Coming soon · Book Profile
Predictive HR Analytics, Text Mining Organizational Network Analysis with Excel
A practical, do-it-yourself guide showing HR professionals how to run predictive analytics, text mining, sentiment analysis, and organizational network analysis entirely in Microsoft Excel to drive better business decisions.
A profile of this book is on the way.
What it’s about
This is the only book that teaches Predictive HR Analytics, Text Mining, and Organizational Network Analysis using tools you already own and know—Microsoft Excel and free add-ins—without months of learning R or buying expensive SPSS software. Through step-by-step print-screen instructions, it walks you from defining a business problem through the ARHAT framework, gathering and analyzing data with decision trees, correlation, multiple and logistic regression, mining unstructured text into word clouds and sentiment scores, and mapping employees' social networks into measurable centrality metrics. Packed with real-world case studies (Best Buy, Nielsen, Xerox, HP, Hilton, JetBlue) and dozens of HR metrics, it shows you how to predict attrition, performance, engagement's impact on sales, diversity's impact on EBIT, and workplace accidents—and crucially, how to translate those findings into an engaging data story that drives change.
The through-line
- Who it’s for
- An HR or people analytics professional who wants to deliver data-driven recommendations that improve business performance and establish credibility with executives.
- The problem
- They need to run predictive analytics, mine text, and analyze networks but lack expensive software, programming skills, and a structured method. They feel intimidated by statistics and machine learning and fear their analytics won't be trusted or won't drive change.
- The plan
- Learn the basics of machine learning, statistics, and the analytics maturity model
- Apply the five-step ARHAT framework to a real, sponsor-backed business problem
- Install free Excel add-ins (Analysis ToolPak, Solver, NodeXL, Azure ML) following step-by-step instructions
- Run decision trees, correlation, regression, logistic regression, text mining, sentiment analysis, and ONA
- Translate findings into a data story with narrative and visuals to drive stakeholder action
- The payoff
- You predict attrition, performance, and engagement impact with confidence · You uncover actionable insights from text and social networks · You tell compelling data stories that win executive approval and drive change
See our guide
Related profiles we’ve built
- Beyond Hr Boudreau Ramstad →
- Compensating Your Employees Fairly →
- Handbook of Regression Modeling in People Analytics →
- Transformative HR: How Great Companies Use Evidence-Based Change for Sustainable Advantage →
- Work Rules! →
- The basic principle of people analytics learn how to use hr data to drive better outcomes for your business and employees →
Additional reading
- Jack: Straight from the Gut · Jack Welch
The book critiques the widespread, unthinking adoption of GE's '20-70-10' performance ranking system as a prime example of management fad-following, which talentship aims to replace with context-specific, logical analysis.
- Moneyball: The Art of Winning an Unfair Game · Michael Lewis
Used as a key analogy for talentship. It demonstrates how a decision-science approach can identify undervalued, pivotal capabilities to create a competitive advantage, just as talentship aims to do for organizations.
- Work Rules! · Laszlo Bock
Written by Google's former head of People Operations, it provides detailed insights into how Google uses a data-driven approach for hiring and management, a core theme of this book.
- Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things · Bernard Marr
The author's own book, recommended for readers who want more detailed guidance on creating the data strategy that is presented as the foundational first step for data-driven HR.
- High Output Management · Andy Grove
Referenced in the book as an example of how to think analytically and build a business case for a management decision, specifically regarding the ROI of a manager training their own team.
- The Power of People: Learn How Successful Organizations Use Workforce Analytics to Improve Business Performance · Guenole, N., Ferrar, J., & Feinzig, S.
Cited in the book, this is a foundational text that aligns with the book's core theme of using workforce analytics to drive tangible business improvements.
- Human Capital Analytics: How to Harness the Potential of Your Organization's Greatest Asset · Pease, G., Byerly, B., & Fitz-enz, J.
Cited in the book and written by a pioneer in the field, this work provides a comprehensive view on human capital analytics, complementing this book's hands-on manual approach.
- Handbook of regression modeling in people analytics · Keith McNulty
The author's previous book, likely providing foundational quantitative skills for readers who are new to programming or data analysis in R.
- ggplot2: Elegant graphics for data analysis · Hadley Wickham
The definitive guide to the `ggplot2` package in R, which is the foundation for the `ggraph` network visualization package used extensively in the book.
- Stanford Large Network Dataset Collection (SNAP) · Stanford Network Analysis Project
A key public resource with a wide range of large network datasets, recommended by the author for further practice and exploration beyond the book's examples.