img Leseprobe Leseprobe

The Diversity Bonus

How Great Teams Pay Off in the Knowledge Economy

Scott Page

ca. 17,99
Amazon iTunes Hugendubel Bü kobo Osiander Google Books Barnes&Noble Legimi
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Princeton University Press img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Arbeits-, Wirtschafts- und Industriesoziologie


How businesses and other organizations can improve their performance by tapping the power of differences in how people think

What if workforce diversity is more than simply the right thing to do? What if it can also improve the bottom line? It can. The Diversity Bonus shows how and why. Scott Page, a leading thinker, writer, and speaker whose ideas and advice are sought after by corporations, nonprofits, universities, and governments, makes a clear and compelling practical case for diversity and inclusion. He presents overwhelming evidence that teams that include different kinds of thinkers outperform homogenous groups on complex tasks, producing what he calls “diversity bonuses.” These bonuses include improved problem solving, increased innovation, and more accurate predictions—all of which lead to better results. Drawing on research in economics, psychology, computer science, and many other fields, The Diversity Bonus also tells the stories of businesses and organizations that have tapped the power of diversity to solve complex problems. The result changes the way we think about diversity at work—and far beyond.



Netflix, Business case, Demography, New York University, State of the World (book series), Robert Wood Johnson Foundation, Analogy, Probability, Income, Harvard University, Majority minority, Advertising, Analytics, Calculation, Organization, Sexual orientation, Entrepreneurship, Empirical evidence, Result, Social issue, Wealth, Quality control, Institution, Meritocracy, Competition, Race (human categorization), Classroom, Inference, Quartile, Organizational culture, Participant, Employment, Effectiveness, Predictive modelling, Categorization, Team composition, Workforce, Scientist, Political science, Trade-off, Americans, Larry Page, Customer, Asset management, Philosopher, Intersectionality, Tool, Fortune 500, Tradecraft, Biology, Cross-functional team, Knowledge base, Theorem, Ensemble learning, Gender diversity, Engineering, Heuristic, Social science, Asian Americans, Explanation, Product design, Grutter v. Bollinger, Mission statement, Intelligence analysis, Technology, Problem solving, Fluid and crystallized intelligence, Human resources, Mathematics, Profession, Decision-making, Percentage, Estimation, Board of directors, Knowledge economy, Microsoft, Affirmative action, Weighting, Computer scientist, University of Michigan, Career, Forecasting, African Americans, Collective intelligence, Marketing, Economist, Prediction, Supply chain, Collaboration, Accuracy and precision, National Science Foundation, Obesity, Hidden Figures, Rule of thumb, Causality, Mathematician, Restaurant, Workplace, Boeing, Finding