The Science of Dream Teams: How Talent Optimization Can Drive Engagement, Productivity, and Happiness
Language: English
Published by McGraw Hill, 2021
- Hardcover
- Used

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- Title
- The Science of Dream Teams: How Talent Optimization Can Drive Engagement, Productivity, and Happiness
- Author
- Zani, Mike
- Publisher
- McGraw Hill
- Publication year
- 2021
- Condition
- very_good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1260473740
- ISBN 13
- 9781260473742
From the CEO of The Predictive Index, the leader in talent optimization, comes Moneyball for HR and people management
How do you find the perfect person for the job in a stack of hundreds of resumes? Why do some teams succeed while others―made up of equally talented people―stumble? If the quality of your workforce is your company’s most important asset, then why are your managers still basing these critical decisions primarily on interviews and their gut instincts?
In The Science of Dream Teams, Mike Zani details a data-driven approach to talent optimization that makes hiring, motivating, and managing people more efficient and effective than ever. It employs sophisticated assessments, tools, and software that enable leaders to:
- measure the traits and characteristics that predict success in a role or fit on a team
- build finely tuned project teams and well-balanced leadership teams
- boost employee productivity, engagement, retention―and happiness
- unlock the hidden potential of individual workers and your organization as a whole
"Synopsis" may belong to another edition of this title.
About the Author
Stephen Baker was a journalist at BusinessWeek. He is the author of The Numerati and Final Jeopardy: Man vs. Machine and the Quest to Know Everything, and the coauthor of the New York Times bestseller Where Does It Hurt?: An Entrepreneur's Guide to Fixing Health Care and Hop, Skip, Go: How the Mobility Revolution Is Transforming Our Lives.
"About the title" may belong to another edition of this title.
-OnTimeBooks-
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AbeBooks seller since March 9, 2023
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