Athena Assessment Validity
A More Detailed View -
Are Employee Performance AssessmentsValid?
Most methodologies that purport to assist in employee performance, evaluation, selection, and development are not validated. That is not to say they are entirely invalid; rather, they are typically not validated against real-world outcomes. Few, if any, have been validated with the rigor, history, and scientific objectivity of our assessment, the Athena Quotient (AQ).
The AQ has been validated multiple times across a wide range of settings, across industry sectors, employee populations, and the actual applications of the instrument. In fact, we are so confident in our claims regarding the AQ’s predictive validity that we guarantee its use.
Not only do we believe the AQ is the most predictive tool in use today, but it is also the most statistically elegant instrument for quantifying employee decision-making and therefore for predicting positive outcomes across a wide range of human resource applications.
Advanced statistical techniques are used to drive the AQ selection decision. Through best- and worst-performer sampling, we can benchmark specific judgments essential to job success.
Big Data Analysis… and why it’s important
Different jobs may require different types and levels of decision-making for an individual to be successful in that job. Our statistical techniques allow us to pinpoint these judgment requirements and give the AQ incredible referential validity. We can accurately predict who will succeed in specific jobs and who will not.
Through concurrent validation in your specific application, we’ve built “templates” that represent the ideal candidate across multiple job descriptions or positions. While highly predictive as a general hiring tool (its widest use), the AQ becomes even more powerful when combined with templates customized to your business and job descriptions.
This application of the AQ is widely used and well-liked because it not only ensures that you have the right people on the bus, but also that each person is in the right seat.
Best/Worst Sample from 700 Employee Company
The following graphic takes a look at typical judgment scores of a “Best/Worst” sample provided by an organization.
For the AQ to be a valid predictor of employee success, those selected by the organization as “Best” should have strong scores, and those selected as “Worst” should have weak scores. These data points are real and typical.
- This chart shows the very close correlation between the customer-provided “Best/Worst” sample and AQ scores.
- Individuals in the “Best” sample scored 1, 2, or 3—the best possible scores.
- Individuals in the “Worst” sample scored 8, 9, or 10—the worst possible scores.
