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Synopsis
A leading business psychologist casts a critical eye over common talent management myths and uses research on the science of talent to reveal how we can improve our ability to understand, predict and manage talent.
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About the Author
Dr Tomas Chamorro-Premuzic, PhD, is an international authority in personality, talent management and organizational psychology. He is Professor of Business Psychology at University College London (UCL), Visiting Professor at Columbia University, and the CEO Hogan Assessment Systems, a global leader in talent and leadership assessment tools.
Chamorro-Premuzic has taught at New York University and the London School of Economics, and published 8 books and over 140 scientific papers, making him one of the most prolific and widely cited social scientists of his generation.
From the Back Cover
Why the science of people is your key weapon in the war for talent
All organisations have problems, and they nearly always concern people: how to manage them; whom to hire, fire or promote; and how to motivate, develop and retain high potential employees.
Psychology, the main science for understanding people, should be a pivotal tool for solving these problems - yet most companies play it by ear, and billions of dollars are wasted on futile interventions to attract and retain the right people for key roles.
Bridging the gap between the psychological science of talent and common real-world talent practices, The Talent Delusion aims to educate HR practitioners and leaders on how to measure, predict and manage talent. It will provide readers with data-driven solution to the common problems around employee selection, development and engagement; how to define and evaluate talent; how to detect and inhibit toxic employee behaviours; and how to identify and harness leadership potential.
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The Talent Delusion : Why Data, Not Intuition, Is the Key to Unlocking Human Potential
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The Talent Delusion : Why Data, Not Intuition, Is the Key to Unlocking Human Potential
Published by
Little, Brown Book Group Limited, 2017
ISBN 10: 0349412480
ISBN 13: 9780349412481
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