In this episode, co-hosts Ron Landis and Jennifer Miller deconstruct natural language processing (NLP), a technique used to drive insights from text based information. They focus on how natural language processing can uncover information from different types of text such as performance management reviews, employee engagement responses, pulse survey responses, and job descriptions.  

In this episode, we had conversations around these questions:  

• What is natural language processing?  
• How can natural language processing be used in HR?  
• What are some of the data analytic requirements needed to use natural language processing?  
• What are some clear steps that HR professionals can take to use natural language processing?  

Key Takeaways:  

• Natural language processing utilizes machine learning algorithms to interpret and process text.  
• Ron and Jennifer provide an in-depth example of how performance feedback in the form of text could be used in conjunction with quantitative ratings. They discuss the example in the context of the data analytic process. First, what problem are you trying to solve? Second, what kind of data do you have to answer the question? Third, they discuss some of the NLP techniques. Finally, they provide recommendations on interpretation and communication to other key stakeholders.  
• At the end of the episode, Jennifer and Ron recommend steps for folks just starting out in this space all the way to the more advanced HR professional.  

Related Links  

• Millan Chicago 
• Basics of Text Analysis for HR 
• What is Natural Language Processing, and How is it Used in Workforce Analytics?