People Analytics For Dummies

Book description

Maximize performance with better data

Developing a successful workforce requires more than a gut check. Data can help guide your decisions on everything from where to seat a team to optimizing production processes to engaging with your employees in ways that ring true to them.

People analytics is the study of your number one business asset—your people—and this book shows you how to collect data, analyze that data, and then apply your findings to create a happier and more engaged workforce.

  • Start a people analytics project
  • Work with qualitative data
  • Collect data via communications 
  • Find the right tools and approach for analyzing data

If your organization is ready to better understand why high performers leave, why one department has more personnel issues than another, and why employees violate, People Analytics For Dummies makes it easier. 

Table of contents

  1. Cover
  2. Introduction
    1. About This Book
    2. Foolish Assumptions
    3. Icons Used in This Book
    4. How This Book is Organized
    5. Beyond the Book
    6. Where to Go from Here
  3. Part 1: Getting Started with People Analytics
    1. Chapter 1: Introducing People Analytics
      1. Defining People Analytics
      2. Blazing a New Trail for Executive Influence and Business Impact
      3. Competing in the New Management Frontier
    2. Chapter 2: Making the Business Case for People Analytics
      1. Getting Executives to Buy into People Analytics
      2. People Analytics as a Decision Support Tool
      3. Formalizing the Business Case
      4. Presenting the Business Case
    3. Chapter 3: Contrasting People Analytics Approaches
      1. Figuring Out What You Are After: Efficiency or Insight
      2. Deciding on a Method of Planning
      3. Choosing a Mode of Operation
  4. Part 2: Elevating Your Perspective
    1. Chapter 4: Segmenting for Perspective
      1. Segmenting Based on Basic Employee Facts
      2. Visualizing Headcount by Segment
      3. Analyzing Metrics by Segment
      4. Understanding Segmentation Hierarchies
      5. Creating Calculated Segments
      6. Cross-Tabbing for Insight
      7. Good Advice for Segmenting
    2. Chapter 5: Finding Useful Insight in Differences
      1. Defining Strategy
      2. Measuring If Your Company is Concentrating Its Resources
      3. Finding Differences Worth Creating
    3. Chapter 6: Estimating Lifetime Value
      1. Introducing Employee Lifetime Value
      2. Understanding Why ELV Is Important
      3. Applying ELV
      4. Calculating Lifetime Value
      5. Making Better Time-and-Resource Decisions with ELV
      6. Drawing Some Bottom Lines
    4. Chapter 7: Activating Value
      1. Introducing Activated Value
      2. The Origin and Purpose of Activated Value
      3. Measuring Activation
      4. Combining Lifetime Value and Activation with Net Activated Value (NAV)
      5. Using Activation for Business Impact
      6. Taking Stock
  5. Part 3: Quantifying the Employee Journey
    1. Chapter 8: Mapping the Employee Journey
      1. Standing on the Shoulders of Customer Journey Maps
      2. Why an Employee Journey Map?
      3. Creating Your Own Employee Journey Map
      4. Using Surveys to Get a Handle on the Employee Journey
      5. Making the Employee Journey Map More Useful
      6. Using the Feedback You Get to Increase Employee Lifetime Value
    2. Chapter 9: Attraction: Quantifying the Talent Acquisition Phase
      1. Introducing Talent Acquisition
      2. Getting Things Moving with Process Metrics
    3. Chapter 10: Activation: Identifying the ABCs of a Productive Worker
      1. Analyzing Antecedents, Behaviors, and Consequences
      2. Introducing Models
      3. Evaluating the Benefits and Limitations of Models
      4. Using Models Effectively
      5. Getting Started with General People Models
    4. Chapter 11: Attrition: Analyzing Employee Commitment and Attrition
      1. Getting Beyond the Common Misconceptions about Attrition
      2. Measuring Employee Attrition
      3. Segmenting for Insight
      4. Measuring Retention Rate
      5. Measuring Commitment
      6. Understanding Why People Leave
  6. Part 4: Improving Your Game Plan with Science and Statistics
    1. Chapter 12: Measuring Your Fuzzy Ideas with Surveys
      1. Discovering the Wisdom of Crowds through Surveys
      2. O, the Things We Can Measure Together
      3. Getting Started with Survey Research
      4. Designing Surveys
      5. Managing the Survey Process
      6. Comparing Survey Data
    2. Chapter 13: Prioritizing Where to Focus
      1. Dealing with the Data Firehose
      2. Introducing a Two-Pronged Approach to Survey Design and Analysis
      3. Evaluating Survey Data with Key Driver Analysis (KDA)
      4. Having a Look at KDA Output
      5. Outlining Key Driver Analysis
      6. Learning the Ins and Outs of Correlation
      7. Improving Your Key Driver Analysis Chops
    3. Chapter 14: Modeling HR Data with Multiple Regression Analysis
      1. Taking Baby Steps with Linear Regression
      2. Mastering Multiple Regression Analysis: The Bird's-Eye View
      3. Doing a Multiple Regression in Excel
      4. Interpreting the Summary Output of a Multiple Regression
      5. Moving from Excel to a Statistics Application
      6. Doing a Binary Logistic Regression in SPSS
    4. Chapter 15: Making Better Predictions
      1. Predicting in the Real World
      2. Introducing the Key Concepts
      3. Putting the Key Concepts to Use
      4. Understanding Your Data Just in Time
      5. Improving Your Predictions with Multiple Regression
    5. Chapter 16: Learning with Experiments
      1. Introducing Experimental Design
      2. Designing Experiments
      3. Selecting Random Samples for Experiments
      4. Analyzing Data from Experiments
  7. Part 5: The Part of Tens
    1. Chapter 17: Ten Myths of People Analytics
      1. Myth 1: Slowing Down for People Analytics Will Slow You Down
      2. Myth 2: Systems Are the First Step
      3. Myth 3: More Data Is Better
      4. Myth 4: Data Must Be Perfect
      5. Myth 5: People Analytics Responsibility Can be Performed by the IT or HRIT Team
      6. Myth 6: Artificial Intelligence Can Do People Analytics Automatically
      7. Myth 7: People Analytics Is Just for the Nerds
      8. Myth 8: There are Permanent HR Insights and HR Solutions
      9. Myth 9: The More Complex the Analysis, the Better the Analyst
      10. Myth 10: Financial Measures are the Holy Grail
    2. Chapter 18: Ten People Analytics Pitfalls
      1. Pitfall 1: Changing People is Hard
      2. Pitfall 2: Missing the People Strategy Part of the People Analytics Intersection
      3. Pitfall 3: Missing the Statistics Part of the People Analytics intersection
      4. Pitfall 4: Missing the Science Part of the People Analytics Intersection
      5. Pitfall 5: Missing the System Part of the People Analytics Intersection
      6. Pitfall 6: Not Involving Other People in the Right Ways
      7. Pitfall 7: Underfunding People Analytics
      8. Pitfall 8: Garbage In, Garbage Out
      9. Pitfall 9: Skimping on New Data Development
      10. Pitfall 10: Not Getting Started at All
  8. Index
  9. About the Author
  10. Advertisement Page
  11. Connect with Dummies
  12. End User License Agreement

Product information

  • Title: People Analytics For Dummies
  • Author(s): Mike West
  • Release date: March 2019
  • Publisher(s): For Dummies
  • ISBN: 9781119434764