The Science of Dream Teams: How Talent Optimization Can Drive Engagement, Productivity, and Happiness
WALL STREET JOURNAL BESTSELLER
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:
1138649876
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
The Science of Dream Teams: How Talent Optimization Can Drive Engagement, Productivity, and Happiness
WALL STREET JOURNAL BESTSELLER
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:
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
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The Science of Dream Teams: How Talent Optimization Can Drive Engagement, Productivity, and Happiness
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240
30.0
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Product Details
ISBN-13: | 9781260473742 |
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Publisher: | McGraw Hill LLC |
Publication date: | 07/06/2021 |
Pages: | 240 |
Sales rank: | 1,105,329 |
Product dimensions: | 9.10(w) x 6.10(h) x 0.80(d) |
About the Author
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