Team Genius: The New Science of High-Performing Organizations (5 page)

BOOK: Team Genius: The New Science of High-Performing Organizations
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We are driven not only by biology to form teams of certain predetermined sizes but also by mathematics—or more precisely, combinatorics—to choose the smaller of those sizes whenever possible. And, conversely, combinatorics drives the quality of the relationships in teams to degrade so quickly from close acquaintance to mere recognition.

It also explains why, as we have seen over and over again in recent years, companies and other institutions can spend fortunes on the hottest and coolest new information tools and the latest new management techniques only to end up even
less
competitive. Too often, even the most ambitious and enlightened schemes crash on the rocky shore of human nature—that is, whatever other advantages these schemes enjoy, they have failed to build the
appropriate
teams to employ their strengths.

FROM TEAM ART TO TEAM SCIENCE

If the laws of networking constrain the behavior of human teams, the reality of networks—particularly the Internet—may help us construct them more efficiently than ever before.

One of the most compelling new industries created by the intersection of the Internet, sensor technology, and software analytics is
Big Data
.

Though Big Data has lately suffered the overhyping that comes
with any powerful new technology, the reality is that it represents a revolutionary new approach to our ways of looking at the natural world. In particular, it signals the end of
sampling
. Historically, because measuring all cases of a particular phenomenon was all but impossible, humans developed the science of statistics: that is, taking samples and then using mathematical tools to measure correlation and chance of error, blowing up the results to cover
all
cases.

Big Data turns this upside down. Using everything from high-resolution satellite imagery to tiny semiconductor sensors to the cloud-based collection of millions of daily transactions, we now find it possible for the first time to measure
everything—
every fish passing a point in the ocean, every tree in the Amazon, every purchase made at every Walmart, every step taken by every shopper in a retail mall . . . and soon, every gust of wind on earth, and every blood cell in our bodies.

Even better, all of these mountains of raw data, including metadata, can be crunched, using the latest computer-based analytical tools to discover truths about the natural world (for example, long-term trends in climate, animal species, human behavior, and epidemiology), and nonintuitive connections (for example, the connection between childhood behavior and cancer sixty years into the future) never before even imagined.

One of the most interesting consequences of the Big Data revolution is its ability to conduct massive searches, using multiple characteristics. Not surprisingly, this ability has earned considerable attention in the commercial world.

In particular, a brand-new industry has sprung up to use Big Data to aid in the hiring process. Corporations and government agencies now contract Big Data firms to look for the best candidate for a position by not just doing a global search but also by gathering and processing huge amounts of available information about individuals—from school grades to personality tests to past performance—to determine the very best fit for the job. Begun just
a few years ago, this industry has already grown to a billion-dollar size . . . not surprisingly, as the value of the perfect candidate for a given job is many times that of rolling the dice on a new hire after a couple of interviews.

“Recruiters and hiring managers rely heavily on instincts, hunches and memory to choose the right candidates,” said Mark Newman, the CEO of HireVue, to
Forbes
in 2014. “But there isn’t a lot of data to help them predict who will become a top performer, or decide who should be interviewing candidates.” The
Wall Street Journal
and
Entrepreneur
magazine ran similar stories hailing the bright new dawn of algorithmic hiring.

But as valuable as using Big Data to hire individual employees can be—count us skeptical—its value pales against the value of a well-designed, high-functioning team. That said, until now, teams have by necessity largely been recruited and formed by hunch, intuition, and experience, with little to no empirical support.

That is about to change.

The New Science of Teams

T
hink of all of the dysfunctional or barely functional teams that you have known—or worse, been a part of—over the course of your life. Painful memories, aren’t they?

Let’s go in a more pleasant direction. Think of those one or two teams—a childhood sports team, a best friendship, a Scout patrol, a college study group, a department in your company—that just seemed to gel. The team you felt so much a part of that it was like an extension of yourself. A team that accomplished—and helped
you
accomplish—far more than you ever thought possible. The team that remains the ideal against which you have judged all subsequent teams. The team whose members remained friends long after its tenure ended.

Now imagine if
every
team of which you’ve been a member had been that successful, that productive, and that rewarding. Imagine
you
at your best, surrounded by teammates at their bests, sharing personal experiences that will be remembered fondly decades later.

HARDWIRED TO WORK AND IMPROVE TOGETHER

The most fundamental questions one can ask about teams are, Are human beings designed to work together? And can each person grow and perform at his or her best if properly fit into the right team? Some of the most compelling new research in brain science in the twenty-first century says yes.

In fact, the human brain is evolutionarily designed so that individuals can adjust to one another’s perspectives and emotions in order to engage in cooperative activity.
1
Such adaptation does not occur at a “software” level; rather, as the noted psychologist Daniel Goleman has shown,
humans are actually wired to connect
. That is, when we engage with another person, we are, in fact, embarking on an intimate brain-to-brain connection with that person.

