In a review of the research on workplace diversity, Beryl Nelson, a former software-engineering manager at Google, referred to several studies showing that teams “whose members are heterogeneous”—diverse—“have a higher potential for innovation than teams whose members are homogeneous.” According to Nelson, “diverse teams are more effective” in two key respects: “They produce better financial results and results in innovation.” She cites, for example, the financial benefits to companies at which women serve in senior positions: Companies in the top quartile— those ranking better than 75 percent of all companies— enjoyed 41 percent greater return on equity and 56 percent greater earnings before taxes. Among companies with at least three women on their boards of directors, return on equity was 16.7 percent, as opposed to an average of 11.5 percent; return on sales was 16.8 percent, as opposed to an average of 11.5 percent. 

Racial diversity also has significant benefits: Studies show that greater racial diversity corresponds to better results in market share, sales revenue, and profits. A study of 366 companies by the consulting firm McKinsey & Co., for example, reveals that for every 10 percent increase in racial diversity among senior executive teams, earnings before taxes increased by 0.8 percent. 

Research also indicates that the presence of women contributes to the “collective intelligence and creativity” of teams—and thus to their potential for innovation. One study divided participants into teams of three to five members and assigned each team tasks involving brainstorming, decision making, and problem solving. Individual intelligence tests were given beforehand and used to ensure intellectual equality among teams, which were given collective intelligence scores after they had performed their assigned tasks. There was only one predictor of collective intelligence: the presence of women on a team. All the high-scoring teams were composed of about 50 percent women, while all groups with less gender mix had lower scores. Why did women make a difference? The researchers concluded that higherscoring teams did a better job of applying the contributions of all members because they displayed better social skills— skills on which, according to additional research, women tend to score more highly.

Note, however, that this study was based on small groups. When we’re talking about organizations, as opposed to teams, we’re talking about much larger groups, and this difference has an important implication for the study of workplace diversity. One research team, for instance, looked at the top firms on the Standard & Poor’s Composite 1500 list in order to see if there was a relationship between the makeup of their top-management teams and their financial results. The researchers concluded that “female representation in top management leads to an increase of $42 million in firm value.” Another team analyzed eight years of employee survey data provided by a company with more than 60 offices worldwide. They found that by shifting from an all-male or all-female staff to a staff split 50–50 by gender, an office could increase revenue by 41 percent. 

Obviously, large-scale studies like these also suggest a correspondence between greater diversity and better financial performance. But as Katherine W. Phillips, formerly of the Columbia University Business School, pointed out, large-scale studies “show only that diversity is correlated with better performance, not that it causes better performance.” Two things may correlate with one another simply because we find some reason to associate them, but it doesn’t mean that one necessarily causes the other. Nelson acknowledged the same drawback in studies of workplace diversity. Many studies, she reminds us, “show a correlation between diverse organizational composition, financial success, and innovation” but demonstrate no “clear causal relationship between diversity and success.”

Before going any further, we need to understand what the issue is. The problem has to do with the kinds of conclusions that can be drawn from what Phillips calls “large data-set studies,” which involve so many variables that it’s difficult to isolate those that indicate cause and effect from those that indicate mere correlation. A firm that enjoys a 41 percent greater return on equity than comparable companies may have given itself a competitive advantage by putting more women in senior positions, but it clearly has additional competitive advantages as well. 

Because there are fewer variables involved in smallerscale studies of teams (as opposed to larger organizations), these studies may reveal a causal relationship that might also be present in larger groups. Phillips thus recommends closer analysis of “diversity in small groups” as a valid means of focusing on possible cause-and-effect relationships between diversity and performance. In fact, she says, “the findings are clear: for groups that value innovation and new ideas, diversity helps.”  

Phillips cites a study in which she teamed with fellow researchers “to examine the impact of racial diversity on small decision-making groups.” The team assembled threeperson groups with two different racial compositions—all white and two white members plus one nonwhite member. Each group had to solve a murder mystery. All groups shared certain common information, but individual members were given important clues that only he or she knew. In order to solve the mystery, each group had to share all of its collective information, including the clues known only to one member. “The groups with racial diversity,” reports Phillips, “significantly outperformed the groups with no racial diversity.” Why? The researchers concluded that members teamed with “similar others” tended to assume that everyone shared the same information and the same perspective. As a result, all-white groups were less diligent in processing all of their available information—a sure hindrance to creativity and innovation.

