In the early years of the twentieth century, an American mechanical engineer named Frank Bunker Gilbreth made his living watching bricklayers. This was, even then, an unusual profession. Gilbreth had begun his career as a bricklayer himself — apprenticed at seventeen, foreman by twenty — and had developed, in the process, an obsession with the small inefficiencies that crept into the work of his colleagues. He noticed that an experienced bricklayer might bend down dozens of times an hour to pick up a brick, even though the brick could have been placed on a scaffold at waist height. He noticed that mortar was being scooped from a tub on the ground when it could have been delivered, pre-portioned, to the mason’s free hand. He noticed, in other words, that a tradesman who appeared to be working continuously was in fact spending most of his time switching between unrelated micro-tasks — bending, reaching, scooping, walking — and that the actual brick-laying was a small fraction of the day.
Gilbreth’s solution, which he refined over years of measurement, was to redesign the bricklayer’s environment so that similar motions could be grouped together. The bricks were stacked in a particular order on an adjustable scaffold. The mortar was pre-mixed and positioned at hand height. The mason was no longer required to alternate between fetching and laying. He fetched in batches and then laid in batches. The result was that Gilbreth’s workers, doing the same job with the same tools, increased their output from approximately a hundred and twenty bricks per hour to something closer to three hundred and fifty. They were not working harder. They were working in a different rhythm. They had stopped switching.
The principle Gilbreth stumbled into is the one we now call task batching, and it has been rediscovered, in more or less the same form, in nearly every productivity literature of the past century. The version that applies to a knowledge worker in 2026 looks superficially different from the version that applied to a bricklayer in 1908. The mechanism is identical. Switching between unrelated tasks costs more than the tasks themselves cost. Grouping similar tasks into uninterrupted blocks recovers the lost time. The recovery is not modest. It is, in many cases, the difference between a workday that produces almost nothing and a workday that produces almost everything you needed it to.
What Bricklayers Knew That We Have Forgotten
The peculiar irony of modern white-collar work is that we have access to all of Gilbreth’s insights and continue, with admirable persistence, to ignore them. The contemporary office worker spends her day in a state of nearly continuous switching — replying to a message, glancing at the calendar, opening a document, returning to the message, switching to a meeting, returning to the document, checking another message, and so on. Each switch is a small act of inefficiency, almost imperceptible on its own. The accumulation, however, is enormous.
Researchers at Microsoft, who have been quietly amassing one of the largest datasets in the history of work, found in their 2023 Work Trend Index that the average knowledge worker switched between communication tools and other applications more than 1,100 times in a typical workday. That number does not include the smaller switches within applications — between tabs, between conversations, between browser windows — which would multiply it considerably. The switches happen so quickly and so reflexively that the worker performing them rarely notices. They feel, instead, that they are working continuously. The continuity is an illusion. The actual experience is one of perpetual interruption, most of it self-administered.
What Gilbreth understood, and what we have somehow forgotten, is that the cost of a switch is not the duration of the switch itself. The cost is the cognitive cost of reorienting your attention to the new task — a cost paid in the minutes after the switch, not the seconds during it. Doing one thing for ten minutes and then another thing for ten minutes does not produce twenty minutes of output. It produces, on average, somewhere closer to twelve. The missing eight minutes are spent re-entering each task after switching out of it. Across a day with hundreds of switches, the missing minutes become hours. Across a year, they become weeks.
The Science of the Mode-Shift
The neurological mechanism behind the cost of switching has been studied extensively, although the results are usually buried in journals that no one outside the relevant subfield reads. The relevant phrase is “task-set reconfiguration,” and it refers to the brain’s process of rearranging its working contents — the active vocabulary, the relevant memories, the appropriate emotional tone, the mental tools required for the work — every time the task changes. The reconfiguration is not instant. It takes time, and during that time, performance on both the old task and the new task is measurably degraded.
