Much like manufacturers that gradually replaced manual labor with automation, recruiters and HR professionals replaced manual review of resumes and cover letters with data aggregators and applicant tracking software. This data analysis portion of hiring, called workforce science, uses high-tech tools to find the best candidates. The way this data mining works might surprise a lot of job seekers.
Thanks to ever-increasingly complex programs and algorithms, employers can take advantage of big data's role in workforce science. Specialized firms, such as Knack and TalentBin, use their software to match people with companies. Peter Kazanjy, CEO of TalentBin, says that with his company's recruiting technology, candidates may not even need to submit a resume for employers to get a good idea of who is a perfect fit for a position. That's because people store a resume on a computer's hard drive, Google Documents, Dropbox, LinkedIn or custom-made professional website. Rather than candidates submitting a resume, companies scan for the documents through these many sources.
A New York Times article from April 2013 shows that computer programs can analyze personality quizzes, games, surveys and other information-gathering tools to weed through thousands of candidates very quickly. Previously, workforce science was limited to hundreds of candidates in one survey, but computer programs speed up the recruitment process. Algorithms can search through social media, emails, instant messages and even someone's hard drive to find information about a candidate.
The Example of LinkedIn
When Microsoft bought LinkedIn for $26 billion, the tech giant got more than just a social network for business professionals. Microsoft bought a workforce science juggernaut filled with data on millions of people who want jobs. Candidates store all of their professional information in one place, and that makes Microsoft's information absolutely invaluable to companies seeking the perfect candidates. Instead of just scanning someone's previous employers, LinkedIn congregates a person's blog posts, communications with colleagues, liked posts and network connections.
In short, Microsoft can analyze a candidate's entire professional persona beyond a resume's keywords. This makes LinkedIn's data such a huge prize, because the point of recruiting technology is to focus on ways to narrow a large pool of candidates to a much more manageable size. When marketed to employers the right way, Microsoft has a huge gold mine in that companies can easily weed out candidates without even using a specialized applicant tracking system that requires people to upload a resume or fill out an online job application. Instead, employers just pick the type of worker they want, and then Microsoft's programming can search LinkedIn for the rest.
Workforce science shows employers one other critical aspect of recruiting. The very nature of work is changing. As of 2017, as many as 40 percent of work is classified as contingent work. A majority of jobs created in the European Union from 2010 to 2017 were short-term contract work. Rather than full-time jobs, more and more people have part-time work or self-employment opportunities.
Workforce science stands to improve when computers and technology advance. Employers must pay attention to big data trends to stay competitive, especially when it comes to LinkedIn's massive treasure trove of professional data. Recruiting isn't just about finding someone with the prefect resume anymore.
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