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Creepy Analytics : Avoid Crossing the Line and Establish Ethical HR Analytics for Smarter Workforce Decisions / Salvatore V. Falletta.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Falletta, Salvatore V., 1962- author.
Language:
English
Subjects (All):
Personnel management--Data processing.
Personnel management.
Personnel management--Statistical methods.
Personnel management--Decision making.
Physical Description:
1 online resource (323 pages)
Edition:
First edition.
Place of Publication:
New York : McGraw Hill, [2024]
Summary:
Discover how to develop and implement an HR analytics system that benefits employees, as well as your organization The potential of HR analytics is a major discussion among scholars, practitioners, thought leaders, and technology vendors, with companies like Amazon, Apple, Google, and Meta digging deeply into HR research and analytics practices that extend beyond simple metrics, scorecards, and reporting. Additionally, ethical questions have begun to arise about the potential abuses of HR analytics with respect to technological advancements and the "datafication" of personal--and often trivial--characteristics, preferences, and behaviors that have little relevance to job performance. As a former chief human resources officer, head of Global HR Research and Analytics at a Fortune 100, and thought leader on this subject, Salvatore Falletta has witnessed first-hand the emergence of "creepy analytics" as a hot-button issue. In this one-of-a-kind guide, Falletta delivers a proven step-by-step process for establishing HR analytics capabilities that serve employees and organizations alike. You'll learn how to rethink and redefine HR analytics, determine stakeholder requirements, gather and transform data, communicate intelligence results, and establish an ethical ecosystem to ensure HR analytics remains a force for good.
Notes:
Description based on print version record.
Place of publication from publisher's website.
ISBN:
9781265133610
1265133611
OCLC:
1420253951

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