In 2001, the cognitive psychologists Joshua Rubinstein, Jeffrey Evans, and David Meyer published a series of experiments at the University of Michigan demonstrating just how expensive task-switching could be. They asked participants to alternate between solving math problems and classifying geometric shapes. The participants performed each task perfectly in isolation. When asked to alternate between the two, their accuracy dropped and their speed fell. The drop was not subtle. It was consistent enough to be measured to the millisecond, and it grew larger as the tasks became more dissimilar.
Subsequent research by Sophie Leroy at the University of Minnesota — whose work on attention residue we have discussed elsewhere — extended the finding into the territory most relevant to office workers: switching between tasks with different cognitive demands left a “residue” of unfinished mental processing that degraded performance on the new task for an average of fifteen to twenty minutes. The brain, in other words, was not designed for the kind of work most knowledge workers actually do. It was designed to engage with one thing at a time, intensely, until the thing was finished, and then move on.
"The illusion of continuous work is sustained by the small mercies of self-interruption — the quick check, the brief reply, the harmless glance — each of which costs more than it appears to."
The Anatomy of a Batch
A batch, in the technical sense Gilbreth gave it, is a deliberate cluster of similar tasks performed in immediate succession, without intervening switches to unrelated work. The crucial word is similar. The tasks must share enough cognitive overhead that the brain’s task configuration can remain stable across them. Replying to twenty emails is a batch. Replying to two emails, then writing a paragraph of a report, then replying to three more emails, then taking a meeting, is not a batch — even though the email count is similar. The first version costs the brain one configuration. The second costs four.
The most common application of batching in white-collar work is communication. Email, Slack messages, voicemails, and similar small-text correspondence all share the same underlying cognitive demands: read, comprehend, decide, respond. Doing these in clusters — say, twice a day, for forty-five minutes each — produces dramatically more output per minute than checking them constantly throughout the day. The output is also of higher quality, because the brain remains in correspondence-mode long enough to develop the slightly elevated focus that the task requires.
The same logic applies to almost every category of recurring office work. Phone calls can be batched into a single window. Administrative tasks (expense reports, scheduling, paperwork) can be batched into one afternoon a week. Reading — articles, reports, internal documents — can be batched into a single morning hour. Even meetings can be batched, when scheduling permits, into back-to-back blocks rather than being scattered across the day in ways that prevent any continuous stretch of focused work from forming.
In The 4-Hour Workweek (2007), Tim Ferriss made the case that batching was the single highest-leverage productivity intervention available to most knowledge workers. The argument was hyperbolic, as Ferriss tends to be, but the underlying claim was almost certainly correct. A worker who batches his communication into two windows per day, instead of checking continuously, recovers somewhere between an hour and three hours of focused time daily — depending on how interruption-prone his original schedule was. The recovered time is not a marginal improvement. It is, often, the entire difference between a day that produced something and a day that produced nothing.
What the Brain Wants Versus What It Will Settle For
There is a small psychological complication that explains why batching, despite its obvious benefits, is so rarely practiced. The brain, left to its own devices, does not want to batch. It wants to switch. Each switch — the new email, the new tab, the new notification — produces a small dopamine release that the brain finds slightly more rewarding than the steady, low-level effort required to keep working on the same task. Switching feels like progress, even when it isn’t. Sustained focus, by contrast, feels like nothing in particular. The reward for sustained focus arrives at the end, in the form of a finished piece of work. The reward for switching arrives every few minutes, in tiny installments, indefinitely.
This is why most people, asked whether they would rather have an hour of uninterrupted writing or an hour of intermittent multitasking, say they prefer the former — and then, when actually given an hour, choose the latter. The preference is sincere. The behavior is sincere too. They are simply produced by different parts of the brain, and the part that controls behavior in the moment is not the part that gives thoughtful answers in the abstract.
