A World Without Email: Find Focus and Transform the Way You Work Forever (from the NYT bestselling productivity expert)

by Cal Newport

As Stone told me, they experienced five to six times more traffic than he had estimated, meaning that almost immediately after email was introduced at IBM, the volume of internal communication exploded. A closer examination revealed that not only did people send many more messages than they did in the pre-email era; they also began cc’ing these messages to many more people. “Pre-email, simple communication was largely person-to-person,” Stone told me. After email, these same conversations now unfolded over long back-and-forth threads including many different people. “Thus—in a mere week or so—was gained and blown the potential productivity gain of email,” he joked.

We like to believe that we deploy tools rationally to solve specific problems. But cases like IBM’s server meltdown complicate this story line. No group of managers at IBM decided that massively increasing internal communication would improve productivity, and the individuals suddenly trapped in this deluge of messages weren’t happy about it.

the intention of the system was simply to move the communication that already existed in the office to a more efficient medium—to take what people were already doing and make it easier. So who ultimately decided that everyone should instead start interacting five to six times more than normal? To some who study this question closely, the answer is radical: it was the technology itself.

If you talk with a scholar of the history of technology, you’ll likely discover a fascination with a seemingly unlikely topic: the rise of medieval feudalism in the early Carolingian Empire.

In the eighth century CE, Martel kick-started feudalism by confiscating Church lands and redistributing them to his vassals.

granting land to loyal subjects was necessary for Martel to maintain horse-mounted warriors for his army.

Brunner marshaled historic documents to demonstrate persuasively that this maintenance of knights in shining armor was one of the main motivations for Martel’s setting up fiefdoms throughout his kingdom.

Why did Martel feel the sudden need to raise a massive cavalry force?

When the Franks under Martel faced a Muslim army from Spain, near Poitiers in 732, Martel’s forces were largely fighting on foot, while the Muslim soldiers were largely mounted. According to Brunner’s theory, Martel quickly realized his disadvantage. Almost immediately after this conflict—i...

the crisis which generated feudalism, the event which explains its almost explosive development toward the middle of the eigh...

Brunner’s date for the pivotal Battle of Poitiers was wrong; it actually took place a year after Martel began grabbing Church lands. “We are faced, in the reigns of Martel [and his successors], with an extraordinary drama which lacks motivation,

“The new age is heralded in the eighth century by excavations of stirrups.”

The footnote implied that the force that drove Charles Martel to develop feudalism was the arrival in western Europe of a basic technology: the horse stirrup.

the introduction of the stirrup does indeed explain well Martel’s sudden shift toward mounted troops.

In the eighth century, the warrior with a lance and stirrups on a horse was a form of “shock warfare” devastating to opponents.

In a medieval version of the nuclear arms race that would follow more than a millennium later, Charles Martel realized that the advantage provided by the stirrup was so “immense” that he had to do whatever it took to get it before his enemies did—even if that meant upending centuries of tradition and creating a brand-new form of government.

we find a classic example of a technology introduced for a simple reason (to make riding horses easier) leading to vast and complicated consequences never imagined by i...

Over time, this idea that tools can sometimes drive human behavior became known as technological determinism.

One of the better-known determinist books is Neil Postman’s 1985 classic, Amusing Ourselves to Death.

the format through which mass media is delivered can impact the way a culture...

Postman uses this concept to argue, among other points, that the impact of the printing press is deeper than we realize. The standard narrative about this invention is that mass-produced pamphlets and books allowed information to spread faster and farther, speeding up the evolution of knowledge that culminated in the Age of Reason. Postman replies that the influence of the resulting “typographic” culture did more than just speed up information flow; it changed the way our brains processed our world. “Print put forward a definition of intelligence that gave priority to the objective, rational use of the mind,” he writes, “and at the same time encouraged forms of public discourse with serious, logically ordered content.”16 It was this new way of thinking—not just newly available information—that suddenly made intellectual innovations such as Enlightenment philosophy and the scientific method natural next steps. Gutenberg, in other words, thought he was setting information free, but in reality, he was changing fundamentally what information we treated as important.

technological determinism is the introduction of the Like button to Facebook. As revealed by contemporaneous blog posts written by the design team, the original purpose of this feature was to clean up the comments below users’ posts. Facebook engineers noticed that many such comments were simple positive exclamations, like “cool” or “nice.” They figured that if those could instead be captured by clicking Like, the comments that remained would be more substantive. The goal of this tweak, in other words, was a modest improvement, but they soon noticed an unexpected side effect: users began spending more time on the service.

As became clear in retrospect, incoming Likes provide users with an uneven stream of social approval indicators—bits of evidence that other people are thinking about you. The idea that every tap of the Facebook app might give you new information about these indicators hijacked ancient social drives ...

they were now more likely to check in constantly throughout the day to see how much approval thei...

a battle that left in its wake a small number of massively powerful technology platform monopolies and a weary populace exhausted by a life increasingly dominated by handheld glowing screens. All this because of a small number of engineers who desired to make social media comments less cluttered.

A key property of technological determinism is that the innovation in question alters our behavior in ways that were neither intended nor predicted by those first adopting the tool.

