Slow Productivity: The Lost Art of Accomplishment Without Burnout

“We are overworked and overstressed, constantly dissatisfied, and reaching for a bar that keeps rising higher and higher,” writes Celeste Headlee in the introduction to Do Nothing. A few years earlier, this sentiment might have seemed provocative. By the time the pandemic peaked, however, she was preaching to the choir.

As I witnessed this fast-growing discontent, it became clear to me that something important was happening. Knowledge workers were exhausted—burned out from an increasingly relentless busyness. The pandemic didn’t introduce this trend so much as push its worst excesses beyond the threshold of tolerability. More than a few knowledge workers, thrust suddenly into remote work, their kids screaming in the next room as they suffered through yet another Zoom meeting, began to wonder, “What are we really doing here?”

I began extensively covering knowledge worker discontent, as well as alternative constructions of professional meaning, on my long-standing newsletter, as well as on a new podcast I launched early in the pandemic. As the anti-productivity movement continued to pick up speed, I also began to cover the topic more frequently in my reporting for The New Yorker, where I’m on the contributor staff, ultimately leading, during the fall of 2021, to my taking on a twice-a-month column called Office Space that was dedicated to this subject.

The storylines I uncovered were complicated. People were overwhelmed, but the sources of this increasing exhaustion weren’t obvious. Online discussion of these issues offered no shortage of varied, and sometimes contradictory, theories: Employers were relentlessly increasing the demands on their employees in an attempt to extract more value from their labor. No, it’s actually an internalized culture valorizing busyness, driven by online productivity influencers, that’s leading to our exhaustion. Or maybe what we’re really seeing is the inevitable collapse of “last-stage capitalism.” Fingers were pointed and frustrations vented; all the while, knowledge workers continued to descend into increasing unhappiness. The situation seemed dark, but as I continued my own research on this topic, a glimmer of optimism emerged, sparked by the very tale with which we opened this discussion.

When I first encountered the story of John McPhee’s long days looking up at the leaves in his backyard, I received it nostalgically—a scene from a time long past, when those who made a living with their minds were actually given the time and space needed to craft impressive things. “Wouldn’t it be nice to have a job like that where you didn’t have to worry about being productive?” I thought. But eventually an insistent realization emerged. McPhee was productive. If you zoom out from what he was doing on that picnic table on those specific summer days in 1966 to instead consider his entire career, you’ll find a writer who has, to date, published twenty-nine books, one of which won a Pulitzer Prize, and two of which were nominated for National Book Awards. He has also penned distinctive articles for The New Yorker for over five decades, and through his famed creative nonfiction course, which he has long taught at Princeton University, he has mentored many young writers who went on to enjoy their own distinctive careers, a list that includes Richard Preston, Eric Schlosser, Jennifer Weiner, and David Remnick. There’s no reasonable definition of productivity that shouldn’t also apply to John McPhee, and yet nothing about his work habits is frantic, busy, or overwhelming.

This initial insight developed into the core idea that this book will explore: perhaps knowledge workers’ problem is not with productivity in a general sense, but instead with a specific faulty definition of this term that has taken hold in recent decades. The relentless overload that’s wearing us down is generated by a belief that “good” work requires increasing busyness—faster responses to email and chats, more meetings, more tasks, more hours. But when we look closer at this premise, we fail to find a firm foundation. I came to believe that alternative approaches to productivity can be just as easily justified, including those in which overfilled task lists and constant activity are downgraded in importance, and something like John McPhee’s languid intentionality is lauded. Indeed, it became clear that the habits and rituals of traditional knowledge workers like McPhee were more than just inspiring, but could, with sufficient care to account for the realities of twenty-first-century jobs, provide a rich source of ideas about how we might transform our modern understanding of professional accomplishment.

