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People Analytics

Data and Text Analytics for Human Resources

Eduardo Valencia

"People Analytics" is the same as analytics and data for human resources. Or if you prefer, big data for human resources. People Analytics is based on applying data science methodologies and techniques to the field of HR.

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About

About

About the Book

We have more information at our disposal about tastes, opinions, and certain behaviors that could be very useful in making decisions about performance, salaries, turnover rate, leaves of absence, etc.

Accordingly, People Analytics processes that information through analysis tools that allow you to look at talent management decisions in a new way. People Analytics is based on data analysis as opposed to traditional methods of relationships or personal experiences.

I have worked in the area of analytics and data for quite a few years. Lately I've been specializing in data for use in Human Resources departments. I have spent a lot of time doing consulting work and training others. Now, I also direct People Analytics Pro (http://www.peopleanalyticspro.com), where we host a 140-hour Master's program that teaches HR professionals to use data and analytics tools to make informed decisions that improve employee management in an organization. In other words, we help prepare HR analysts.

This book was born from this experience. I intend to give a practical tour of the most important points that are taught in the People Analytics Pro Master's program. In fact, this book is conceived of as a practical guide for how to put into place what I previously only talked about.

People Analytics offers a unique opportunity for human capital professionals to position themselves as strategic senior management partners, using analytically proven techniques to hire and retain employees who drive higher value in companies.

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ManagementComputers and Programming

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Author

About the Author

Eduardo Valencia

Eduardo Valencia (call him Eddy) is a New York-based People Analytics expert with 23 years of expertise in the application of HR analytics, business intelligence, data mining, and statistics in multiple industries. Eddy is founder and director of the on-campus executive master People Analytics Pro (140 hrs-Madrid). 

Contents

Table of Contents

Foreword

  1. Jose Gonzalez: People Analytics the easy way

Burn After Reading!

  1. More about People Analytics
  2. In people analytics we use the evidence that the data provides to respond to several questions:
  3. Is This Book for Me?
  4. Structured and Unstructured Data
  5. What Will You Find in This Book?
  6. Table of Instructions
  7. Without further ado, I want you to know more about me and my flaws.
  8. Vampirizing Data Coaching
  9. It's a fun book that you can learn from.
  10. Illustrations by Marisa Echarri
  11. I. An Introduction to People Analytics

01. What Is People Analytics About?

  1. In this Chapter:
  2. 1. About Moneyball
  3. 2. The Most Valuable Asset is Also the Most Expensive.
  4. 3. Tomayto, Tomahto
  5. 4. Big Data for Human Resources
  6. 5. The Path to Transformation
  7. Takeaways:
  8. Recommended Reading

02. People Analytics: Why and How

  1. In this Chapter:
  2. Examples of Questions:
  3. 1. If You Could Only Ask One Question
  4. 2. Result Indicators and Causal Indicators, Happiness and Profit
  5. 3. Methodology
  6. Takeaways:

03. Big Data and People Analytics

  1. In this Chapter:
  2. 1. The Great Confusion
  3. 2. Big Data and Privacy: A Practical Rule to Govern Ethics
  4. Takeaways:
  5. II. Statistics, Errors, and Biases

04. Intuition vs. Data Analysis

  1. In this chapter:
  2. 1. The Power of Intuition
  3. 2. The Synthesis Between Intuition and Data
  4. Takeaways:
  5. Recommended Reading

05. Defense Against the Dark Arts: Don’t Be Fooled by Data

  1. In this Chapter:
  2. 1. Correlation Does Not Imply Causality.
  3. 2. Simpson's Paradox and Causality
  4. 3. So, How is Causation Demonstrated?
  5. 4. Too Small of a Sample: the Law of Small Numbers
  6. 5. A Sensible Guide to Cleaning Data
  7. Takeaways:
  8. III. Strategy and Economics

