| |
| |
Preface | |
| |
| |
Acknowledgments | |
| |
| |
Introduction Realizing the Dream: From Nuisance to Necessity | |
| |
| |
| |
Human Capital Analytics | |
| |
| |
Human Capital Analytics Continuum | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
Alignment | |
| |
| |
The Stakeholder Workshop: Creating the Right Climate for Alignment | |
| |
| |
Aligning Stakeholders | |
| |
| |
Who Are Your Stakeholders? | |
| |
| |
What Should You Accomplish in a Stakeholder Meeting? | |
| |
| |
Deciding What to Measure with Your Stakeholders | |
| |
| |
Leading indicators | |
| |
| |
Business Impact | |
| |
| |
Assigning Financial Values to "intangibles" | |
| |
| |
Defining Your Participants | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
The Measurement Plan | |
| |
| |
Defining the intervention(s) | |
| |
| |
Measurement Map | |
| |
| |
Hypotheses or Business Questions | |
| |
| |
Defining the Metrics | |
| |
| |
Demographics | |
| |
| |
Data Sources and Requirements | |
| |
| |
Summary | |
| |
| |
Note | |
| |
| |
| |
It's All about the Data | |
| |
| |
Types of Data | |
| |
| |
Tying Your Data Sets Together | |
| |
| |
Difficulties in Obtaining Data | |
| |
| |
Ethics of Measurement and Evaluation | |
| |
| |
Telling the Truth | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
What Dashboards Are Telling You: Descriptive Statistics and Correlations | |
| |
| |
Descriptive Statistics | |
| |
| |
Going Graphic with the Data | |
| |
| |
Data over Time | |
| |
| |
Descriptive Statistics on Steroids | |
| |
| |
Correlation Does Not Imply Causation | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
Causation: What Really Drives Performance | |
| |
| |
Can You Create Separate Test and Control Groups? | |
| |
| |
Are There Observable Differences? | |
| |
| |
Did You Consider Prior Performance? | |
| |
| |
Did You Consider Time-Related Changes? | |
| |
| |
Did You Look at the Descriptive Statistics? | |
| |
| |
Have You Considered the Relationship between the Metrics? | |
| |
| |
A Gentle Introduction to Statistics | |
| |
| |
Basic Ideas behind Regression | |
| |
| |
Model Fit and Statistical Significance | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
Beyond ROI to Optimization | |
| |
| |
Optimization | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
Share the Story | |
| |
| |
Presenting the Financials | |
| |
| |
Telling the Story and Adding Up the Numbers | |
| |
| |
Preparing for the Meetings | |
| |
| |
Summary | |
| |
| |
Notes | |
| |
| |
| |
Conclusion | |
| |
| |
Human Capital Analytics | |
| |
| |
Alignment | |
| |
| |
The Measurement Plan | |
| |
| |
It's All about the Data | |
| |
| |
What Dashboards Are Telling You: Descriptive Statistics and Correlations | |
| |
| |
Causation: What Really Drives Performance | |
| |
| |
Beyond ROI to Optimization | |
| |
| |
The Ultimate Goal | |
| |
| |
What Others Think about the Future of Analytics | |
| |
| |
Final Thoughts | |
| |
| |
Notes | |
| |
| |
| |
Different Levels to Describe Measurement | |
| |
| |
| |
Getting Your Feet Wet in Data: Preparing and Cleaning the Data Set | |
| |
| |
| |
Details of Basic Descriptive Statistics | |
| |
| |
| |
Regression Modeling | |
| |
| |
| |
Generating Soft Data from Employees | |
| |
| |
Glossary | |
| |
| |
About the Authors | |
| |
| |
Index | |