Working in Groups- Duhigg
Please study NY Times article (below) for important/interesting things to discuss in response to the prompt questions below. Paraphrase or use direct quotations from the article for following questions:
Prompt questions:
How does the author define norms?
How does the author define collective IQ?
How the does the author define psychological safety/security?
What traits does the article suggest strong teams practice?
How do you define leadership?
https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html?_r=0Links to an external site.
What Google Learned From Its Quest to Build the Perfect Team
New research reveals surprising truths about why some work groups thrive and others falter.
By CHARLES DUHIGG Links to an external site.FEB. 25, 2016 Excerpts from the original article below:
Project Aristotle’s researchers began by reviewing a half-century of academic studies looking at how teams worked. Were the best teams made up of people with similar interests? Or did it matter more whether everyone was motivated by the same kinds of rewards? Based on those studies, the researchers scrutinized the composition of groups inside Google: How often did teammates socialize outside the office? Did they have the same hobbies? Were their educational backgrounds similar? Was it better for all teammates to be outgoing or for all of them to be shy? They drew diagrams showing which teams had overlapping memberships and which groups had exceeded their departments’ goals. They studied how long teams stuck together and if gender balance seemed to have an impact on a team’s success.
No matter how researchers arranged the data, though, it was almost impossible to find patterns ? or any evidence that the composition of a team made any difference. ”We looked at 180 teams from all over the company,” Dubey said. ”We had lots of data, but there was nothing showing that a mix of specific personality types or skills or backgrounds made any difference. The ‘who’ part of the equation didn’t seem to matter.”
As they struggled to figure out what made a team successful, Rozovsky and her colleagues kept coming across research by psychologists and sociologists that focused on what are known as ”group norms.” Norms are the traditions, behavioral standards and unwritten rules that govern how we function when we gather: One team may come to a consensus that avoiding disagreement is more valuable than debate; another team might develop a culture that encourages vigorous arguments and spurns groupthink. Norms can be unspoken or openly acknowledged, but their influence is often profound. Team members may behave in certain ways as individuals ? they may chafe against authority or prefer working independently ? but when they gather, the group’s norms typically override individual proclivities and encourage deference to the team.
Project Aristotle’s researchers began searching through the data they had collected, looking for norms. They looked for instances when team members described a particular behavior as an ”unwritten rule” or when they explained certain things as part of the ”team’s culture.” Some groups said that teammates interrupted one another constantly and that team leaders reinforced that behavior by interrupting others themselves. On other teams, leaders enforced conversational order, and when someone cut off a teammate, group members would politely ask everyone to wait his or her turn. Some teams celebrated birthdays and began each meeting with informal chitchat about weekend plans. Other groups got right to business and discouraged gossip. There were teams that contained outsize personalities who hewed to their group’s sedate norms, and others in which introverts came out of their shells as soon as meetings began.
After looking at over a hundred groups for more than a year, Project Aristotle researchers concluded that understanding and influencing group norms were the keys to improving Google’s teams. But Rozovsky, now a lead researcher, needed to figure out which norms mattered most. Google’s research had identified dozens of behaviors that seemed important, except that sometimes the norms of one effective team contrasted sharply with those of another equally successful group. Was it better to let everyone speak as much as they wanted, or should strong leaders end meandering debates? Was it more effective for people to openly disagree with one another, or should conflicts be played down? The data didn’t offer clear verdicts. In fact, the data sometimes pointed in opposite directions. The only thing worse than not finding a pattern is finding too many of them. Which norms, Rozovsky and her colleagues wondered, were the ones that successful teams shared?
Imagine you have been invited to join one of two groups.
Team A is composed of people who are all exceptionally smart and successful. When you watch a video of this group working, you see professionals who wait until a topic arises in which they are expert, and then they speak at length, explaining what the group ought to do. When someone makes a side comment, the speaker stops, reminds everyone of the agenda and pushes the meeting back on track. This team is efficient. There is no idle chitchat or long debates. The meeting ends as scheduled and disbands so everyone can get back to their desks.
Team B is different. It’s evenly divided between successful executives and middle managers with few professional accomplishments. Teammates jump in and out of discussions. People interject and complete one another’s thoughts. When a team member abruptly changes the topic, the rest of the group follows him off the agenda. At the end of the meeting, the meeting doesn’t actually end: Everyone sits around to gossip and talk about their lives.
Which group would you rather join?
In 2008, a group of psychologists from Carnegie Mellon, M.I.T. and Union College began to try to answer a question very much like this one. ”Over the past century, psychologists made considerable progress in defining and systematically measuring intelligence in individuals,” the researchers wrote in the journal Science in 2010 Links to an external site.. ”We have used the statistical approach they developed for individual intelligence to systematically measure the intelligence of groups.” Put differently, the researchers wanted to know if there is a collective I.?Q. that emerges within a team that is distinct from the smarts of any single member.
