Predictive Analytics for Human Resources

by Jac Fitz-Enz, John Mattox

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 "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 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.

Genres: Nonfiction, Historical Romance, Business

176 pages, Hardcover

First published June 23, 2014

Reviews

[Rendell · Rating 4 out of 5]

This is a good introduction to predictive analytics through examples. Although the authors did cover a few basic statistical model, don't expect it to be comprehensive as such statistical guide will require a few more volumes of work.

[Pavel · Rating 5 out of 5]

Exceptional piece of art written in a clear way seems to be great for everyone interested in making HR analytics work.

[Abhijeet Lele · Rating 4 out of 5]

Good if you want to know more on theortical underpinning of HR analytics. It lacks practical exercises. Hence, do not read it from academic or textbook perspective.