What are some ways that machine learning systems can be helpful for human resources?
Wherever you look, machine learning is transforming industries. One of the later adopters is the human resources field – at first, machine learning was largely applied to marketing and customer-facing software, but now, it's expanding into offering human resources managers better ways to keep on top of managing an office of any kind.
One of the most frequent and popular ways that machine learning is used in human resources is to help weed through large numbers of resumes from applicants. It's a well-established problem at many companies that any job offer receives a flood of applications. Part of that relates to historically high unemployment after the 2008 financial crisis, but even in flush times, a lot of people end up wanting the same jobs and positions.
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Machine learning can help make the screening process a lot less labor-intensive. In a Techopedia article on trends in technology, Cristian Rennella, CEO & co-founder of MejorTrato.com.mx, talks about how his company uses artificial intelligence tools to go through the CVs of different candidates. This, he said, took the majority of the human resources department's time before the move to software, and is now done quickly and easily with automation tools.
Machine learning systems can also review resumes in more deep and intelligent ways. They can look for specific skill sets and things like the geographic location of the applicant. In some ways, machine learning systems can even take over a lot of the interview process. If a first interview is only to create a rough match in terms of skills and logistics, a lot of this can now be done with sophisticated machine learning products.
Human resources departments can also use machine learning systems to keep an eye on turnover or attrition. In too many cases, these problems are only noticed when the staffing model becomes strained, or when holes develop in a schedule. But at that point in time, it's often too late to really make a quick and agile comeback and get more people involved. By having a bird's-eye view of the organization through a machine learning platform, human resources people understand the trend before it gets too far down the road.
At the same time, human resources people can also use machine learning for talent acquisition. Machine learning systems can sort through past interactions to find what makes the company attractive to talent, so that writers can promote those things in future job postings.
As pointed out by many corporate experts, today's job ads are not just formal letters of intent. They are researched and optimized, in the same way as companies research and optimize direct mailers and other customer materials. That's because talent is so important in today's company – and machine learning helps human resources to go out there and compete in a high-pressure environment.
In addition, machine learning helps with the general responsibility of human resources communications. Items like payroll, benefits, vacation time and more can be tracked, analyzed and controlled through some type of central interface. All of this helps to streamline the work that human resources departments do on a regular basis, and that's another reason why so many companies are looking at machine learning applications for HR.
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