These revelations sparked new thinking about how we approach our work, eventually coalescing into a fully formed alternative to the assumptions driving our current exhaustion:

SLOW PRODUCTIVITY

A philosophy for organizing knowledge work efforts in a sustainable and meaningful manner, based on the following three principles:

1. Do fewer things.

2. Work at a natural pace.

3. Obsess over quality.

As you’ll learn in the pages ahead, this philosophy rejects busyness, seeing overload as an obstacle to producing results that matter, not a badge of pride. It also posits that professional efforts should unfold at a more varied and humane pace, with hard periods counterbalanced by relaxation at many different timescales, and that a focus on impressive quality, not performative activity, should underpin everything. In the second part of this book, I’ll detail the philosophy’s core principles, providing both theoretical justification for why they’re right and concrete advice on how to take action on them in your specific professional life, regardless of whether you run your own company or work under the close supervision of a boss.

My goal is not to simply offer tips about how to make your job somewhat less exhausting. Nor is it to merely shake my metaphorical fist on your behalf at the exploitative fiends indifferent to your stressed-out plight (though we’ll certainly do some of that). I want to instead propose an entirely new way for you, your small business, or your large employer to think about what it means to get things done. I want to rescue knowledge work from its increasingly untenable freneticism and rebuild it into something more sustainable and humane, enabling you to create things you’re proud of without requiring you to grind yourself down along the way. Not every office job, of course, will enjoy the ability to immediately embrace this more intentional rhythm, but as I’ll detail, it’s more widely applicable than you might at first guess. I want to prove to you, in other words, that accomplishment without burnout not only is possible, but should be the new standard.

Before we get ahead of ourselves, however, we must first understand how the knowledge sector stumbled into its current malfunctioning relationship with productivity in the first place, as it will be easier to reject the status quo once we truly understand the haphazardness of its formation. It’s toward the pursuit of this goal, then, that we’ll now start our journey.

Part 1

FOUNDATIONS

1

THE RISE AND FALL OF PSEUDO-PRODUCTIVITY

In the summer of 1995, Leslie Moonves, the newly appointed head of entertainment for CBS, was wandering the halls of the network’s vast Television City headquarters. He was not happy with what he saw: it was 3:30 p.m. on a Friday, and the office was three quarters empty. As the media journalist Bill Carter reports in Desperate Networks, his 2006 book about the television industry during this period, a frustrated Moonves sent a heated memo about the empty office to his employees. “Unless anybody hasn’t noticed, we’re in third place [in the ratings],” he wrote. “My guess is that at ABC and NBC they’re still working at 3:30 on Friday. This will no longer be tolerated.”

On first encounter, this vignette provides a stereotypical case study about the various ways the knowledge sector came to think about productivity during the twentieth century: “Work” is a vague thing that employees do in an office. More work creates better results than less. It’s a manager’s job to ensure enough work is getting done, because without this pressure, lazy employees will attempt to get away with the bare minimum. The most successful companies have the hardest workers.

But how did we develop these beliefs? We’ve heard them enough times to convince ourselves that they’re probably true, but a closer look reveals a more complicated story. It doesn’t take much probing to discover that in the knowledge work environment, when it comes to the basic goal of getting things done, we actually know much less than we’re letting on . . .

What Does “Productivity” Mean?

As the full extent of our culture’s growing weariness with “productivity” became increasingly apparent in recent years, I decided to survey my readers about the topic. My goal was to nuance my understanding of what was driving this shift. Ultimately, close to seven hundred people, almost all knowledge workers, participated in my informal study. My first substantive question was meant to be easy; a warm-up of sorts: “In your particular professional field, how would most people define ‘productivity’ or ‘being productive’?” The responses I received to this initial query, however, surprised me. The issue was less what they said than what they didn’t. By far the most common style of answer simply listed the types of things the respondent did in their job.

“Producing content and services for the benefit of our member organizations,” replied an executive named Michael. “The ability to produce [sermons] while simultaneously caring for your flock via personal visits,” said a pastor named Jason. A researcher named Marianna pointed to “attending meetings . . . running lab experiments . . . and producing peer-reviewed articles.” An engineering director named George defined productivity to be “doing what you said you would do.”

