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Predictive Hiring Using Brain Science

It’s a challenge in and of itself to get quality candidates to even apply for your openings these days, yet alone hiring top talent that’s a fit for the role and your culture. The current labor market is causing employers to look to different approaches when it comes to hiring employees. Given the weak correlation between previous work experience and future job performance, savvy hiring managers are now recognizing the power of data in the selection process through more of a predictive hiring approach.


What is Predictive Hiring?

Predictive hiring uses data and analytics to improve the hiring process by predicting best-fit candidates based on various performance metrics and key performance indicators.


While traditional hiring practices are often based on brief resume screenings and the recruiter's gut-feeling during interviews, predictive analytics for hiring leverages statistical algorithms and artificial intelligence to identify the likelihood of future outcomes. The goal is to directly correlate various data points to desired business outcomes. Meaning, allowing employers to make predictions about candidates and improve the talent acquisition process through data-driven decision making.


How Does Predictive Hiring Benefit a Company?

Here are a few of the many ways an employer can leverage predictive hiring to benefit their companies.

  • Increase Employee Productivity

  • Reduce Unwanted Turnover

  • Improve Net Promotor Scores

  • Lower Accident Rates

  • Reduce Shrinkage

  • Improve Quality of Hire

  • Remove Bias from Hiring

  • Improve Customer Retention

  • Grow Sales Revenue

Removing Bias

While there are numerous data points that are leveraged for predictive hiring algorithms such as total years of experience, certifications, college GPA, and many others. These data points don’t always remove bias in their predictions.


In 2018, Amazon reportedly scrapped an AI and machine learning-based recruitment program after it was found out that the algorithm was biased against women. Amazon’s AI model was programmed to screen candidates by observing patterns in resumes submitted to the company over a 10-year period. The majority of those candidates had been men, which led the system to deduce that male candidates were preferred over female candidates.


Whatever data sets you’re using for predictive modeling in the hiring process, you will always want to test out the algorithms to confirm they don’t show bias against a protected class.


Science-based Assessment

One important aspect of predictive hiring these days is done by leveraging candidate assessments. Using the right type of pre-employment assessment can be a key difference in accurately screening candidates and identifying the right person for the job, manager, and culture. Like research has shown, past experience is less relevant when it comes to predicting future job performance. Job performance and retention data continue to show that emotional intelligence is a key differentiator between top performers vs. average and weaker performers.


Additionally, by using a candidate assessment that has proven to show no bias against a protected class you will eliminate bias from your data sets and create level-playing field that will help with diversity and inclusion. The ZERORISK HR Emotional Intelligence assessment is one such candidate assessment that has proven to be objective while also measuring emotional intelligence. The tool is based on the deductive social science Axiology and has gone through rigorous validation studies over the last 25 years to confirm a complete objective and unbiased evaluation of the candidate.


Axios in Greek means worth or value. Axiology is the social, deductive science that measures how a person assigns meaning to things and makes decisions (i.e. how they think). The powerful 15-minute assessment identifies what someone naturally gives attention to, what their natural blinds spots are, and also identifies the resolution that is happening in various parts of the brain that allow for clarity in thinking and judgement (i.e. emotional intelligence).


The science of Axiology tells us that the brain processes things through three different filters, and that we use those three filters when thinking about things that are external to us (i.e. World View) and things that are related to us personally (i.e. Self View).


The brain’s three thinking filters are:

Intrinsic Thinking Filter – Intrinsic thinking applied to our World View is the ability to see the uniqueness in others and to be able to personally identify with other people and things. This particular thinking is the source of empathy and relationship building skills. Intrinsic thinking applied to our Self View is the ability to handle rejection and critique in stride and to exhibit courage.


Extrinsic Thinking Filter – Extrinsic thinking applied to our World View is the ability to see how other people and things relate and compare to each other. This particular thinking is the source of common sense, and the ability to focus on efficiencies in achieving desired outcomes. Extrinsic Thinking applied to our Self View is the source of self-confidence, persuasion skills, competitiveness, and energy.


Systemic Thinking Filter – Systemic thinking applied to our World View is the ability to pay attention to rules, processes, and systems. This particular thinking is the source of rigidity and being dogmatic. Systemic thinking applied to our Self View is the source of work ethic, accountability, and the internal rudder that guides us from personal right and wrong.


By evaluating the thinking patterns and correlative trends to various performance metrics, the tool has been found to be a great data set for predicting employee outcomes and performance. The Axiological assessment has been used in thousands of predictive modeling studies and yielded significant business results while also removing bias from the hiring process.


Case Studies Using a Science-based Assessment for Predictive Hiring

The proof is the pudding, so-to-speak. Here’s a link to three separate data analysis studies combining predictive algorithms with the emotional intelligence assessment based on the science of Axiology.


These case studies show the value of combining data analysis with assessment technology based on a formal and deductive brain science.

Three-Step Process for Implementing Predictive Hiring Using an Assessment

Step 1: Identify a job title in your organization, as well as the top, average, and bottom performers for that title, based on measurable performance metrics. Examples of key metrics to use might be turnover, sales revenue, or customer retention. They key to this step is to separate the performance groups by a consistent performance metric so to compare apples to apples.


Step 2: Have your employees complete a validated behavioral assessment that has proven to be objective and show no bias against a protected class. They key to this step is how you communicate the assessment to your employees. Make sure they know that their job status isn’t based on the assessment results, and that they are assisting in gathering data that will benefit the company and the culture.


Step 3: Once your study group has completed the assessment, the data analysis process begins. Review the data findings from the assessment provider showing the patterns that separate the three performance groups. This data is usually presented to the participating company to debrief on the findings and to sign-off on incorporating the findings in the hiring process going forward, whereby candidates for that job title will complete the same assessment as the study group and then compare to the top performers to predict the likelihood of success for candidates.


Workforce Tomorrow Research Initiative for Predictive Hiring

As a way to begin building predictive hiring data for your organization, the Workforce Tomorrow Research Initiative is a human capital research study that aims to correlate Emotional Intelligence Quotient (EQ) competencies to employee and organizational performance metrics such as:

  • New hire sales revenue

  • Net promotor scores

  • Employee engagement & satisfaction scores

  • Turnover rates

  • Customer satisfaction scores

  • Agile Development Time

  • Theft Reduction

  • Patient Satisfaction

  • Safety

Whether you're learning to manage a virtual workforce or restructuring your company due to loss of revenue, we are all navigating new challenges to the way we work. Emotional Intelligence is more important to organizational success than it has ever been. Eighty percent of the competencies that correlate to success at work relate to emotional intelligence.


The main objective of the research study is to identify the core emotional intelligence competencies that correlate to objective performance data and great workplace cultures. This information will help companies accurately evaluate and ultimately hire, develop, and retain the best employees for their specific positions and company culture, thereby positively influencing the bottom line. This initiative was created to help you make strategic human capital decisions that positively impact your workforce of tomorrow.


ZERORISK HR is fully funding the Workforce Tomorrow Initiative on a limited basis to organizations that qualify. Research projects such as this typically cost upwards of $10,000 for each participating organization. This complimentary study is an excellent opportunity for your organization to define best practices to enhance your financial performance and retain a quality workforce without an upfront investment.

If your organization is interested in predictive hiring using brain science and emotional intelligence, please go to the following link Workforce Tomorrow Research Initiative for more information and to submit your application to begin the process.



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