The implication is that batching cannot rely on willpower. It has to be designed. The conditions for batching have to be created in advance — notifications silenced, tabs closed, time blocked on the calendar — so that the in-the-moment temptation to switch is muted by the in-the-moment difficulty of doing so. People who batch successfully do not have stronger discipline than people who don’t. They have arranged their environments to make switching slightly harder than continuing. Slightly harder is enough.
The Deeper Lesson Gilbreth Was Teaching
What Frank Gilbreth was really documenting, when he watched his bricklayers, was not just a more efficient way to lay bricks. He was documenting a fundamental insight about how human attention works under repetition. The mind enters a kind of groove when it performs similar tasks in sequence — a state of partial automation in which the cognitive overhead of the task drops, the body’s movements become more efficient, and the work begins to feel almost effortless. The bricklayer in batch-mode is not the same person as the bricklayer in switching-mode. He is faster, more precise, less tired at the end of the day, and producing better work. The difference is not effort. It is rhythm.
The same is true of writing, coding, designing, planning, and almost every other form of cognitively demanding modern work. The first ten minutes of any task are the most expensive in attentional terms; the next thirty are dramatically cheaper. A worker who structures her day around forty-minute blocks of similar work is buying the cheap minutes and selling the expensive ones. A worker who structures her day around ten-minute switches is doing the opposite — paying the entry cost over and over without ever reaching the productive interior of any task.
In Deep Work (2016), Cal Newport made a similar point in the language of contemporary cognitive science: the people who produce exceptional work in a knowledge economy are almost always those who have learned to spend most of their working time in extended, undistracted blocks of focused effort. Newport’s argument was framed as a prescription for elite performance. The underlying mechanism, however, is the one Gilbreth identified more than a century ago. The blocks work because they batch. The batching works because the brain — like the body of a bricklayer — gets more efficient as it stays in mode and less efficient as it switches.
Try this: Pick one category of task you currently do throughout the day in scattered fragments — replying to messages, processing email, making phone calls, handling administrative work. For one week, do that category only twice a day, in fixed forty-five-minute windows. Outside the windows, the category does not exist. Notice how much more of the rest of your day becomes available to other things.
The Paradox of the Visible Worker
There is a final, slightly uncomfortable observation about batching that the productivity literature tends to soft-pedal. In many workplaces, the worker who batches her communication into two daily windows looks, to her colleagues and supervisors, less responsive — less visible — than the worker who replies instantly to every message. She is, in fact, producing more and better work. But the visible work is the rapid responding, and the invisible work is the focused output that the responding makes impossible. Many organisations, without quite admitting it, reward the visible at the expense of the actual.
This is why batching is, at root, a small act of professional courage. It requires accepting that other people may briefly think you are slower than you are, in exchange for actually being faster. It requires trusting that the work will speak louder, eventually, than the response time. Most people will not make this trade. They will continue to check, switch, and respond, because the cost of doing so is invisible to them and the cost of not doing so is highly visible to everyone else. The minority who do make the trade — who quietly batch their communication, protect their focus blocks, and organise their days around the rhythms their brains actually prefer — are the ones who, year after year, seem mysteriously to produce more than everyone else without ever appearing to be in a hurry.
Frank Gilbreth was eventually vindicated. His methods became the foundation of industrial efficiency studies, and his daughter, Lillian, who continued his work after his death in 1924, became one of the first prominent women in the field of engineering psychology. Their joint book, Cheaper by the Dozen, became a household title, though it was the family memoir version of the story rather than the scholarly one that made the name famous. The bricklayers Gilbreth watched are long gone, the scaffolds dismantled, the houses they built standing or fallen by now. But the integer he discovered — the small, stubborn fact that grouping like tasks is almost always faster than alternating them — remains. It applies to bricks. It applies to inboxes. It applies to almost everything you spent today doing in fragments that could have been done in a single, longer, quieter stretch. The decision to batch is the decision to take that fact seriously. Most people do not. Most people are slower than they need to be.