HR Data Labs podcast – Episode 13 – Applicability of Predictive Models for Assessments in the World of HR

While insights certainly measure the past, data can also be used to predict the future. Chris Kunze is the Founder and President of Kunze Analytics where he assists decision-makers, sales leaders, HR professionals, trainers, and coaches in order to predict employee performance, retention, engagement, and safety. Chris is a self-proclaimed Data Geek who dives into the data to find ‘hidden talent.’

Let’s get a bit technical today and learn from Chris how he uses the Predictive Model Markup Language used to create and run models in different software packages.

[00:01 – 05:18] Opening Segment

•  Let’s get to know Chris Kunze
• Chris gives some background on himself
• Chris talks us through some of the in and outs of PMML

[05:31 – 07:41] Why PMML is Useful 

•  The value and importance of having a common language
•  Automating your process

[07:55 – 23:39] The Most Predictive Data for Employee Performance

• PMML’s usefulness in assessment data
• Chris talks about creating and running models
• Reliable data designed to be used for serious decisions
• Finding hidden traits; Chris’ example
• Chris’ advanced statistical modeling test set

[23:53 – 32:36] Coaching; Insights from People Analytics

•  Chris talks about his experience with training students
• Pulling out people’s greatest strengths
• The ability to monetize your work

[32:37 – 35:41] Closing Segment

• Summarizing our discussion today
• Final Words

Tweetable Quotes:

•  “This [PMML]  is a way the industry can standardize concepts, and provide some transparency…” – Chris Kunze
•  “What gets measured gets managed, if you don’t know what your measurements are you don’t know where you stand or where you can make and track improvements.” – David Turetsky