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People Analytics Theory, Tools and Techniques

A practical, hands-on guide that demystifies people analytics for managers and students by teaching the metrics, visualization tools, and statistical techniques needed to turn workforce data into evidence-based HR decisions.

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What it’s about

People Analytics: Theory, Tools and Techniques bridges the gap between intuition-driven and evidence-based human resource management by walking readers step-by-step through the entire analytics pipeline—from understanding the evolution and maturity levels of business analytics, to calculating HR and marketing metrics, to building interactive dashboards in Excel, Power BI, and Tableau, and finally to applying statistical and machine-learning techniques (correlation, regression, t-tests, ANOVA, logistic regression, neural networks, decision trees, factor and cluster analysis) using accessible open-source software like JAMOVI, R Commander, and Rattle. Rich with vignettes, real-world corporate case studies (Google, Coca-Cola, Wells Fargo, IBM, SanDisk), data-driven exercises, and a companion website of datasets, the book serves both management students across HR, OB, marketing, and applied psychology and practicing executives who want to implement data-driven decision-making without needing expensive proprietary software or a deep programming background.

The through-line

Who it’s for
An HR manager, management student, or business executive who wants to make confident, data-driven workforce decisions and prove HR's strategic value.
The problem
They face abundant workforce data but lack the statistical and computing skills to turn it into actionable insight using accessible tools. They feel intimidated by analytics, anxious about being seen as a non-strategic support function, and uncertain whether their HR initiatives actually work.
The plan
  1. Understand the evolution, definitions, and maturity levels of business and people analytics.
  2. Learn to calculate meaningful, benchmark-based HR and marketing metrics.
  3. Build interactive dashboards using accessible tools (Excel, Power BI, Tableau).
  4. Apply statistical and machine-learning techniques using free software (JAMOVI, R Commander, Rattle).
  5. Interpret outputs correctly and translate them into managerial action.
The payoff
Making evidence-based people decisions that demonstrably improve performance, satisfaction, and retention. · Predicting attrition, candidate joining, and training effectiveness before they happen. · Earning top-management trust and elevating HR to a strategic business partner role.

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