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LinkedIn Recruiter Unveils New Look, Candidate Matching Feature

by Apr 10, 2013, 12:01 pm ET
New Recruiter Homepage

New Recruiter Homepage

Sporting a new look and with some new features — including a recommendation engine that ‘learns’ the kind of people a recruiter most want — LinkedIn Recruiter is getting an official relaunch this morning.

The redesign itself is an update of the classic LinkedIn Recruiter look to make it more consistent with the LinkedIn homepage redesign that was introduced last fall.

Parker Barril, Linkedin’s Talent Solutions head of product, unveiled the fresh, new LinkedIn Recruiter at a live and webcast user event — ConnectIn — in San Francisco. As he put it, “the consumerization of the enterprise,” the trend toward making products and services easier to use, “is influencing a new generation of products.”

But LinkedIn Recruiter is not just putting on a pretty new face. In conjunction with the redesign, LinkedIn is adding a recommendation engine that, like matching services on job boards and tracking systems, will make suggestions for people recruiters may want to follow. Unlike those other matching systems which present lists of candidates ranked on how well they match your job description, the “People You May Want To Hire” feature uses your searching habits to come up with suggestions.

At first, you may get fairly generic recommendations. As you drill down, filtering your search to an ever finer degree, the suggestions will more precisely match your search. The more searches you do, the more LinkedIn’s algorithms will understand the kind of people you seek.

“It recommends relevant candidates for roles by analyzing previous recruiter behavior — like past searches, InMails sent and jobs posted — and identifying candidate commonalities and patterns that traditional searches might overlook — like career trajectory, job-function similarities and propensity to change locations,” added Barrile.

Previous version

Previous version

Clicking on a recommendation lets you see how good a fit the person is. Then you can add them to those you already follow, associating the person with a specific search. Until you decide otherwise, every time they update their LinkedIn profile, you’ll know. The more they contribute to the groups they’ve joined, and the more actively they manage their careers, the better you’ll get to know them.

This is a convenient way to build a talent pipeline and decide who you want to pursue when the right job comes open. LinkedIn Recruiter clients have long been able to do that. But you had to go actively search for people meeting the criteria. You still have to search, but once you do, LinkedIn helps make it an ongoing, automated process.

This article is provided for informational purposes only and is not intended to offer specific legal advice. You should consult your legal counsel regarding any threatened or pending litigation.

  • Keith Halperin

    Thanks John. The main change I’d like for LIR would be something I won’t hold my breath on:
    Having the “I’m open to new jobs/career opportunities” setting as an “OPT-IN” feature and not as currently “an “OPT-OUT” one. This would greatly improve our efficiency, as we wouldn’t be wasting our time going after people who really aren’t open to any new opportunities, but haven’t bothered to say so…

    -kh

  • Roland Behm

    To what extent have these LIR processes been validated from the perspective of not having a discriminatory impact on persons in protected classes (e.g., age, sex, gender, disability)?

    As noted in the article, “[t]he more searches you do, the more LinkedIn’s algorithms will understand the kind of people you seek.” What if there are “flaws” in those algorithms that, wittingly or not, screen out persons in protected classes? Alternatively, what if there are subtle (or even not so subtle) biases of the recruiter/employer? Won’t those biases be replicated and “insitutionalized” by this process?

    Since the employer has legal responsibility for any discriminatory aspects of its hiring and recruiting processes, it can’t point to the third-party provider (i.e., LIR) to avoid liability.

    I’m reminded of a quote from an article from about five years ago that reads, “the seemingly “scientific results” attributed to pre-employment tests [may]cause all differences to “appear” real. In cloaking imperfect measurements beneath the veil of science, the numbers touted by the test publishers are injected with an air of authority, legitimacy, and truth that intentionally or otherwise, … [may] disguise the … reality of discrimination produced by the process.”

  • http://www.matchpointcareers.com Paul Basile

    It looks to me like this new approach will successfully enable employers to make mistakes consistent with the mistakes they have made in the past. It institutionalizes bad (and good) habits. But there is nothing that I can see that improves the prediction of performance. Without that, why bother?

  • Keith Halperin

    @ Roland, @ Paul. Very good and relevant points. I do not know whether or not LI intended to do so, but either way, LI is performing a very sound business strategy- you can usually make lots of money confirming a clients, biases, prejudices, and errors while convincing them they are actually doing something different and better…

    Cheers,

    Keith
    Keithsrj@sbcglobal.net

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