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Predictive Analytics for Human Resources

Predictive Analytics for Human Resources Hardback - 2014

by Jac Fitz-enz

  • New
  • Hardcover

Description

Hardback. New. 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.
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Details

  • Title Predictive Analytics for Human Resources
  • Author Jac Fitz-enz
  • Binding Hardback
  • Edition INTERNATIONAL ED
  • Condition New
  • Pages 176
  • Volumes 1
  • Language ENG
  • Publisher Wiley
  • Date 2014-07-28
  • Features Index
  • Bookseller's Inventory # B9781118893678
  • ISBN 9781118893678 / 1118893670
  • Weight 0.75 lbs (0.34 kg)
  • Dimensions 9 x 6.2 x 0.8 in (22.86 x 15.75 x 2.03 cm)
  • Library of Congress subjects Decision making, Personnel management
  • Library of Congress Catalog Number 2014013430
  • Dewey Decimal Code 658.3

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From the jacket flap

Predictive Analytics for Human Resources offers human resource professionals the information and tools they need to harness the power of analytics and determine future outcomes. Written by Jac Fitz-enz (one of the founders of human resources measurement) and John Mattox II, this important resource answers the questions: "Where do I start?" and "What tools are available?" The book explains the fundamentals of every business--the vision, the brand, and the culture, and shows how predictive analytics supports these basic elements. Fitz-enz and Mattox put the focus on the essentials of predictability and include a framework of logical questions to help set up an analytic program or project. The authors include a clear explanation of statistical applications that will help a human resource project run smoothly.

The book discusses the technology needed to implement and sustain a successful program. And since most programs need support, the authors include suggestions for whom and what can offer support along with rationales provided for each example. Next, Fitz-enz and Mattox describe a typical case of building an analytics project. As this example clearly demonstrates, rather than starting off by asking what to measure, analytics begins with logical questions-statistics come later.

When building a project, often overlooked is the need for persuasive skills and effective change management. Predictive Analytics for Human Resources gets down to the nature of data and examines the critical issues of sources, ownership, and quality. The authors explore how to deal with where it is, who owns it, whether it is valid and reliable, and what forms it comes in. The book then digs deeper into analytics with illustrative examples of regression, correlation, and structural equation modeling.

This vital resource is written for anyone who wants to launch an effective analytics project or program for human resources management.

Predictive Analytics for Human Resources is a complete guide filled with the vital information and instructions needed to get started on a critical program or project right way.

  • Illustrative examples that clearly show how to go to market
  • Develop an approach to analytics that will link HR activities to HR outcomes
  • Critical steps required in building an effective analytics function

About the author

JAC FITZ-ENZ, PHD, is founder and Chief Executive Officer of Human Capital Source, Inc. He founded the Saratoga Institute in Santa Clara, California after holding human resource positions at several major technology and financial services companies. He is widely regarded as the father of human capital strategic analysis, having published the first HR metrics in 1978 and the first international HR benchmarks in 1985.

JOHN R. MATTOX II, PHD, is Director of Research at KnowledgeAdvisors. He is a former Associate Director of Performance Management at KPMG, Manager of Learning Effectiveness at PricewaterhouseCoopers, and a Manager at Arthur Andersen.