Machine Learning Applications in HR

Typing “What is machine learning (ML)?” into a Google search opens up a pandora’s box of forums, blogs and academic research. The purpose of this article is to simplify the definition of ML and how can you apply ML in human resources.

What is Machine Learning?
“Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to “learn” and acts like human do from data, without being explicitly programmed.”

The name machine learning was coined in 1959 by Arthur Samuel.

You can find different definitions I found this from Wikipedia with slight change here.

Data, quality data, this is the first essential requirement. If we want to better understand, for instance, what employee experience is like in our company, the first thing to do is to make sure that we are storing really relevant data on the company: we need accurate, digitized information on employee turnover, employee satisfaction, feedback processes we implemented (performance appraisals, one to one, coaching …), and more. Once we have correctly established the data sources, it will be necessary to assure their quality through data integrity validation processes that allow us to discard repeated, inconsistent, or outdated data.

ML in HR can influence and shape any number of HR systems or processes. Whether it’s hiring and working with technology to find the best employees for the job or analyzing how employees relate to your business to help you make appropriate changes to your culture or processes, machine learning is a valuable tool for all HR teams.

Here are some of the ways technology trends are shaping machine learning tools that HR can use and benefit from.

Saving Valued Time
Time is money and you know worth of time when there is urgency. ML allows HR departments to quickly assess and analyze applications during the recruitment process. Based on keywords and other measurements, machine learning applications and software can help HR management find the highest quality candidates based on pre-determined factors. It can help speed up the application process by offering HR managers and recruiters a quickly assessed candidate profile from a talent analytics perspective, saving valuable time.

Performance and Engagement
ML in HR also extends to performance evaluations and measuring employee engagement. More and more HR departments are adding additional feedback software and programs to give their employees an opportunity to offer feedback at more than just at their annual review. Machine learning can be implemented alongside these programs to analyze trends among employees. A few of these trends include tracking keywords that appear in various employee reviews and issuing reports on the number of positive and/or negative ratings that are submitted, which can help to track employee trends and overall employee morale. This can help HR departments see trends among employees and work to implement changes or address concerns.

Enriched predictive capabilities
ML can help predict key movements (attrition, job role success, adverse events) and their impact. HR teams can set clear parameters that map possible scenarios and can, therefore, assess the extent of possibility in a particular case. Findings based on these parameters can then be collected, converted to analytics, and decisions can be made, which are more intelligent and well-articulated.

Conclusion
Machine learning and AI have opened new possibilities for HR departments. It allows HR to see the most complete information available and helps businesses make decisions based on data. This data allows them to hire the best people and make changes to business culture if necessary, all benefiting the organization. Has your business used machine learning to create more robust HR processes or better employee data gathering?