Matchmaker, Matchmaker, Make Me a Match

Lovers of musical theatre will immediately recognize the title of this post as a lyric to the Tony-award winning Broadway musical, “Fiddler on the Roof.” The story revolves around a fiddler, who in 1905 hires a matchmaker to find suitable husbands for each of his five daughters. The pool of husbands to consider lived in or near their small Russian town, narrowing potential choices.

The Fiddler on the Roof-matchmaker situation is not unlike the pool of candidates recruiters typically have to select from when filling open positions—and it’s equally outdated. Their small towns consist of Indeed.com, LinkedIn, and Monster. In neighboring villages are recruiters, who may be able to cast a slightly wider net.

Equally challenging is the online dating scenario where one uploads a profile and gets swarmed with a flurry of candidates who don’t meet the necessary criteria for a good match. There’s so much swiping left to find the few suitable profiles worth swiping right!

No matter how you approach job matchmaking, there are two significant challenges to address: quantity and quality. While you want to optimize the intersection between quantity and quality, let’s analyze them separately.

Quantity

Sourcing is the top of your recruiting funnel. You want to feed into that funnel as many people as you can who meet your job requirements and pre-defined criteria, including:

  • Distance/geographically desirable
  • Education
  • Total years working
  • Relevant experience
  • Position keywords

If you focus solely on those who are actively seeking jobs, the best candidates may not be readily visible to you and your hiring team. Sometimes it feels like searching for a needle in a haystack to locate the best candidates—and quickly. Why? These potential hires aren’t actively seeking to change jobs. As passive searchers or happily employed, they are invisible to recruiters. That means you could be missing up to 50% of the total talent population when seeking your perfect match.

Today’s typical candidate pool consists solely of active job seekers when the total group ought to also include:

  • Individuals working with a recruiting firm
  • Passive job seekers
  • Happily employed people

Artificial Intelligence (A.I.) can help remove inefficiencies by utilizing algorithms to seek out hard-to-find candidates. Provided you have clean data and clear requirements, A.I. can generate a robust list of talent for the hiring manager’s consideration.

Quality

Consider when there’s a job opening in your company. In today’s environment, a flood of résumés hits your email and inbox. The stack gets sifted through, with a majority of the submissions not fitting your job description or meeting minimum requirements. Recruiters often spend more time disqualifying people than qualifying them. How inefficient and frustrating!

Now, imagine a different scenario. You post a job with clear requirements, and your A.I. solution trawls external and internal databases for potential applicants. When you arrive at your office the next morning, coffee in hand, and fire up your computer, you’re greeted with one email listing 46 candidates who meet or exceed your specifications. No more sifting. No more swiping left to discard those undesirable applicants who show up repeatedly.

Recruiters and human resources managers love passive candidates, primarily because they allow recruiting functions to demonstrate they are adding value.  A downside to hiring passive candidates is there’s typically a longer lead time as they’re already happily employed.

Another aspect of this equation is that recruiters often encounter candidates who have excellent qualifications but aren’t the right fit for a currently open position. Traditionally, talent pipeline management has been limited or non-existent. (A letter is sent informing the applicant that their résumé will remain on file for a specific period and the C.V. gets tucked away to gather dust until the next scheduled purge day.)

A.I. can facilitate candidate relationship management, by repurposing acceptable candidates who were previously engaged. Current A.I. solutions like HiredScore are capable of grading candidates and, when a vacancy opens up, generating a shortlist of those candidates “on file” who could potentially be a great fit.

Summary

By implementing A.I. algorithms, companies can proactively find ideal and hard-to-locate candidates who fulfill job requirements. These processes reduce recruiting costs and streamline hiring cycles, often allowing sourcing and screening to occur in parallel. Our next post will explore the benefits of using A.I. during the laborious screening phase. In the words of our Fiddler’s daughters, “Find me no find/Catch me no catch/Unless he’s a matchless match.” That’s a tune every hiring manager can get behind.

2018-07-27T17:11:50+00:00July 27th, 2018|Insights, Insights - Companies|