Optimizing Team Performance at Google
Effective teams can make the difference between a business’s success and failure. This exercise is important because in order for managers to build effective teams, they must recognize the strengths and weaknesses of potential team members and develop their teams accordingly.
The goal of this exercise is to demonstrate the positive impact of effective team building.
Read the case about the role of Project Aristotle at Google; then, using the 3-step problem-solving approach, answer the questions that follow.
Google is well on its way to ruling the universe. Whether this is its actual goal or not, the company’s short- and long-term success depend on the performance of its work teams. Realizing this, Google applied its immense human, technological, and financial resources to finding out what makes top-performing teams so effective. Despite its legendary achievements, the company knew that teams vary considerably in terms of their performance, member satisfaction, and level of cohesion and conflict. To understand why, it did what it does best—collect and analyze data. It created Project Aristotle and spent millions of dollars to gather mountains of data from 180 teams across the company. The only thing more surprising than what it found was what it didn’t find.
What Did Google Expect to Find?
Google sliced and diced the team data looking for patterns that would distinguish the most successful from the less successful teams. It expected that some combination of team member characteristics would reveal the optimal team profile. Such a profile or pattern never emerged. Google examined seemingly everything, such as team composition (team member personality, experience, age, gender, and education), how frequently teammates ate lunch together and with whom, their social networks within the company, how often they socialized outside the office, whether they shared hobbies, and team managers’ leadership styles.
It also tested the belief that the best teams were made up of the best individual contributors, or that they paired introverts with introverts and friends with friends. To the researchers’ amazement, these assumptions were simply popular wisdom. In sum, “the ‘who’ part of the equation didn’t seem to matter.” Even more puzzling was that “two teams might have nearly identical makeups, with overlapping memberships, but radically different levels of effectiveness,”2 said Abeer Dubey, a manager in Google’s People Analytics division.
What Did the Company Actually Find?
It turned out it wasn’t so much who was in the group but the way the group functioned or operated that made the performance difference. Group norms—expected behaviors for individuals and the larger team—helped explain why two groups with similar membership function very differently. But this finding was only the beginning. Now Google needed to identify the operative norms.
Members of the Project Aristotle team began looking for team member data referring to factors such as unwritten rules, treatment of fellow team members, ways they communicated in meetings, and ways they expressed value and concern for one another. Dozens of potential norms emerged, but unfortunately the norms of one successful team often conflicted with those of another.
To help explain this finding, the Project Aristotle team reviewed existing research on teams and learned that work teams that showed success on one task often succeed at most. Those that performed poorly on one task typically performed poorly on others. This helped confirm their conclusion that norms were the key. However, they still couldn’t identify the particular norms that boosted performance or explain the seemingly conflicting norms of similarly successful teams.
Then came a breakthrough. After intense analysis, two behaviors emerged. First, all high-functioning teams allowed members to speak in roughly the same proportion. Granted, they did this in many different ways, from taking turns to having a moderator orchestrate discussions, but the end result was the same—everybody got a turn. Second, the members of successful teams seemed to be good at sensing other team members’ emotions, through either their tone of voice, their expressions, or other nonverbal cues.
Having identified these two key norms, the Project Aristotle team was able to conclude that many other team inputs and processes were far less important or didn’t matter at all. Put another way, teams could be very different in a host of ways, but so long as everybody got and took a turn when communicating, and members were sensitive to each other, then each had a chance of being a top-performing team. With this knowledge in hand, now came the hard part. How to instill these norms in work teams at Google?
How could Google instill the appropriate communication practices, as well as build empathy into their teams’ dynamics?
Apply the 3-Step Problem-Solving Approach to OB
Step 1: Define the problem.
Step 2: Identify causes of the problem by using material from this chapter, which has been summarized in the Organizing Framework for Chapter 8 and is shown in Figure 8.8. Causes will tend to show up in either the Inputs box or the Processes box.
Step 3: Make your recommendations for solving the problem. Consider whether you want to resolve it, solve it, or dissolve it (see Section 1.5). Which recommendation is desirable and feasible?
1. C. Duhigg, “What Google Learned from its Quest to Build the Perfect Team,” The New York Times, February 25, 2016, http://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html.