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9781118893678: Predictive Analytics for Human Resources

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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 businessthe 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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

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.

Dalla quarta di copertina

The step-by-step guide for executing an effective analytics project

We are standing amid the greatest accumulation of data ever in existence, and it is growing exponentially while you read this. The imperative is to turn data into information and then into intelligence.From the Preface

Dr. Jac has been the real deal in Human Capital thought leadership for more than 35 years. He proves it once again by laying out a step-by-step roadmap to analytics in his fifth book on the subject, co-authored with John R. Mattox II. If half as many people buy it as have come to hear him speak about the subject at the HR Technology Conference over the years, you wont get to read this.
Bill Kutik, technology editor for Human Resource Executive for 25 years; father of the 17-year-old HR Technology Conference

Jac and John write from decades of experience, describing practical steps for human capital managers to get started with human capital analytics. They provide a wealth of very accessible tools, tips, and examples, distilling the best from their unique insights.
Dr. John W. Boudreau, Professor of Management and Research Director, Center for Effective Organizations and Marshall School of Business, University of Southern California

Predictive Analytics for Human Resources is a must-read for HR professionals seeking to build a robust analytics practice. Jac and John have provided the HR profession an indispensable guide on how to get started and how to move forward with predictive analytics. If you are serious about building capability in human capital analytics, you will follow the guidance found in Predictive Analytics for Human Resources.
Patti Phillips, PhD, President and CEO, ROI Institute

Fitz-enz and Mattox have applied analytics to predictive analytics. Their work isolates the analytics process and reintegrates it into useful tools for solving business problems. This excellent work is both a primary on the principles of analytics and a codebook on how to use them. Jac continues to evolve this field in creative ways.
Dave Ulrich, Rensis Likert Professor of Business, University of Michigan; Partner, the RBL Group

Jac and John have written the essential book on analytics for human resources. Its a practical guide on how to design, develop, and maintain an analytics program. If you want to know where to start and how to do it, this is the book for you.
Stuart Evans, PhD, Distinguished Service Professor, Carnegie Mellon University-Silicon Valley

Dr. Jac Fitz-enz is simply a gift to HR leaders who want to be effective in business today. Any HR practitioner living through the dramatic curve jump from too little to too much quantitative workforce data should read this book. It is a practical and insightful manual that will help the reader navigate the critical requirement of transforming data into knowledge that drives performance.
Joni Thomas Doolin, CEO and Founder, People Report, a TDn2K Company

Dal risvolto di copertina interno

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 businessthe 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 questionsstatistics 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

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

  • EditoreWiley
  • Data di pubblicazione2014
  • ISBN 10 1118893670
  • ISBN 13 9781118893678
  • RilegaturaCopertina rigida
  • LinguaInglese
  • Numero di pagine176
  • Contatto del produttorenon disponibile

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