"Predictive Analytics for Human Resources is a comprehensive guide to developing and implementing a human resource analytics project. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, it addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor"--
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.
Predictive HR Analytics
Author: Martin Edwards, Kirsten Edwards
Publisher: Kogan Page
Confidently use predictive analytic and statistical techniques to identify key relationships and trends in HR-related data in order to aid strategic organizational decision making.
The New HR Analytics
Author: Jac Fitz-enz
Publisher: AMACOM/American Management Association
In his landmark book The ROI of Human Capital, Jac Fitz-enz presented a system of powerful metrics for quantifying the contributions of individual employees to a company's bottom line. The New HR Analytics is another such quantum leap, reveal ing how to predict the value of future human capital investments. Using Fitz-enz's proprietary analytic model, readers learn how to measure and evaluate past and current returns. By combining those results with focused business intelligence and applying the exclusive analytical tools in the book. Brimming with real world examples and input from thirty top HR practitioners and thought leaders, this groundbreaking book ushers in a new era in human resources and human capital management.
Human Capital Analytics
Author: Gene Pease, Boyce Byerly, Jac Fitz-enz
Publisher: John Wiley & Sons
An insightful look at the implementation of advanced analytics on human capital Human capital analytics, also known as human resources analytics or talent analytics, is the application of sophisticated data mining and business analytics techniques to human resources data. Human Capital Analytics provides an in-depth look at the science of human capital analytics, giving practical examples from case studies of companies applying analytics to their people decisions and providing a framework for using predictive analytics to optimize human capital investments. Written by Gene Pease, Boyce Byerly, and Jac Fitz-enz, widely regarded as the father of human capital Offers practical examples from case studies of companies applying analytics to their people decisions An in-depth discussion of tools needed to do the work, particularly focusing on multivariate analysis The challenge of human resources analytics is to identify what data should be captured and how to use the data to model and predict capabilities so the organization gets an optimal return on investment on its human capital. The goal of human capital analytics is to provide an organization with insights for effectively managing employees so that business goals can be reached quickly and efficiently. Written by human capital analytics specialists Gene Pease, Boyce Byerly, and Jac Fitz-enz, Human Capital Analytics provides essential action steps for implementation of advanced analytics on human capital.
Author: Dipak Kumar Bhattacharyya
Publisher: Sage Publications Pvt. Limited
Human resource management function over the years -- HR decision-making and HR analytics -- Introduction to HR analytics -- HR business process and HR analytics -- Forecasting and measuring HR value propositions with HR analytics -- HR analytics and data -- HR analytics and predictive modelling -- HR analytics for future
Author: Tracey Smith
Publisher: Numerical Insights LLC
How can HR show value? With 20+ years of analytical expertise, the author guides you into the land of HR analytics to answer this question. The reader of this book is a business leader, an HR leader, analyst, student or just plain curious about what analytics in the Human Resource function is all about. It is intended for the business-minded individual interested in learning about the strategic advantages which can be obtained from performing analytics on the wealth of data stored in HR systems. The book begins with a brief history of the evolution of HR information and explains some of the differences between the stages of information progression. It also provides an opinion on who needs to know these differences and who doesn’t. The book moves on to provide advice on how to best select metrics for HR and how to approach an analysis is an organized way. A full chapter is dedicated to practical examples in order to assist the reader in generating ideas of how to provide value to the organization. Examples are provided using simple and more advanced techniques. The intent, however, is to show where value can be found in HR data and not to provide instruction on mathematical techniques. For the HR leader, the book will go on to examine the advantages and disadvantages of trying to build these capabilities in-house and will provide a realistic view of the challenges associated with implementing analytics in Human Resources. For the HR analyst, a section is included to discuss the realistic challenges you will face in collecting and analyzing HR data. Those entering this field or thinking about it, can then go in with their eyes wide open. A brief introduction to Strategic Workforce Planning is provided because it overlaps with HR analytics in one of its major steps. Finally, the book provides advice and opinions on data analysis and visualization tools available to the HR professional. What Will This Book Do for Me? Before the reader embarks on his / her journey through the pages of this book, it is important to know the types of questions that will be answered. Only then can the reader determine the true value of this material for his / her business. The list below is not all inclusive, but will provide the reader with an idea on how the information contained herein can be used. 1. How can I show some HR analytics quick wins to my leadership team? 2. What are the evolutionary stages of analytics and in what stage are most businesses? 3. How can I organize my analysis efforts? 4. What can regression analysis do for me? 5. How can I link HR to the business? 6. How can I get strategic value out of an HR survey? 7. Should I have an in-house analytics group? If so, which skill sets should I look for? 8. What challenges can I realistically expect to face if I head into HR analytics? Under the new pressure for Human Resources to provide higher value to the company, answering these and similar questions for the organization will increase the strategic level of Human Resources.