Hints of the depth of that connection pop up in our everyday language—for instance, when we “don’t laugh at someone, but with them” or when we say we are “of one mind” with another person. The deeper that engagement—love, friendship, a partnership of complete trust—the greater that relationship affects our brains and our well-being to the point of actually activating genes controlling our immune systems. Thus, nourishing relationships really are beneficial for our health, while toxic ones can actually be physically destructive.

We tend to think of our brains as pure thought and our bodies as physical entities (except when we suffer a concussion or endure a hangover). But in fact, our brains make up 2 percent of our total body weight—the high relative number being one of those things that distinguish us from most other animals. And that bundle of nerve cells is especially hungry: our brains are responsible for 25 percent of our body’s total glucose use, 20 percent of its oxygen use, and 15 percent of our total cardiac output.
2

This hunger for fuel—which we typically credit to that thin and wrinkled bedsheet-size layer of cerebral cortex that gives us higher
thinking and consciousness—also appears to come from our need to socialize. Thus, the correlation between brain size and group complexity appears to be the strongest for pair-bonding animals.
3

One popular explanation for why this is so is that teamwork made us this way. This is the “social intelligence hypothesis,” which states that advanced cognitive abilities such as those found in humans and other primates are a result of the selection pressures from the varied demands of their social interactions. In other words, we have big brains because environmental forces—hunting on the veldt, near-extinction events, the Ice Ages—in our distant history
forced us to work together
in complicated ways. Our large brain size is the outcome of that teamwork.
4

Simulation experiments conducted by the evolutionary microbiologist Luke McNally of Trinity College Dublin and his team found that when groups were faced with cooperative problems, organisms invariably selected for greater cognitive abilities.
5
In other words, we’re smarter precisely because we had to work together.

This finding is so important that we want to give you a bit more detail on how the experiment was conducted. The simulation, done on computers, began with fifty simple “brains,” each with three to six neurons. Each brain challenged the others to a classic human social interaction scenario: either the prisoner’s dilemma (each individual, without any information, either has to betray the others or trust them) or the snowdrift game (a.k.a. playing chicken to see who swerves first). In other words, the brains could either cooperate or cheat.

The “brains” that did well in these games were then programmed to be more likely to have offspring—that is, “winner begets all.” After each game, the brains reproduced asexually. In these new generations, all the brains had a chance to undergo a random mutation, in a manner similar to real life, that could change the brain’s structure or the number or connectivity of its neurons.

The simulation ran for 50,000 generations (about as many as
we’ve had as something resembling humans). The slow transition to a more cooperative society resulted in the evolution of more complex brains. Thus, teams have literally helped make us who we are.

Such cooperative behavior was induced in this experiment by external forces (the researchers), but where, you may ask, does cooperative behavior come from in nature? Now it gets even more interesting. It turns out that cooperative behavior appears
everywhere
among living things—from genes to multicellular organisms to societies.
6
Some have even speculated that this cooperative behavior may have been necessary for the emergence of
all
complex biological systems, from genomes to the global human community.
7

But even if cooperative behavior is ubiquitous in the animal kingdom, this still doesn’t quite explain why it not only exists among humans, but—consider nation-states with hundreds of millions of citizens—is almost unimaginably complex.

WHY WE COLLABORATE BEYOND KIN

One likely explanation for the depth of cooperation found in human societies is
kin relations
. Humans have lived as foragers for 95 percent of their history—there is evidence of australopithecine kin behavior dating back one million years. The simple answer is that people cooperated in hunter-gatherer groups because they were related to one another.

But it turns out that this isn’t exactly correct: analyses of coresidence patterns in the archaeological record have revealed that kin relations were too few in human hunter-gatherer groups to have been the driving force for the evolution of human cooperation. In other words, there weren’t enough distant cousins in these groups to drive real genetic change. Rather, it took large interacting networks
of
unrelated
adults to evolve capacities for social learning—which in turn created cumulative culture.
8

The implications of this discovery go in two directions. The first is that, perhaps from the start, human beings teamed up with people beyond their kin. And that in turn underscores the notion that those humans didn’t have to
learn
how to bring nonkin members into their team, but that they already, naturally, had that inclination.

In the other direction, just where that inclination came from is not so obvious. For example, in a comparative study of sequential problem-solving groups, researchers assembled teams of capuchin monkeys, chimpanzees, and human children. Each were given an experimental puzzle box that could only be solved in three stages. As an incentive, successful problem solvers were given ever-better rewards the closer they got toward the solution.