What interested the researchers most, however, was that teams that did well on one assignment usually did well on all the others. Conversely, teams that failed at one thing seemed to fail at everything. The researchers eventually concluded that what distinguished the ”good” teams from the dysfunctional groups was how teammates treated one another. The right norms, in other words, could raise a group’s collective intelligence, whereas the wrong norms could hobble a team, even if, individually, all the members were exceptionally bright.
But what was confusing was that not all the good teams appeared to behave in the same ways. ”Some teams had a bunch of smart people who figured out how to break up work evenly,” said Anita Woolley, the study’s lead author. ”Other groups had pretty average members, but they came up with ways to take advantage of everyone’s relative strengths. Some groups had one strong leader. Others were more fluid, and everyone took a leadership role.”
As the researchers studied the groups, however, they noticed two behaviors that all the good teams generally shared. First, on the good teams, members spoke in roughly the same proportion, a phenomenon the researchers referred to as ”equality in distribution of conversational turn-taking.” On some teams, everyone spoke during each task; on others, leadership shifted among teammates from assignment to assignment. But in each case, by the end of the day, everyone had spoken roughly the same amount. ”As long as everyone got a chance to talk, the team did well,” Woolley said. ”But if only one person or a small group spoke all the time, the collective intelligence declined.”
Second, the good teams all had high ”average social sensitivity” ? a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions and other nonverbal cues. One of the easiest ways to gauge social sensitivity is to show someone photos of people’s eyes and ask him or her to describe what the people are thinking or feeling ? an exam known as the Reading the Mind in the Eyes test. People on the more successful teams in Woolley’s experiment scored above average on the Reading the Mind in the Eyes test. They seemed to know when someone was feeling upset or left out. People on the ineffective teams, in contrast, scored below average. They seemed, as a group, to have less sensitivity toward their colleagues.
In other words, if you are given a choice between the serious-minded Team A or the free-flowing Team B, you should probably opt for Team B. Team A may be filled with smart people, all optimized for peak individual efficiency. But the group’s norms discourage equal speaking; there are few exchanges of the kind of personal information that lets teammates pick up on what people are feeling or leaving unsaid. There’s a good chance the members of Team A will continue to act like individuals once they come together, and there’s little to suggest that, as a group, they will become more collectively intelligent.
In contrast, on Team B, people may speak over one another, go on tangents and socialize instead of remaining focused on the agenda. The team may seem inefficient to a casual observer. But all the team members speak as much as they need to. They are sensitive to one another’s moods and share personal stories and emotions. While Team B might not contain as many individual stars, the sum will be greater than its parts.
Within psychology, researchers sometimes colloquially refer to traits like ”conversational turn-taking” and ”average social sensitivity” as aspects of what’s known as psychological safety ? a group culture that the Harvard Business School professor Amy Edmondson defines as a ”shared belief held by members of a team that the team is safe for interpersonal risk-taking.” Psychological safety is ”a sense of confidence that the team will not embarrass, reject or punish someone for speaking up,” Edmondson wrote in a study published in 1999 Links to an external site.. ”It describes a team climate characterized by interpersonal trust and mutual respect in which people are comfortable being themselves.”
When Rozovsky and her Google colleagues encountered the concept of psychological safety in academic papers, it was as if everything suddenly fell into place. One engineer, for instance, had told researchers that his team leader was ”direct and straightforward, which creates a safe space for you to take risks.” That team, researchers estimated, was among Google’s accomplished groups. By contrast, another engineer had told the researchers that his ”team leader has poor emotional control.” He added: ”He panics over small issues and keeps trying to grab control. I would hate to be driving with him being in the passenger seat, because he would keep trying to grab the steering wheel and crash the car.” That team, researchers presumed, did not perform well.
Most of all, employees had talked about how various teams felt. ”And that made a lot of sense to me, maybe because of my experiences at Yale,” Rozovsky said. ”I’d been on some teams that left me feeling totally exhausted and others where I got so much energy from the group.” Rozovsky’s study group at Yale was draining because the norms ? the fights over leadership, the tendency to critique ? put her on guard. Whereas the norms of her case-competition team ? enthusiasm for one another’s ideas, joking around and having fun ? allowed everyone to feel relaxed and energized.
For Project Aristotle, research on psychological safety pointed to particular norms that are vital to success. There were other behaviors that seemed important as well ? like making sure teams had clear goals and creating a culture of dependability. But Google’s data indicated that psychological safety, more than anything else, was critical to making a team work.
”We had to get people to establish psychologically safe environments,” Rozovsky told me. But it wasn’t clear how to do that. ”People here are really busy,” she said. ”We needed clear guidelines.”
However, establishing psychological safety is, by its very nature, somewhat messy and difficult to implement. You can tell people to take turns during a conversation and to listen to one another more. You can instruct employees to be sensitive to how their colleagues feel and to notice when someone seems upset. But the kinds of people who work at Google are often the ones who became software engineers because they wanted to avoid talking about feelings in the first place.
Rozovsky and her colleagues had figured out which norms were most critical. Now they had to find a way to make communication and empathy ? the building blocks of forging real connections ? into an algorithm they could easily scale.
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