Streamline HR functions with Machine Learning
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Streamline HR functions with Machine Learning

By CIOReview | Friday, August 24, 2018

Like every facet of modern business, technology presses on its journey of transforming how we function and behave. Human Resources (HR) is one such department that despite containing the word “human” in it has benefitted from technological transform. From big data to Internet of Things, virtual and augmented reality, mobility, cloud computing, blockchain, and a legion of technologies, both emergent and evolving, have encroached into sophisticated HR domains in the industry.

The technology that most strikes the eye in augmenting HR refinement and progression is Machine Learning (ML) coupled with Artificial Intelligence (AI). Historical data has increasingly come in handy when identifying trends and patterns. ML is capable of efficient management, streamlining and automation of the most routine tasks.

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By gaining insights on the company and assimilating pertinent knowledge, machine learning can

•  Track, guide and enhance employee growth and development

•  Aid in performance reviews

•  Identify knowledge gaps or weakness in training

•  Fine-tune and personalize training to make it more accessible and relevant to the employee

•  Be a resource for information and questions related to company policies, benefits, company procedures and basic conflict resolution

While machine learning is not a new technology in itself, it is making a significant impact with the increasing popularity of its applications for human resources. The technology has already been able to manage efficiently the following tasks:

•  Measure and manage engagement

•  Personalize training

•  Better recruitment procedures

•  Reduce employee turnover

•  Schedule HR functions that include performance appraisals, interviews, and group meetings, and more

•  Enhance rewards and recognition programs

•  Analytics and report on data relevant to HR

•  Streamline workflows

The technology’s impact on HR operations has been discussed further.

Employee Engagement.

Machine learning can gather insights on the work environment by its ability to assess and interpret workforce engagement using pulse polls and engagement tools. The ultimate benefits of these insights are productivity increase and lower attrition rates.

Companies like Glint and Workometry have brought forth software solutions that measure, analyze and report on employees’ work engagement and their general view on their work.

Learning and Development.

Using machine-learning tools, HR has the option to personalize learning based on a person’s job experience, profile, past learning patterns, and skills required to get ahead in the job. HR can improve their employees’ learning roadmap by recommending the optimum learning courses based on historical data with the use machine-learning tools.


Artificial intelligence paired with machine learning can be utilized in initiating a regular touch point with a company’s new recruit. Machine learning interfaces can dispatch reminders for document or form submissions using conversational chatbots. They can further auto-fill fields in extensive forms and answer basic queries of a prospective employee, keeping them engaged.

Managing Attendance, Time and Leave.

Manual registers no longer record employee attendance. They have become obsolete after the introduction of biometrics, mobile applications and CCTV based platforms where time and attendance go into record using facial recognition. These technology-infused tools provide companies with significant timesavings.

Tools of machine learning like PeopleStrong’s Alt Worklife mobile application have made it possible to assist employees, who take sick leave, with information on doctors and insurance policy comparisons. Companies are able to assess trends of leave with respect to employee performance with the assistance of machine-learning tools.


Machine learning algorithms make it easier to construct a job description by suggesting applicable skillsets desired for the job. With its assistance, recruiters can acquire market data on salary statistics, skills, and competitive jobs.

ML relieves hiring managers of the troublesome task of manually screening candidates from hundreds of aspirants. The technology can obtain candidates from multiple sources like social media, job boards, and more, and offer insights on prospective candidates. It would be beneficial in employee referral programs and helpful in scouting passive talents.

Companies like LinkedIn and Glassdoor, employ machine learning’s intelligent algorithms to better their chances of attracting suitable candidates.

Employee Turnover.

ML tools help HR and managers predict the reasons behind employee turnover and enable them to gain a better understanding on the vital factors of the turnover. Using this information companies can reduce attrition and improve the workforce environment.

Insights from data.

HR has to stockpile huge volumes of data recording employee activities. To present usable reports, HR needs to compile this information but cannot comprehend and analyze it without the help of some form of machine learning. It will be even more difficult to identify important trends, threats and opportunities. Machine learning can analyze the data and provide meaningful viable insights to optimize workflows, improve training outcomes, and understand hiring trends, sick leave and vacation requests.

Some real world applications of machine learning in HR include automation workflows, attracting top-grade candidates for employment, and reduce time and bias while improving accuracy in recruitment.

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