So, what happened? Well, each member of the capuchin (the lower level of the intelligence scale) and the chimp (the middle level) teams tried to solve the problem on its own. By comparison, the groups of children worked as teams, teaching each other, exchanging advice, and sharing their rewards. The more they cooperated, the better they did at the task. Indeed, by working together, many of the teams of children actually solved their puzzles.
9

As it turns out, contrary to a more selfish notion of humankind—that is, people are only in it for themselves—
cooperation
may be the default tendency in humans, and self-interest may be something you
will
yourself toward. This position is underscored by the results of so-called resource allocation experiments in which subjects are forced to make decisions quickly. These snap decisions result in more cooperation among subjects than is found when they are given time to deliberate and reflect on their decisions.
10
Give us time, it seems, and we’ll start thinking of only ourselves.

GETTING AHEAD BY GETTING ALONG

Still don’t buy it? Consider the incredible contribution of open-source software—computer code that’s freely developed through public, collaborative efforts of programmers around the world. Some of our most important Internet infrastructure has been enabled through open-source development, like Apache’s HTTP Web server, Red Hat’s Linux operating system, Mozilla’s Firefox web browser, Sun’s Java programming language, and MySQL database systems.

Or consider Wikipedia. Traditional encyclopedia companies such as Collier’s and Encyclopedia Britannica weren’t buried by cheap foreign labor or rising paper costs; they were usurped by the collaborative effort of volunteer writers and editors.

Maybe it’s an Internet thing, right? Don’t be too sure. Work probably doesn’t get any more isolated and independent than commercial fishing. Located in the top lobster-producing region of the United States, the Maine lobster industry brings in almost $300 million a year and comprises 5,400 separate businesses employing 35,000 individuals. Yet it’s one of the best modern examples of collective action. Just a couple of decades ago, the industry was on the verge of collapse. Century-old businesses were being shuttered and boats dry-docked. But now it’s a study in the way people with a common interest can work together to protect a resource through promoting sustainability. Authority over the industry lies with both the fishermen and government agencies; this authority includes the establishment of size restrictions, seasonal boundaries, and trap regulations. Because of this voluntary cooperation, the industry is flourishing and the community is thriving. So even in an industry defined by individual effort, humans naturally seem to work better together.

Still, why this should be so is not yet obvious. One explanation for cooperation being our natural default response—what social
scientists refer to as
prosociality
—is that cooperation actually engages the reward regions of our brains; that is, we go there first because it
feels
good. But for now, that is still just speculation.
11

Supporting this notion that prosociality is deeply engrained in humans is a wide range of both anthropological studies and field anecdotes from around the world and across numerous cultures. Wherever they are, people tend to engage in prosocial behavior—even when it is not obviously to their advantage.

For example, in resource distribution studies in which participants are requested to split resources, people—wherever they are—typically choose to share between 40 and 50 percent of what they have, even when the recipient is anonymous and there is no penalty for not sharing those resources.
12
And we’re not just talking about adults here, or acculturated young people, but even toddlers: children as young as fourteen months old will actively cooperate in joint tasks (of course, they’ll also hit each other over the head with those “shared” toys on occasion).
13

SOCIAL NORMS AND “ULTIMATE GAMES”

As you might imagine, these innate prosocial traits are made manifest in
social norms—
and those norms in turn are a distinguishing feature of human beings.
14
What makes social norms so important is that they can shape behavior without the force of law—that is, they are people’s beliefs about acceptable social behavior in situations in which the law is not present to enforce it.
15
Think of all those times you waited at a stoplight at 3:00 a.m. when there wasn’t a cop, or even another car, in sight; or the items you never took from stores even though no one was watching. Or when you gave the right price to an inquiring cashier who couldn’t find the tag on your item.

As it turns out, you are not alone. In-depth ethnographic studies
of cultures around the world, from hunter-gatherers to the citizens of modern cities, depict groups as sharing a wide range of social norms, running from food sharing to cooperation to honesty.
16
These attitudes are directed not only at members of the group, but also toward those considered outsiders.

Joe Henrich of the University of British Columbia has spent the last decade working with various colleagues to uncover the cognitive sources of human society. In one of his research projects, he and his team studied social behavior in fifteen different small societies, including foragers, nomadic herding groups, and individuals in settled, agricultural societies in Africa, South America, and Indonesia. They found that within-society social norms even affected individuals’ behavior toward strangers.
17

One of his more interesting findings is that the more that individuals from a particular society have to collaborate to survive, the more they will offer to strangers in “ultimatum” games. (These are games in which two players divide a sum of money; the first player chooses the division, and the second can veto that decision—but then all the money is lost). Henrich and his associates found that the Machiguenga people of Peru, who rarely collaborate outside of their own families, still allocated on average 26 percent of their total resources in ultimatum games to strangers. In contrast, the Lamerala of Indonesia, who fish in highly collaborative groups of individuals from different families, on average allocated 58 percent of their total resources to strangers.

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