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Candidate Matching: Everything You Need to Know

Candidate Matching

Imagine a scenario. Applicant A has stumbled upon an open position at your company. They have a total of 8 years’ experience in Oracle products. Applicant B has 8 years of experience in the Oracle database. Applicant C has 8 years of experience in the Oracle commerce platform. Nearly indistinguishable? These are the nuances that any premium candidate matching software crawls, analyses, and hits it right off the park.

Two different sides emerge when the subject of job automation arises. One side thinks that these technologies need to be developed cautiously.

Or they believe that recruiting requires human efforts and not technological support.  The other doesn’t give any credence to this perspective and believes that we have nothing to fear from the latest technologies, which allow us to delegate the most rote tasks to machines. And the latter point of view seems to touch every sector of business. Especially, HR tech through job matching software.

Of all the problems a recruiter faces, job matching is the most convoluted.

According to Tilkee’s latest edition of its barometer of recruiter’s habits, a recruiter currently spends an average of 34 seconds reading a CV — 21% less time than they did in 2017— which leads us to wonder just what an algorithm can do in 34 seconds.

It can choose between applicants A, B, and C in those 34 seconds. Without predilections.

What Really is Candidate Matching?

Merriam-Webster defines an algorithm as a procedure for solving a mathematical problem in a finite number of steps that frequently involves repetition of an operation. Here, we’ll be talking about the predictive analytics used in job recruiting, where algorithms are used to predict the future performance of employees in their new companies. Sourcing and filtering algorithms were created to help recruiting services do their job, but matching-algorithm platforms, function

as a search engine for people looking for jobs. Applicants post their résumé, which is then parsed using predictive analysis to find the jobs that best correspond to the skills cited on their CVs.

In simpler words, you get the best fit for your job. In seconds.

It makes it easier for candidates – they don’t have to fill out those deterring forms anymore. It makes it easier for companies – you just passed the baton to the lesser being.

Keywords: The Chink in Our Armour

Suppose you’re a medical assistant working in a paediatrics office, and you’re looking for a new opportunity. With the typical job board software, “job matching” might mean that you type the words “medical” and “assistant” into a job search engine. There’s nothing wrong with this, except that it will present results for “assistant” positions that may have nothing to do with medicine, as well as results for “medical” positions that may have nothing to do with being a medical assistant.

In other words, you’ll waste time sifting through non-relevant job listings. Haven’t we come further than this by now? Many job board software products claim to have “job matching” included in their platforms, but they rely on keyword-based searching to run the platforms rather than the performance-based matching of positions to applicants. True job matching doesn’t rely on keyword searching, because it is about matching the most qualified candidates to the best jobs automatically and in real-time.

With true job matching, as a medical assistant, you would automatically match with medical assistant job listings for which you meet qualifications based on your resume, skill set, and preferences. 

What does Candidate Matching Involve?

True job matching also automatically allows employers to receive qualified candidates right to their employer accounts, so that they can quickly review these candidates and make faster decisions.

As a job seeker for a medical assistant position. You would deliver job matches ranked by match percentage, helping you find the most relevant positions for which you’re qualified right away. Likewise, employers receive matches from active applicants and matching passive candidates directly into their employer account, graded and ranked based on match percentage. There’s simply no better or faster way for employers and job candidates to find each other.

Objectivity and Job Matching Software

One of the most underrated aspects of candidate matching in job boards is eliminating all human biases.

Humans always conditioned to predispositions. We impulsively tend to believe that men are better at programming and women are better at HR. Candidate matching tools and candidate matching software absolutely obliterate this.

Through objectivity, comes fairness and through fairness, come equal opportunity.

Most of the job matching engines today only take into consideration the information directly extracted from the resumes and vacancies. The two sets of information match against each other based on some predefined rules.

We’ve come a lot further than that. Premium job matching tools and their sophisticated algorithm can almost take over a human.

We say almost. That is the operative word. And that shall always be.

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Data-driven Recruitment and Ways to Implement it

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