Expert Commentary

Learn How To Interpret Technology during the Hiring Process

Business decision-makers have more information at their fingertips than ever before, but how do you interpret technology to help ensure you are hiring the right candidates? An advanced hiring program is capable of generating real-time data and detailed profiles of top candidates. But, once you have that data, it is imperative to know what you are looking at.


Employee Hiring, Development, and Retention
September 2017

Translating what the technology says into action requires understanding the foundational elements of advanced human resources technology to make the right personnel decisions.

Leveraging Technology into the Hiring Process

In Major League Baseball, Oakland Athletics General Manager Billy Beane famously introduced the concept of "Moneyball" to manage a baseball team and make personnel decisions to build a championship team by looking strictly at the data. His foundational principles are to use analytics to interpret the data, remove bias, and let the data guide them in finding the right players for the right positions on the team.

By using analytics, Mr. Beane takes his own personal beliefs or views out of the equation. If a player hit 30 home runs last season but struck out 200 times, Beane would remove himself from the equation of weighing those 30 homers against the 200 strikeouts and let the analytics tell him whether to make a personnel move by considering all relevant data points.

The key is allowing the nonhuman technology to tell us what the best personnel decisions are for the team or the organization. It might be difficult to cut loose the player who hit 30 home runs, but it could lead to a stronger team by replacing him with a player who will only strike out 100 times next season.

In an organizational sense, your company might be looking at hiring a new sales team manager. Analytics generated by an advanced hiring program will allow you to hypothetically drop that person in the role and see if the organization benefits. It's moving beyond personal biases of thinking or believing this person is the best fit by allowing the technology to guide you.

Common Mistakes in Interpreting What Technology Says

One of the biggest mistakes companies make when attempting to translate the technology into practice is not having set procedures for how to interpret the data. The organization needs to be aligned in how to look at the data points, make evaluations, and then act in personnel decisions. But, if one department is looking at the data points differently than another department, your company could make the mistake of hiring a person who fits one department but not the overall company culture.

The best practice is to utilize the data to determine fit within the culture. Then, determine whether a candidate is a match for the role, team, and subculture within the organization. If departments are not aligned in this way, managers tend to go rogue making their own hiring decisions, distancing themselves from the advanced technology that holds the answers.

Without set processes for how to translate the technology into practice, managers cannot be held accountable for their decisions. Having those processes in place allows an organization to hold everyone accountable if a person is hired but is clearly not the right fit after being brought on board.

Another big mistake is seeking objective information based on subjective data. By definition, you cannot obtain objective information if the data is not objective.

Mr. Beane should not ask 1,000 A's fans whether he should keep a star player next season. The results of this hypothetical survey might indicate 750 fans want the player to stay and 250 want him gone. But, that subjective data will not generate the objective information that is being sought. Only unbiased technology can produce the objective information that he is looking for to make the right decision.

How To Put the Technology into Practice

An advanced hiring program helps organizations analyze results generated by technology to confirm a candidate's thinking and how that thinking manifests itself in the workplace.1 This objective snapshot includes the following.

  • Way of thinking
  • Clarity of thinking
  • Biases
  • Method for handling stress

This profile allows your company to compare the candidate's overall thinking pattern to other successful people in similar roles. Is there a fit or not a fit?

There is even more invaluable information to be gleaned from the process. A behavioral interview provides a process to ask questions that correlate to a particular competency you are looking for in the ideal candidate. Through the interview, you can dive into a candidate's past behavior in a similar context to evaluate the following.

  • Does the candidate have mastery of the competency?
  • What did they do in a specific situation?
  • What decisions did they make?
  • How did they think out their actions?
  • What was their behavior during the situation?
  • How did they work with others?
  • Was there a resolution to the situation?

These important behavioral interview questions are based on looking at the candidate's past behavior to evaluate how they will work in your environment if you hire them. This gives your company a clear picture of the candidate's thinking pattern and the likelihood of success in your company. Your company can then plug in this information and allow the technology to generate an unbiased profile, following the best practices for how to interpret technology in hiring. This ultimately guides your company in making the right hiring decisions to improve productivity, like home runs, and reduce risk, like strikeouts.


1For more information, the ZERORISK Online Behavioral Training Course allows companies to analyze these key data points found in advanced hiring technology such as the ZERORISK Hiring System. The course provides interview tools to probe a candidate's competencies to evaluate how their thinking manifests itself in behavior.


Opinions expressed in Expert Commentary articles are those of the author and are not necessarily held by the author's employer or IRMI. Expert Commentary articles and other IRMI Online content do not purport to provide legal, accounting, or other professional advice or opinion. If such advice is needed, consult with your attorney, accountant, or other qualified adviser.

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