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What Informs Your Hiring?

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Psychological Science

Pre-hire tests designed to define a personality type or profile are not scientifically valid for predicting new hire performance. 

Psychological science has long proven that people vary more by degrees than by type. So, hiring tools that purport to help you hire a “profile type” are likely to do more harm than good.

At a time when all organizations are asking themselves hard questions about their commitment to diversity, hiring tools need to help, not hinder meeting such goals.

Enterprise Hiring Platform

Pre-hire profiling tests, like the Myers-Briggs Type Indicator and the DiSC Personality Test, do not predict job success. 

Instead, profiling tools reinforce stereotypes that encourage managers to seek out people like themselves. Profiling institutionalizes a preference for a particular demographic, which flies in the face of ensuring diversity of types of people brought into the company. 

When trying to gauge an employee’s work style and how they’ll fit and work with others, a profiling tool offers little more insight than a “Which Game of Thrones Character Are You?” Buzzfeed quiz. 

When flawed and inaccurate profiling quiz results are used to measure new hires against, organizations may end up with a workforce that very closely mirrors the existing workforce, creating a complete lack of diversity. 

Enterprise Hiring Platform

Pre-hire profiling tests, like the Myers-Briggs Type Indicator and the DiSC Personality Test, do not predict job success. 

Instead, profiling tools reinforce stereotypes that encourage managers to seek out people like themselves. Profiling institutionalizes a preference for a particular demographic, which flies in the face of ensuring diversity of types of people brought into the company. 

When trying to gauge an employee’s work style and how they’ll fit and work with others, a profiling tool offers little more insight than a “Which Game of Thrones Character Are You?” Buzzfeed quiz. 

When flawed and inaccurate profiling quiz results are used to measure new hires against, organizations may end up with a workforce that very closely mirrors the existing workforce, creating a complete lack of diversity. 

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Hiring Based on Profiling Leads to Bias

When flawed and inaccurate profiling quiz results are used to measure new hires against, organizations may end up with a workforce that very closely mirrors the existing workforce, creating a complete lack of diversity.

Organizations achieve their diversity and inclusion goals when they make a whole-of-company commitment, starting with hiring.

A scientifically valid multimethod assessment to measure the whole candidate with all the weaknesses and compensatory strengths that make us human is a proven method for achieving these goals.

The Solution: A Scientifically Valid Multimethod Approach

Organizations achieve their diversity and inclusion goals when they make a whole-of-company commitment, starting with hiring. A scientifically valid multimethod assessment to measure the whole candidate with all the weaknesses and compensatory strengths that make us human is a proven method for achieving these goals.

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Why Fairness Matters 

As new approaches to hiring driven by data science are becoming more common, many organizations that have long pursued the legal definitions of fairness in hiring are asking if these standards are sufficient to meet the higher ethical standard of “fair”. Put another way, is it sufficient to meet the 4/5s rule or should organizations expect their hiring tools to do more to uncover talented individuals?  

Using data-driven science and technology to create a continuously improving process can effectively manage to meet the legal standards of adverse impact while also addressing other types of common human decision-making bias. 

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Can you answer the following questions about your current hiring solution or vendor? 

Are the pre-hire assessments validated in accordance with accepted practice? 

  • Any assessment solution can promise to predict outcomes and reduce bias accurately, but where is the proof?
  • At Modern Hire, decades of research, hundreds of client validation studies, and hiring and performance data from over one hundred million applicants provide the scientific and analytical foundation for our pre-hire assessment solution, the Virtual Job Tryout.  

Is the process candidate-centric and transparent? 

  • Many vendors talk about candidate experience, but do they measure it? Pre-hire assessments should help candidates better understand the role and the organization to aid in their decision-making. 
  • Look for assessments that inform candidates if artificial intelligence is being applied and how their data is being used.   

Resources

  • People in business suits in front of graphic

    Principles for the Ethical Application of AI to Employee Selection

    Using AI to inform high-stakes decisions about people means taking responsibility for the outcomes. It means a commitment to understanding how decisions are made and being accountable for its impact on your candidates and organization.

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    Redefining Success: Talent Analytics for the Future

    The latest report from Aptitude Research is based on research collected during the last quarter of 2020 and looks at how companies are redefining success, rethinking talent analytics, and preparing for the future.

  • Woman at computer with pencil in mouth

    Pre-hire Assessments Help Avoid Bias

    Pre-hire assessments can help you overcome these common hiring challenges, but only if the assessments are grounded in validated science.

  • assessment of candidates

    What are assessments, and do I really need one?

    Assessments are a way of gathering data during the hiring process. Find out how a Modern Hire assessments can help improve your hiring results.

  • Apple computer at desk

    Technology & Science Improve Hiring Efficiency

    These days, everyone is being asked to do more, with less. With an enterprise hiring platform like Modern Hire, you make even better use of your recruiting talent and achieve better hiring results.

  • metrics at a computer

    Measure Twice, Cut Once: It Is All About Job Fit

    Sage advice to the trades suggests an accurate fit can be achieved by taking the time to measure, and then to make a second measure to verify, before cutting. Two measures increase the confidence in and accuracy of the cut.

  • Six Reasons to Invest in Job Simulator Assessments

    Job simulation assessments are designed to predict candidates’ success and offer a realistic preview of what it’s like to work in that role.

  • Does Your Assessment Fit?

    Choosing a pre-hire assessment is a lot like buying a swimsuit. It all comes down to fit. The style, material, or head-turning price tag doesn’t matter a bit if it doesn’t fit.

  • How Do Your Employment Assessments Stack Up?

    Technology is changing employment assessments – when they are used, how they are delivered, and what it’s like to participate in one as a candidate.

  • Modern Hire’s Ethical AI Position

    At Modern Hire, we respect the need for transparency in the application of AI technology to organizational employment, due to its potential for both beneficial and harmful effects. We believe there is no more important area of professional life than employment and organizational selection.

  • two people at computer looking at gallery

    Can We Return to Work Stronger?

    Despite all of the uncertainty surrounding the return to work, many recruiting teams are ensuring a stronger future for their organization through better hiring.

  • People at table reviewing charts

    The Future Is Fair: How AI Is Eliminating Bias

    Bias has been a concern for hiring professionals for decades. The good news is that the responsible application of technologies like artificial intelligence can be the key to a future of fair and transparent hiring practices.

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Ready for a candidate-centric hiring process?

With Modern Hire’s HR technology on your side, and our tens of millions of candidate interactions, your hiring process will be efficient, effective, and fair.

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