoy than free time, because like flow activities they have built-in goals, feedback rules, and challenges, all of which encourage one to become involved in one’s work, to concentrate and lose oneself in it. Free time, on the other hand, is unstructured, and requires much greater effort to be shaped into something that can be enjoyed.

Human beings, it seems, are at their best when immersed deeply in something challenging.

This, ultimately, is the lesson to come away with from our brief foray into the world of experimental psychology: To build your working life around the experience of flow produced by deep work is a proven path to deep satisfaction.