Phillips also cites a study designed “to examine the influence of racial and opinion composition in small-group discussions.” Groups were given 15 minutes to discuss some relevant social issue (e.g., the death penalty). The researchers created a dissenting opinion on each issue and had one group member present it as part of the discussion. Phillips reports that 

when a black person presented a dissenting perspective to a group of whites, the perspective was perceived as more novel and led to broader thinking and consideration of alternatives than when a white person introduced that same dissenting perspective. The lesson: when we hear dissent from someone who is different from us, it provokes more thought than when it comes from someone who looks like us.

Roy Y. J. Chua, an organizational behavior specialist at Harvard, has studied a specific kind of workplace team— multicultural teams. He has found that, for certain types of tasks, culturally diverse teams exhibit greater creativity, mainly because cultural diversity supplies “unique access to a range of knowledge systems.” Chua has also discovered, however, that  “it’s inevitable to have conflict when you bring people from different cultural backgrounds together.” Neither teams nor organizations are more creative when the organization suffers from what Chua calls “ambient cultural disharmony”—the effect on individuals and groups of cultural conflict in an organizational environment. If people perceive diversity as a source of conflict, says Chua, they tend to “shut down the search for connections involving ideas from different cultures” and thus miss opportunities for creativity and innovation afforded by diversity of ideas and information. 

Case Questions 

1. According to Katherine W. Phillips, Research has shown that social diversity in a group can cause discomfort, rougher interactions, a lack of trust, greater perceived interpersonal conflict, lower communication, less cohesion, more concern about disrespect, and other problems. So what is the upside?

Provide a cogent answer to Phillips’s closing question—that is, one that reflects what you’ve learned about diversity, group dynamics, workplace teams, and creativity /innovation 

2. Discuss the pros and cons of socially diverse teams in terms of behavioral norms. What, for example, is likely to be the extent of norm variation in a diverse team? What sorts of variations are likely to affect team performance? How might group leaders deal with such variations? How might they manage variations to the team’s benefit? To what extent should group leaders encourage norm conformity? What steps can leaders take to encourage conformity? 

3. Among “Challenges Faced by Diverse Teams,” Beryl Nelson include unconscious bias and stereotype threat. We define stereotyping in Chapter 14 as “the process of categorizing people on the basis of a single attribute.” Nelson explains that stereotypes 

are learned through cultural messages and stories, comments from family and friends, portrayals in the media, and so forth. Despite our best intentions, they can bias our impressions of, and affect our actions toward, others in our environment. . . . They shape our expectations of what people should be doing, especially at work. . . . The stereotypes especially relevant in work situations include not only those characteristics that are visible, such as sex, race, weight, and age, but also those not visible but relatively easy to discern, such as educational background and nationality  

Nelson also points out that “almost everyone has measurable biases.” An ongoing test conducted by Harvard’s Project Implicit has found, for example, that 70–80 percent of all participants have a bias against women in technology. Findings such as those by Project Implicit indicate the stereotype threat to teams composed of diverse members 

First, explain various ways in which stereotype threat can keep a diverse team from being as effective as it could be. 

Second, suggest a few strategies that group and organizational leaders can take to reduce stereotype threat. 

Finally, think about your own biases: What biases do you harbor about women (e.g., they don’t have an aptitude for math)? About men (e.g., they aren’t altruistic or eager to help others)? What biases do you harbor about Asians, African Americans, Hispanics, and older people? Bear in mind, by the way, that even people who are subject to a given bias can actually share it.

4. Beware of lurking variables. In the following two examples, cause-and-effect conclusions have been drawn from evidence of correlation. In each case, the conclusion is false because there is a so-called “lurking variable”—an unstated third variable that affects both causes of the correlation. Identify a probable Lurking variable in each example and explain why each conclusion is false.

a. When ice cream sales increase, drowning deaths also increase. Therefore, ice cream consumption causes drowning. 

b. A great many people who sleep with their shoes on often wake up with headaches. Therefore, sleeping with one’s shoes on causes headaches.

In the next two examples, matters are complicated because the correlation may work both ways. First, provide both yes and no answers to the question posed by each statement. Next, identify a probable lurking variable in each case and explain why both yes and no answers are likely to be false. 

c. Surveys show that workers who say that they’re happy with their jobs tend to be quite productive. Does being happy cause workers to be more productive? 

d. Surveys show that couples who live together before marriage have a higher rate of divorce than couples who don’t live together before marriage. Does living together cause divorce?