06. Building a Business Case for Human Resources

  1. In this Chapter:
  2. 1. What is a Business Case?
  3. 2. The Business Case as a Trip
  4. Takeaways:

07. Taking the Right Measurements

  1. In this Chapter:
  2. 1. The Most Frequently Used Metrics in People Analytics
  3. 2. Calculating Turnover Costs Is a Must.
  4. 3. Epilogue. Turnover Cost in The Apartment (Billy Wilder 1960)
  5. Takeaways:

08. Lifetime Value, the Gold Standard

  1. In this Chapter:
  2. 1. The ELTV Should Be a Key Metric in All Organizations. Why?
  3. Takeaways:
  4. Recommended Reading

09. Employee Experience, Engagement, and the Bottom Line

  1. In this Chapter:
  2. 1. What Do I Mean by "Engagement?"
  3. 2. The eNPS, Measuring Company Happiness
  4. Takeaways:

10. Performance and Compensations

  1. In this chapter:
  2. 1. If you Can't Measure It…
  3. 2. Subjective performance measurement
  4. 3. Objective performance measurement
  5. 5. Compensation and performance
  6. Takeaways:
  7. IV. Learning to Work with Real Cases of People Analytics

11. Clear and Simple Algorithms for People Management

  1. In this chapter:
  2. 1. Responsible Decision-Making
  3. 2. The Sorcerer's Apprentice
  4. 3. How Can You Predict the Consequences?
  5. 4. Good and Bad Algorithms
  6. Takeaways:

12. Surveys and the Lingering Doubters

  1. In this chapter:
  2. 1. Theory of Measurement
  3. 2. There are many of us
  4. 3. How to Get More Valid Data
  5. Takeaways:

13. Segmentations: Divide and Conquer

  1. In this chapter:
  2. 1. Marketing Saw It First
  3. 2. Monty Python's Life of Brian: "You Are All Different"
  4. 3. Recency, Frequency, and Monetary Value
  5. Do It Yourself. Segmentation RFM with Excel and R
  6. Takeaways:

14. Predictive Selection

  1. In this chapter:
  2. 1. Eternal Return
  3. 2. Google and Selection
  4. 3. Daniel Kahneman: An Algorithm or at Least a Structured Interview
  5. 5. Let's go back to Google. How many interviews are needed to hire a "Googler?" The rule of 4.
  6. 6. The Best Candidates from a Turnover Perspective). Predictive Turnover Analysis
  7. Takeaways:
  8. Recommended Reading

15. Turnover

  1. Starting Questions
  2. In this chapter:
  3. 1. Data about Retention and Turnover
  4. 2. Let's Clear Up Some Previous Concepts
  5. 3. Analyzing information you don't see: Abraham Wald and the Lancaster bombers
  6. Conclusion to do a pro report on survival
  7. 5. Predictive Model for Talent Flight
  8. Do It Yourself. Turnover prediction. Comparison: logistic regression, multilayer perceptron neural network and radial basis function neural network.
  9. Takeaways:
  10. V. Text Analytics for Human Resources

16. Open-Text Analytics and the Voice of the Employee

  1. In this chapter:
  2. 1. Data Sources
  3. 2. Memento
  4. 3. Why do you need open-ended survey questions?
  5. 4. Text Analytics: Value as a Wedding Cake
  6. 5. How to Incorporate Text Analytics into the Voice of the Employee
  7. Takeaways:
  8. Annex. Basic Bibliography on People Analytics

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Oxfam America is a global organization working to right the wrongs of poverty, hunger, and injustice. We save lives, develop long-term solutions to poverty, and campaign for social change. As one of 17 members of the international Oxfam confederation, we work with people in more than 90 countries to create lasting solutions.
Oxfam America is a global organization working to right the wrongs of poverty, hunger, and injustice. We save lives, develop long-term solutions to poverty, and campaign for social change. As one of 17 members of the international Oxfam confederation, we work with people in more than 90 countries to create lasting solutions. Our vision: A just world without poverty. Our mission: To create lasting solutions to poverty, hunger, and social injustice.

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