February 24, 2022

Ross Piper

Wonderlic’s Revolutionary Job Matching Technology, Explained

Wonderlic’s Revolutionary Job Matching Technology, Explained
Ross Piper

So what is TrueMatch, and why should employers be excited about it?

TrueMatch is a groundbreaking new AI-driven technology developed by Wonderlic that will allow companies to more accurately—and more quickly—match their open roles with a job profile that’s unique to the specific needs of those roles.

For years, the job profiles we—and most other assessment providers—offered were based primarily on data from O*NET, the Department of Labor’s tried-and-true collection of about 1,000 rigorously researched job analyses. However, we’d long felt that O*NET was too blunt an instrument for the tailored assessment experience we wanted to curate for our customers. Its “off-the-shelf” profiles didn’t account for the nuanced differences between similar roles deeply enough, nor were they able to keep up with new, emerging job titles.

To create TrueMatch, we used O*NET data as a foundation, then spent two years analyzing data from more than ten million resumes and LinkedIn profiles of real people in real jobs. The end result is the most extensive—and richest—database of job profiles ever made.

With all these data points available to us, we’re now able to provide an in-depth understanding of the knowledge, skills, and abilities required to be successful for over 3.5 million unique jobs—a tremendous leap forward from the previous ceiling of about 1,000.

Not only will TrueMatch help the people who use our assessments identify the right job profile for their roles more efficiently, but it’ll also give them even more confidence in the data they’re using to make hiring decisions.

It’s one of the most significant leaps forward in hiring science in a long time—and I’m thrilled we’re finally launching it.

How does TrueMatch work, from a user standpoint?

It’s very simple. A user types in the job title they’d like the best job profile for.

If there’s already a perfect match with O*NET, TrueMatch provides that job profile.

When a user enters the name of a job that isn’t cataloged in O*NET, they no longer need to work with a consultant to identify the “best fit”; instead, TrueMatch is able to intelligently identify the similarities and differences between that role and others in the same “neighborhood” of jobs—and output a brand-new and entirely unique job profile automatically in under a second.

Who was involved in making TrueMatch?

TrueMatch started with some early-stage proofs-of-concept within Wonderlic’s machine learning practice. But closely collaborating with our R&D and consulting teams, who provided great feedback and validation, played a critical role soon after seeing early promise with our prototypes.

Fast forward a year and a half, and this had truly become an organization-wide effort. Getting TrueMatch across the finish line required investment and support from leadership, as well as hard work from ML engineers, R&D researchers, assessment consultants, product managers, and software engineers.

Furthermore, the rollout wouldn’t have been so smooth had it not been for the all-hands approach taken by our customer-facing teams, who understand our users and their assessment needs so intimately. It’s thanks to them that TrueMatch has been such a day one success story.

We’re always looking out for the “next big thing” in HR technology, but many of our proofs-of-concept are too early in development to discuss right now. One of our next projects slated to launch, however, is our AI-scored open-ended text assessment, the first in a forthcoming lineup of assessments featuring alternative input types to traditional multiple choice.

We’re thrilled about this product launch because it will allow us to measure critical workplace competencies (think Teamwork, Communication, and Results Motivation) by analyzing open-ended responses to short essay questions. State-of-the-art natural language processing (NLP) tools allow us to score these responses at scale with a high degree of accuracy, all while offering the additional bonus of reducing the bias often related to multiple-choice models of assessment. It’s a win-win for job applicants and employers alike, and we can’t wait to make it available to everyone later this year!

Ross Piper is the Manager of AI Innovation at Wonderlic, where his team specializes in the application of ethical artificial intelligence to HR decision-making. Recently, Ross has focused on state-of-the-art natural language processing and deep learning use cases in the hiring and employee development spaces. Prior to joining Wonderlic, he attended the University of Chicago and worked as a management and strategy consultant for numerous Fortune 500 technology companies, facilitating SaaS transformations and the implementation of cutting-edge data solutions, primarily AI and blockchain.

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