None of these answers included specific goals to meet, or performance measures that could differentiate between doing a job well versus badly. When quantity was mentioned, it tended to be in the general sense that more is always better. (Productivity is “working all the time,” explained an exhausted postdoc named Soph.) As I read through more of my surveys, an unsettling revelation began to emerge: for all of our complaining about the term, knowledge workers have no agreed-upon definition of what “productivity” even means.

This vagueness extends beyond the self-reflection of individuals; it’s also reflected in academic treatments of this topic. In 1999, the management theorist Peter Drucker published an influential paper titled “Knowledge-Worker Productivity: The Biggest Challenge.” Early in the article, Drucker admits that “work on the productivity of the knowledge worker has barely begun.” In an attempt to rectify this reality, he goes on to list six “major factors” that influence productivity in the knowledge sector, including clarity about tasks and a commitment to continuous learning and innovation. As in my survey responses, all of this is just him talking around the issue—identifying things that might support productive work in a general sense, not providing specific properties to measure, or processes to improve. A few years ago, I interviewed a distinguished Babson College management professor named Tom Davenport for an article. I was interested in Davenport because, earlier in his career, he was one of the few academics I could find who seriously attempted to study productivity in the knowledge sector, culminating in his 2005 book, Thinking for a Living: How to Get Better Performance and Results from Knowledge Workers. Davenport ultimately became frustrated with the difficulty of making meaningful progress on this topic and moved on to more rewarding areas. “In most cases, people don’t measure the productivity of knowledge workers,” he explained. “And when we do, we do it in really silly ways, like how many papers do academics produce, regardless of quality. We are still in the quite early stages.” Davenport has written or edited twenty-five books. He told me that Thinking for a Living was the worst selling of them all.

It’s hard to overemphasize how unusual it is that an economic sector as large as knowledge work lacks useful standard definitions of productivity. In most every other area of our economy, not only is productivity a well-defined concept, but it’s often central to how work unfolds. Indeed, much of the astonishing economic growth fueling modernity can be attributed to a more systematic treatment of this fundamental idea. Early uses of the term can be traced back to agriculture, where its meaning is straightforward. For a farmer, the productivity of a given parcel of land can be measured by the amount of food the land produces. This ratio of output to input provides a compass of sorts that allows farmers to navigate the possible ways to cultivate their crops: systems that work better will produce measurably more bushels per acre. This use of a clear productivity metric to help improve clearly defined processes might sound obvious, but the introduction of this approach enabled explosive leaps forward in efficiency. In the seventeenth century, for example, it was exactly this type of metric-driven experimentation that led to the Norfolk four-course system of planting, which eliminated the need to leave fields fallow. This in turn made many farmers suddenly much more productive, helping to spur the British agricultural revolution.

As the Industrial Revolution began to emanate outward from Britain in the eighteenth century, early capitalists adapted similar notions of productivity from farm fields to their mills and factories. As with growing crops, the key idea was to measure the amount of output produced for a given amount of input and then experiment with different processes for improving this value. Farmers care about bushels per acre, while factory owners care about automobiles produced per paid hour of labor. Farmers might improve their metric by using a smarter crop rotation system, while factory owners might improve their metric by shifting production to a continuous-motion assembly line. In these examples, different types of things are being produced, but the force driving changes in methods is the same: productivity.

There was, of course, a well-known human cost to this emphasis on measurable improvement. Working on an assembly line is repetitive and boring, and the push for individuals to be more efficient in their every action creates conditions that promote injury and exhaustion. But the ability for productivity to generate astonishing economic growth in these sectors swept aside most such concerns. Assembly lines are dreary for workers, but when Henry Ford switched his factory in Highland Park, Michigan, to this method in 1913, the labor-hours required to produce a Model T dropped from 12.5 to around 1.5—a staggering improvement. By the end of the decade, half of the cars in the United States had been produced by the Ford Motor Company. These rewards were too powerful to resist. The story of economic growth in the modern Western world is in many ways a story about the triumph of productivity thinking.

