What Differences Make a Difference?: The Promise and Reality of Diverse Teams in Organizations
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SUMMARY—As the workplace has become increasingly diverse, there has been a tension between the promise and the reality of diversity in team process and performance. The optimistic view holds that diversity will lead to an increase in the variety of perspectives and approaches brought to a problem and to opportunities for knowledge sharing, and hence lead to greater creativity and quality of team performance. However, the preponderance of the evidence favors a more pessimistic view: that diversity creates social divisions, which in turn create negative performance outcomes for the group. Why is the reality of diversity less than the promise? Answering this requires understanding a variety of factors, including how diversity is defined and categorized, and the moderating as well as mediating processes that affect the diversity–process–performance linkage. We start with a definition. The word diversity has been used to refer to so many types of differences among people that the most commonly used definition—“any attribute that another person may use to detect individual differences” (Williams & O'Reilly, 1998, p. 81)—while accurate, is also quite broad. As a result, various categorization schemes based on factors such as race or gender, or based on proportions such as the size of the minority, have been used to further refine the definition of diversity in teams. The choices researchers have made in using these categorization schemes, however, do lead to particular tradeoffs. Factor approaches, for example, allow an examination of multiple types of diversity and the interactions among them but ignore the sizes of factions and subgroups. Proportional approaches allow the consideration of minority-group size, and hence the study of issues such as tokenism, but also tend to focus on only one type of diversity and thereby overestimate its relevance relative to other types. The underlying effects of diversity, whichever way it is defined and categorized, have typically been understood through three primary theoretical perspectives: the similarity–attraction paradigm, self- and social categorization, and information processing. These approaches also have their biases. The predictions of similarity–attraction theory are straightforward: Similarity on attributes such as attitudes, values, and beliefs will facilitate interpersonal attraction and liking. Empirical research has supported that surface-level similarity tends to predict affiliation and attraction. The similarity–attraction paradigm was developed to understand dyadic relationships. Yet, individuals can express preferences for membership in particular groups even when they have had no prior social interaction with members of that group. This is primarily a cognitive process of categorization: Individuals are postulated to have a hierarchical structure of self-categorizations at the personal, group, and superordinate levels. Research has demonstrated that the specific categories on which we tend to focus in categorizing others—such as race, gender, values, or beliefs—are likely to be those that are the most distinctive or salient within the particular social context. The act of social categorization activates differential expectations for in-group and out-group members. This distinction creates the atmosphere for stereotyping, in which out-group members are judged more stereotypically than in-group members are. The self-categorization/social-identity and similarity–attraction approaches both tend to lead to the pessimistic view of diversity in teams. In these paradigms, individuals will be more attracted to similar others and will experience more cohesion and social integration in homogeneous groups. The information-processing approach, by contrast, offers a more optimistic view: that diversity creates an atmosphere for enhancing group performance. The information-processing approach argues that individuals in diverse groups have access to other individuals with different backgrounds, networks, information, and skills. This added information should improve the group outcome even though it might create coordination problems for the group. As we disentangle what researchers have learned from the last 50 years, we can conclude that surface-level social- category differences, such as those of race/ethnicity, gender, or age, tend to be more likely to have negative effects on the ability of groups to function effectively. By contrast, underlying differences, such as differences in functional background, education, or personality, are more often positively related to performance—for example by facilitating creativity or group problem solving—but only when the group process is carefully controlled. The majority of these effects have typically been explained in terms of potential mediators such as social integration, communication, and conflict. However, the actual evidence for the input–process–output linkage is not as strong as one might like. Clarifying the mixed effects of diversity in work groups will only be possible by carefully considering moderators such as context, by broadening our view to include new types of diversity such as emotions and networks, and by focusing more carefully on mediating mechanisms. As we delve into advice for organizational teams to enhance the assets of diversity and manage the liabilities, we focus on the benefits of “exploring” as opposed to “exploiting” types of tasks, of bridging diversity through values and goals, and of enhancing the power of the minority. Finally, we end with suggestions for how organizations can learn to create incentives for change within the firm.
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Factors such as diversity of perspectives, psychological safety, and enabling meaningful participation have been shown to improve team creativity.
“Factors such as the diversity of perspectives brought by different team members [81], psychological safety to contribute nonsense ideas or make mistakes [137], and enabling everyone to meaningful participate [101] are just a few factors that have been shown to play an important role in improving the creativity of teams.”
From The Impact of Generative AI on Creativity in Software Development: A Research Agenda (2025) · cites this paper as [81]
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Enhancing the Effectiveness of Work Groups and Teams
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Leadership in teams: A functional approach to understanding leadership structures and processes
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Nishii, L. H., & Mayer, D. M. (2009) · Journal of Applied Psychology · doi:10.1037/a0017190 · Cited by 689 · see citing works
Paulus, P. B., & Brown, V. R. (2007) · Social and Personality Psychology Compass · doi:10.1111/j.1751-9004.2007.00006.x · Cited by 364 · see citing works
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Stereotype threat in organizations: implications for equity and performance
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Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers
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Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework
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Subjective Distance and Team Collaboration in Distributed Teams
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How virtual team leaders cope with creativity challenges
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Standards and Separatism: The Discursive Construction of Gender in English Soccer Coach Education
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Chatman, J. A., Greer, L. L., Sherman, E., & Doerr, B. (2019) · Organization Science · doi:10.1287/orsc.2018.1268 · Cited by 32 · see citing works
Hansen, Z., Owan, H., & Pan, J. (2006) · doi:10.3386/w12251 · Cited by 29 · see citing works
The Impact of Generative AI on Creativity in Software Development: A Research Agenda
Jackson, V., Vasilescu, B., Russo, D., Ralph, P., Prikladnicki, R., Izadi, M., D’Angelo, S., Inman, S., Andrade, A., & van der Hoek, A. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3708523 · Cited by 23 · see citing works
- Authors
- Mannix, E., & Neale, M. A.
- Affiliations
- Cornell University (US)
- Stanford University (US)
- Venue
- Psychological Science in the Public Interest
- Publisher
- SAGE Publications
- Published
- 2005-10
- Volume
- 6
- Issue
- 2
- Pages
- 31-55
- ISSN
- 1539-6053 (ISSN-L)
- 1529-1006
- OpenAlex
- W2132440291
- Semantic Scholar
- 34e05cfdd1143ba3a1a13e45efc0e92b3c00a96b
- Cited by
- 1,276
- References
- 226
- Citations by year
- 2026: 36 · 2025: 53 · 2024: 74 · 2023: 68 · 2022: 53 · 2021: 90 · 2020: 68 · 2019: 69 · 2018: 57 · 2017: 73 · 2016: 102 · 2015: 81 · 2014: 71 · 2013: 69 · 2012: 69
- FWCI
- 40.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gothic.net (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Gender Studies › Gender Diversity and Inequality
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- team diversity, team performance, similarity attraction, self-categorization, social categorization, information processing, tokenism, team creativity, group conflict, workplace diversity, knowledge sharing, group decision making, group size
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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