No more mystery. No more jargon.

With so many questions and so much data, the HR analytics journey can seem overwhelming. It doesn’t need to be. At HR Analytics 101, we deliver insights and know-how cleanly, simply, in plain language to drive better decisions and propel careers.

HR Insights, Simply

  • Analytics and Reporting

    Recurring, high-quality analytics insights focused on workforce essentials that establish the ground truth for people decisions and workforce actions.

  • Predictive Models

    Combining powerful machine learning with your organization-specific expertise to help you act today by seeing tomorrow.

  • HR Training and Development

    A complementary suite of programs that build in-house analytics capabilities, bring scientific rigor to your people processes, and lay the foundation for continuous workforce learning.

Our Expertise

Our deeply collaborative approach blends analytic rigor and behavioral science with your local expertise to deliver interpretable insights and powerful skillsets tuned to your specific organization and company culture.

HR Analytics

Statistics and Machine Learning

Engagement and Performance Measurement

Cognition and Employee Development

Transforming HR Professionals

We have the knowledge, perspective, and experience to fundamentally change how you understand and use HR analytics

Our Blog

Tutorials, principles, and insights to help HR analytics practitioners improve their skill set and propel their careers.

26 Jun

Starting Your HR Analytics Program? Follow this Golden Rule

Ten years ago, HR Analytics was fairly new. This made it somewhat easier to get started because few people and even fewer organizations had any idea what they were doing….

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12 Feb

R Dataframes for the Total Beginner

This short tutorial video explains the very basics of dataframes in R, the single most important data structure when using R for HR analytics task. By the time you’re done,…

01 Jun

How Correlations Can Fool You: The Hidden Dangers of Non-Linearity

knitr::opts_chunk$set(echo = TRUE) library(wesanderson) #color palettes library(dplyr) #tidyverse to make our lives better library(fMultivar) wp <- wes_palette(“Darjeeling1”) #specific color palettes Correlations are the simplest and most common statistical method for…

11 May

A Simple Model with Major Insights on Selection Bias

I mentioned earlier that I have been reading (and rereading) Scott Page’s masterful book “The Model Thinker”. If you are serious about understanding models and data as either a leader…

27 Apr

How to Avoid Aggregation Errors and Simpson’s Paradox In HR Analytics: Part 2

In our previous post we described the basic premise of Simpson’s Paradox: aggregate data and see one trend, separate your analyses and see another. Today we’ll be short(er) and sweet,…

20 Apr

How to Avoid Aggregation Errors and Simpson’s Paradox in HR Analytics: Part 1

Recently I’ve been reading Scott Page’s masterful book “The Model Thinker”. It’s full of powerful insights so in this and future posts, I will be taking things I’ve learned there…

13 Apr

How To Make A Turnover Reporting Template

In previous posts I’ve covered how to calculate and breakdown turnover data in your organization. Today I want to provide you a very basic R Markdown reporting template for analyzing…

Meet John Lipinski, PH.D.

Founder & CEO

John completed his PhD in Cognitive Psychology at the University of Iowa, followed by a three-year post-doctoral appointment at the Institute for Neuroinformatics in Bochum, Germany focusing on dynamic systems and human cognition. Since that time he has worked as a Senior Research Psychologist the U.S. Army Research Institute, spearheaded machine learning efforts in human capital analytics for a Fortune 100 company, and led product research and development for an global assessment provider.

Along the way he has witnessed firsthand the ability of data, systematic observation, and people-first processes to increase engagement, improve workplace performance, and ultimately transform lives.

He specializes in human cognition and performance, applied machine learning, and performance measurement.

The best part of his job is collaborating on data and human capital processes to break down complicated behaviors and outcomes into digestible pieces that help leaders make better decisions and help people flourish at work.

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