New tools open up some new options for behavior while closing off others. When these changes then interact with our inscrutable human brains and the complex social systems in which we operate, the results can be both significant and unpredictable.

a tool introduced for a simple purpose (to make existing communication practices more efficient) had an unexpected result (a shift toward the hyperactive hive mind style of collaboration). The speed of this transformation, which required less than a week to get rolling, underscores how powerful these forces can be once unleashed.

To many, this asynchronous approach to communication seemed strictly more efficient.

in a 1985 paper, three computer scientists—Michael Fischer, Nancy Lynch (my doctoral adviser), and Michael Paterson—proved, through a virtuosic display of mathematical logic, that in an asynchronous system, no distributed algorithm could guarantee that a consensus would always be reached, even if it was sure that at most a single computer might crash.

It made it clear that asynchronous communication complicates attempts to coordinate, and therefore, it’s almost always worth the extra cost required to introduce more synchrony.

In 2013, Leslie Lamport, a major figure in the field of distributed systems, was given the A. M. Turing Award—the highest distinction in computer science—for his work on algorithms that help synchronize distributed systems.22

As we’ve learned, managers in office settings fixated on eliminating the overhead of synchronous communication—the annoyance of phone tag or taking the elevator to a different floor to chat with someone in person. They believed that eliminating this overhead using tools like email would make collaboration more efficient. Computer scientists, meanwhile, came to the opposite conclusion. Investigating asynchronous communication from the perspective of algorithm theory, they discovered that spreading out communication with unpredictable delays introduced tricky new complexities. While the business world came to see synchrony as an obstacle to overcome, computer theorists began to realize that it was fundamental for effective collaboration.

This reality summarizes well what many experienced as office communication shifted to email: they traded the pain of phone tag, scribbled notes, and endless meetings for the pain of a surprisingly large volume of ambiguous electronic messages passed back and forth throughout the day.

A problem that might have been solvable in a few minutes of real-time interaction in a meeting room or on the phone might now generate dozens of messages, and even then might still fail to converge on a satisfactory conclusion.

What she uncovered was a social feedback loop gone awry—a process she named the cycle of responsiveness.

And thus the cycle spins: teammates, superiors and subordinates continue to make more requests, and conscientious employees accept these marginal increases in demands on their time, while their expectations of each other (and themselves) rise accordingly.24

The important lesson from Perlow’s work is the haphazard and unplanned manner in which an entirely new way of communicating emerged.

I notice you’re responding a little quicker to my message, so I begin to do the same. Others follow suit; the pattern of responsiveness emerges, then becomes a new default.

Throughout our species’s deep history, this evidence suggests, when we hunted megafauna we did so either alone or in small groups. This reality likely also holds for the other activities—hunting small game, foraging—that made up the “work” that dominates our evolutionary history. It doesn’t require a large leap of speculative evolutionary psychology to arrive at the reasonable conclusion that Homo sapiens are well adapted to small-group collaboration.

As with the Paleolithic hunters, the most natural way for small groups to coordinate is in a free-form manner. It follows that the mode of collaboration most instinctually embedded in both our genetics and our cultural memory shares the main characteristics of the hyperactive hive mind workflow.

The problem, of course, is that the hyperactive hive mind deployed in an office differs from the hive mind collaboration of a Stone Age elephant hunt in one key property: the office connects many more people.

One of the first studies in this area was the now famous work of a nineteenth-century French agricultural engineer, Maximilien Ringelmann, who demonstrated that when you dedicate more people to the task of pulling a rope, the average force exerted by each individual decreases—leading to diminishing returns as group sizes grow.

Ringelmann’s work proved influential, as it introduced the general idea that increasing the size of a team doesn’t necessarily increase its effectiveness in direct proportion.

There are many proposed reasons for why teams above this range are less effective. The loafing effect first observed by Ringelmann, for example, seems to still play a role in knowledge work tasks. (Summarized simply: the more people working on a project, the easier it is to get away with putting in less effort.) But another key factor is the rising complexity of communication. It’s easy for six elephant hunters to coordinate their attack by just speaking up when they have something relevant to say. But if you increase this size to sixty, the effort would devolve into an incomprehensible scrum of competing voices and misunderstood ideas, which is why military units of this size almost always feature strict chains of command.

The best way to deploy these highly skilled individuals, Drucker concluded, was to give them clear objectives and then leave them alone to accomplish their brainy work however they saw fit.

[Knowledge work] demands that we impose the responsibility for their productivity on the individual knowledge workers themselves. Knowledge workers have to manage themselves. They have to have autonomy.

In our shift from industrial to knowledge work, in other words, we gave up automaton status for a burdensome autonomy.

The scenario, which eventually became known as the tragedy of the commons,36 considers a town that maintains common grazing land for cattle and sheep, as was typical in Great Britain in the nineteenth century. Lloyd pointed out an interesting tension: it’s in the individual interest of each herder to graze his animals as much as possible on the commons, and yet when all herders act in their best interest, they’ll inevitably overgraze the commons, rendering it useless to everyone. Similar scenarios of individual interest leading to collective hardship turn out to be common in many different settings—from unstable ecologies, to resource mining, to the behaviors surrounding shared refrigerators.

Once your organization has fallen into the hive mind, it’s in each individual’s immediate interest to stick with this workflow, even if it leads to a bad long-term outcome for the organization as a whole.