Predictive Analytics for Human Resources eBook

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Create and run a human resource analytics project with confidence
For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: “Where do I start?” and “What tools are available?” Predictive Analytics for Human Resources is designed to answer these and other vital questions. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. The authors put the focus on the fundamentals of predictability and include a framework of logical questions to help set up an analytic program or project, then follow up by offering a clear explanation of statistical applications.

Predictive Analytics for Human Resources is a how-to guide filled with practical and targeted advice. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, this important resource addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor. In the book, you’ll find:

A comprehensive guide to developing and implementing a human resource analytics project
Illustrative examples that show how to go to market, develop a leadership model, and link it to financial targets through causal modeling
Explanations of the ten steps required in building an analytics function
How to add value through analysis of systems such as staffing, training, and retention
For anyone who wants to launch an analytics project or program for HR, this complete guide provides the information and instruction to get started the right way.

This is a digital product.

Additional ISBNs
9781118915042

Predictive Analytics for Human Resources 1st Edition is written by Jac Fitz-enz and published by John Wiley & Sons P&T. The Digital and eTextbook ISBNs for Predictive Analytics for Human Resources are 9781118940693, 1118940695 and the print ISBNs are 9781118893678, 1118893670. Additional ISBNs for this eTextbook include 9781118915042.