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Recruiting online market giants Monster.com and CareerBuilder.com have upgraded their platforms. The announcements came on April 30 and May 2, respectively. This timing may have been coincidental, but their motivations are not.
The recruiting online platforms are making better use of their data and new technologies, and have improved their job-matching algorithms. Both said the changes make it more likely a job seeker will find a relevant job and apply for it, which they said should help improve the quality of candidates that an employer sees.
The two sites are responding to broader recruiting online market trends, such as the use of algorithms to rank jobs applicants. But these firms are also "trying to get out of the image that they're job boards," said Michael Rochelle, chief strategy officer and principal HCM analyst at Brandon Hall Group, a research and analyst firm.
Monster and CareerBuilder want to be seen as a "next-gen sourcing, technology rating platform," Rochelle said.
The recruiting market is responding to problems
The recruiting online market is responding to two major problems, Rochelle said. The first is to try to remove unconscious bias in the sourcing and interviewing of candidates. That could open up new talent pools, previously excluded because of biases, he said.
Another driver for recruiting platforms is to gain a better understanding of the new people coming into the workforce, Rochelle said. Recruiting firms are gathering more data about a person, and their digital footprint on social media, to find out how they might fit in an organization.
A business driver is the need for a "more scientific, more data-driven approach to finding the right people for our organization," Rochelle said. HCM is going through "an entire re-engineering" to focus more on "data and data science," he said.
"The jury is still out on whether or not the algorithms are flawed," Rochelle said.
Algorithmic analysis is driving recruiting
The use of algorithms and machine learning technologies also has been fueling recruiting online platform startups. But these technologies may not matter as much as the data, said Jonathan Beamer, Monster's chief marketing officer, in an interview.
An example might be Stella.ai, a just-launched platform that uses algorithmic analysis to screen candidates and then match the best candidate with the available job.
Jonathan Beamerchief marketing officer, Monster.com
"The algorithms are quickly becoming commoditized," Beamer said. A startup that may have a better algorithm "will be quickly drowned out" by "a firm with better scale," he added.
"The algorithm is less important than the amount of data that you have," Beamer said. The data informs the algorithm, and "an OK algorithm can outperform a good algorithm if you have more scale and more data," he said. Monster said it has more than five million job ads.
Monster also said it is deploying best-in-class algorithms to improve the job seeker experience on its recruiting online platform. The company said it has a smarter job matching algorithm, and a refined matching process. It also improved the site's page performance. In addition, Monster removed ads from its job searches to limit distractions, and said more changes are on the way.
CareerBuilder uses Google's search engine
CareerBuilder has been working with Google's Cloud Job Discovery platform and said that it was "fully migrating" over to its platform for job searches.
The online recruiting market is moving to a "quality" model, said Irina Novoselsky, CareerBuilder's president and chief operating officer.
The recruiting online site is working with data it gets from candidates. Although CareerBuilder is using Google's search engine capabilities, it has developed its own machine learning capability to analyze, for instance, resumes to help match job seekers with jobs. Novoselsky said CareerBuilder has 200 data scientists on its payroll.
CareerBuilder has also developed into a platform offering a number of HR services, including benefits administration and onboarding.
Some of the recent changes are being driven by a competitive job market, but others are the result of an improving technology, Novoselsky said. "Five years ago, we wouldn't be able to do some of the AI matching that we're doing today," she said.