"This book will be the ultimate guide for integrating analytics into a company's HR business practices. It provides an actionable framework to leverage predictive analytics at every stage of the hiring process and talent management. The author focuses on integrating analytics across the entire cycle of talent workforce management and planning. The book offers people analytics' case studies from a variety of industries and companies from small and medium sized organizations to large multinational companies. Finally the book focuses on integrating analytics across the entire cycle of talent workforce management and planning; while most books focus on one -- integrating them together and covering the entire hiring cycle is still a relatively new idea"--
Developing Human Capital
Author: Gene Pease, Barbara Beresford, Bonnie Beresford, Lew Walker
Publisher: John Wiley & Sons
Don't squander your most valuable resource! Collectively, your workers are your company's most important and most valuable asset. To make the most of this asset, nothing beats quantitative performance and investment measurement. Learning and Development is an 80 billion-dollar industry, and every valuable employee represents a sizable investment on the part of your company. To keep your business moving forward, effective management of human capital is crucial. It generates plenty of data, and deep analysis of this data helps you provide feedback and make adjustments to capitalize on the combined knowledge, skills, and creativity of your workers. Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments provides a guidebook for collecting, organizing, and analyzing the data surrounding human capital so you can make the most of your employees' potential. Use predictive analysis to optimize human capital investments Learn effective study design and alignment Get the tools you need for measurement, surveys, and analysis Decide what to measure and how to measure it Outline your company's current and future analytics technology needs Map data sources, and overcome barriers to data collection Authors Gene Pease, Bonnie Beresford, and Lew Walker provide case studies in which major companies applied human capital analytics to guide people decisions, and expand upon the role of analytics in Learning and Development. Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments is an essential guide to 21st century human resources and management practices, and can keep you from squandering your company's most valuable resource.
Author: Steve VanWieren
Publisher: Technics Publications
Your CEO just came to you, the HR leader, and said she was hearing rumors about the turnover rate going up. She asks you why this might be happening and how it is could be affecting the bottom line. Are there certain leadership issues? Are engagement levels changing? Is there a problem with the company culture? These are all logical questions. You have hunches for answers, but you have no way to prove those hunches. You know your CEO is going to want data to support any argument you make. You are sure that the answers to her questions are buried in the employee data collected in the different HR systems you have. You have been reading about “HR analytics”, and you wonder how you would answer her question differently if you really understood the data about your people. Quantifiably Better provides a path to follow in search of these answers. It will help you if you are just getting started with your HR analytics initiative, or if you are looking for ways to expand your existing HR analytics practice. In the end, you will find that the insights you desperately seek are easier to find than you ever imagined.
Recently, the use of statistical tools, methodologies, and models in human resource management (HRM) has increased because of human resources (HR) analytics and predictive HR decision making. To utilize these technological tools, HR managers and students must increase their knowledge of the resources’ optimum application. Statistical Tools and Analysis in Human Resources Management is a critical scholarly resource that presents in-depth details on the application of statistics in every sphere of HR functions for optimal decision-making and analytical solutions. Featuring coverage on a broad range of topics such as leadership, industrial relations, training and development, and diversity management, this book is geared towards managers, professionals, upper-level students, administrators, and researchers seeking current information on the integration of HRM technologies.
Author: Eric Siegel
Publisher: John Wiley & Sons
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated — and Hillary for America 2016 plans to calculate — the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.
For advanced students and researchers in the field, this handbook focuses on familiarizing the reader with the fundamentals of applied human resource management whilst contextualizing practice within wider theoretical considerations.
PROVE THE VALUE OF YOUR HR PROGRAM WITH HARD DATA While corporate leaders may well know the value of human capital, they don’t always understand the extent to which the HR function contributes to the bottom line. So when times get tough and business budgets get cut, HR departments often take the first hit. In this groundbreaking guide, the cofounders of ROI Institute, Jack Phillips and Patti Phillips, provide the tools and techniques you need to use analytics to show top decision makers the value of HR in your organization. Focusing on three types of analytics--descriptive, predictive, and prescriptive--Making Human Capital Analytics Work shows how you can apply analytics by: Developing relationships between variables Predicting the success of HR programs Determining the cost of intangibles that are otherwise diffi cult to value Showing the business value of particular HR programs Calculating and forecasting the ROI of various HR projects and programs Much more than a guide to using data collection and analysis, Making Human Capital Analytics Work is a template for spearheading large-scale change in your organization by dramatically influencing your department's overall image within the organization. The authors take you step-by-step through the processes of using hard data to drive decisions and demonstrate the tangible value of HR. You know that your department is more than administrative and transactional--that it's an integral player in your company's strategy. Apply the lessons in Making Human Capital Analytics Work and ensure that all other stakeholders know too.