But then the knowledge sector emerged as a major force in the mid-twentieth century, and this profitable dependence on crisp, quantitative, formal notions of productivity all but vanished. There was, as it turns out, a good reason for this abandonment: the old notions of productivity that worked so well in farming and manufacturing didn’t seem to apply to this new style of cognitive work. One problem is the variability of effort. When the infamous efficiency consultant Frederick Winslow Taylor was hired to improve productivity at Bethlehem Steel in the early twentieth century, he could assume that each worker at the foundry was responsible for a single, clear task, like shoveling slag iron. This made it possible for him to precisely measure their output per unit of time and seek ways to improve this metric. In this particular example, Taylor ended up designing a better shovel for the foundry workers that carefully balanced the desire to move more iron per scoop while also avoiding unproductive overexertion. (In case you’re wondering, he determined the optimal shovel load was twenty-one pounds.)

In knowledge work, by contrast, individuals are often wrangling complicated and constantly shifting workloads. You might be working on a client report at the same time that you’re gathering testimonials for the company website and organizing an office party, all the while updating a conflict of interest statement that human resources just emailed you about. In this setting, there’s no clear single output to track. And even if you do wade through this swamp of activity to identify the work that matters most—recall Davenport’s example of counting a professor’s academic publications—there’s no easy way to control for the impact of unrelated obligations on each individual’s ability to produce. I might have published more academic papers than you last year, but this might have been, in part, due to a time-consuming but important committee that you chaired. In this scenario, am I really a more productive employee?

A Henry Ford–style approach of improving systems instead of individuals also struggled to take hold in the knowledge work context. Manufacturing processes are precisely defined. At every stage of his development of the assembly line, Ford could detail exactly how Model Ts were produced in his factory. In the knowledge sector, by contrast, decisions about organizing and executing work are largely left up to individuals to figure out on their own. Companies might standardize the software that their employees use, but systems for assigning, managing, organizing, collaborating on, and ultimately executing tasks are typically left up to each individual. “The knowledge worker cannot be supervised closely or in detail,” argued Peter Drucker in his influential 1967 book, The Effective Executive. “He can only be helped. But he must direct himself.”

Knowledge work organizations took this recommendation seriously. The carefully engineered systems of factories were replaced with the “personal productivity” of offices, in which individuals deploy their own ad hoc and often ill-defined collection of tools and hacks to make sense of their jobs, with no one really knowing how anyone else is managing their work. In such a haphazard setting, there’s no system to easily improve, no knowledge equivalent of the ten times productivity boost attributed to the assembly line. Drucker himself eventually grew to recognize the difficulties of pursuing productivity amid so much autonomy. “I think he did believe it was hard to improve . . . we let the inmates run the asylum, let them do the work as they wish,” Tom Davenport told me, recalling conversations he had with Drucker in the 1990s.

These realities created a real problem for the emergent knowledge sector. Without concrete productivity metrics to measure and well-defined processes to improve, companies weren’t clear how they should manage their employees. And as freelancers and small entrepreneurs in the sector became more prevalent, these individuals, responsible only for themselves, weren’t sure how they should manage themselves. It was from this uncertainty that a simple alternative emerged: using visible activity as a crude proxy for actual productivity. If you can see me in my office—or, if I’m remote, see my email replies and chat messages arriving regularly—then, at the very least, you know I’m doing something. The more activity you see, the more you can assume that I’m contributing to the organization’s bottom line. Similarly, the busier I am as a freelancer or entrepreneur, the more I can be assured I’m doing all I can to get after it.

