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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 - 34:51] 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

Connect with Chris on LinkedIn. Visit https://www.kunzeanalytics.com to learn more about his space. 

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Connect with me: 

LinkedIn

 Twitter

Email: david@turetskyconsulting.com

This show is brought to you by Turetsky Consulting LLC, our company providing business consulting on Analytics, HR Processes, and Rewards with a focus on getting answers that organizations need by demystifying People Analytics.  

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