As the twentieth century progressed, this visible-activity heuristic became the dominant way we began thinking about productivity in knowledge work. It’s why we gather in office buildings using the same forty-hour workweeks originally developed for limiting the physical fatigue of factory labor, and why we feel guilty about ignoring our inboxes, or experience internalized pressure to volunteer or “perform busyness” when we see the boss is nearby. In the absence of more sophisticated measures of effectiveness, we also gravitate away from deeper efforts toward shallower, more concrete tasks that can be more easily checked off a to-do list. Long work sessions that don’t immediately produce obvious contrails of effort become a source of anxiety—it’s safer to chime in on email threads and “jump on” calls than to put your head down and create a bold new strategy. In her response to my reader survey, a social worker who identified herself only as N described the necessity of “not taking breaks, rushing, and hurrying all day,” while a project manager named Doug explained that doing his job well reduced to “churning out lots of artifacts,” whether they really mattered or not.

This switch from concrete productivity to this looser proxy heuristic is so important for our discussion to follow that we should give it a formal name and definition:

PSEUDO-PRODUCTIVITY

The use of visible activity as the primary means of approximating actual productive effort.

It’s the vagueness of this philosophy that gave my readers so much trouble when I asked them to define “productivity.” It’s not a formal system that can be easily explained; it’s more like a mood—a generic atmosphere of meaningful activity maintained through frenetic motion. Its flaws are also more subtle. For early knowledge workers, there were clear advantages to pseudo-productivity when compared with the concrete systems that organized industrial labor. Many people would rather pretend to be busy in an air-conditioned office than stamp sheet metal all day on a hot factory floor. As we’ll see next, it really wasn’t until the last couple of decades before an approach to work centered on pseudo-productivity derailed. But once it did, the damage was significant.

Why Are We So Exhausted?

The opening vignette about CBS is a classic demonstration of pseudo-productivity. Les Moonves needed better performance, so he turned the obvious knob: demanding his employees work longer hours. Another reason why I chose this specific story, however, was its timing. In the mid-1990s, when Moonves sent out his frustrated memo, the sustainability of pseudo-productivity as a means for organizing knowledge work had begun, seemingly all at once, to quietly but rapidly degrade.

The cause of this deterioration was the arrival during this decade of networked computers in the office. In a setting where activity provides a proxy for productivity, the introduction of tools like email (and, later, Slack) that make it possible to visibly signal your busyness with minimal effort inevitably led to more and more of the average knowledge worker’s day being dedicated to talking about work, as fast and frantically as possible, through incessant electronic messaging. (One particularly damning analysis, conducted by the software company RescueTime, and based on log data from over ten thousand knowledge workers, revealed that the subjects they studied checked their inbox once every six minutes on average.) The subsequent arrival of portable computing and communication, in the form of laptops and smartphones, made this trend even worse, as the demand to demonstrate effort could now extend beyond the workday, following us home at night or to our kid’s soccer field on the weekend. Computers and networks opened many new possibilities, but when combined with pseudo-productivity they ended up supercharging our sense of overload and distraction, pushing us onto a collision course with the burnout crisis that afflicts us today.

It’s important to emphasize the magnitude of these current woes. A recent study conducted by McKinsey and Lean In, for example, which surveyed more than sixty-five thousand North American employees, primarily from knowledge sector jobs, found a significant increase in those describing themselves as feeling burned out “often” or “almost always.” A subsequent Gallup poll showed that American workers are now among some of the most stressed in the world. Jim Harter, Gallup’s chief workplace scientist, noted that these stress measures rose alongside metrics that show an increase in employee efforts. “The intersection of work and life needs some work,” he said.

We don’t need data, however, to teach us what so many have already encountered in their own lives. The responses from my reader survey, for example, were filled with personal accounts of exhausting overload driven by new office technology. A strategic planner named Steve provided a good summary of this experience:

It seems like the benefits of technology have created the ability to stack more into our day and onto our schedules than we have the capacity to handle while maintaining a level of quality which makes the things worth doing. . . . I think that’s where the burnout really hurts—when you want to care about something but you’re removed from the capacity to do the thing or do it properly and give it your passion and full attention and creativity because you’re expected to do so many other things.