In today’s data-driven business environment, over 90% of large companies use pre-employment exams to evaluate potential employees. While many tests are tied to objectively measurable skills, abilities and talents, many more are often seen as more subjective – personality, fit, culture, and integrity.
The risks of these tests are obvious – the subjectivity can lead to misunderstood results, invalid conclusions, or even discrimination. Yet why do these types of pre-employment exams persist? Because they offer information companies seek. Personality exams and cultural assessments highlight potential employee traits in order to predict the likelihood of their fitting into a company’s culture, as well as to a specific role within that company.
Selecting the Right Exam
Which candidates offer the greatest potential benefit to a company? Which will be high performers? Which high performers will remain at the company the longest? There is an entire subset of statistical analysis given to properly and scientifically evaluating employee/employer fit. Data scientists have developed algorithms that offer reliable, consistent results proven to correlate to increased employee retention, and higher performance.
When choosing a pre-employment exam, it is critical to pick an assessment that has been validated by accurate scientific testing. Past popular tests such as handwriting or Rorschach (inkblot) tests have been proven to have near-zero reliability. Even today’s popular Myers-Briggs exam has a legion of critics, and applying its generic results to a specific company or position can be a struggle at best. Accurate options do exist, however.
TalentAIM is the Perfect Pre Employment Exam
New discoveries in the field of statistical analysis have resulted in sculpted tools centering on employment science.
Reliability is also a key criteria. For a test to be reliable, a person’s score should be nearly the same each time they take it. If a potential employee takes the test multiple times and receives widely varying scores, the reliability is likely suspect. Without consistency, the results of a test have little value in predicting a potential employee’s performance or tenure.
For the most accurate results to a specific company or position, incumbent employees should also be evaluated, revealing what traits lead to longer (or shorter) tenures, and greater (or lesser) productivity. By combining the company-specific data with a pre employment exam for new employees, accurate assessments can cut wasted time and money, thus increasing employee retention and performance. The data can also give a psychometric snapshot insight to employee motivations, useful in future evaluations and gauging of potential internal advancement.
When analysis is correctly applied and interpreted, key questions can be answered. Companies can and do save money in the hiring process utilizing data-driven evaluation. We call this talent acquisition analytics.
Career employment data scientists offer validated algorithms that accurately, consistently, and reliably assess both company and candidate personalities. Hiring in alignment to the mathematical scores, their proprietary software produces have increased retention rates by more than 12% and improved performance by up to 15%. Their method combines a services engagement coupled with a SaaS based tool that provides predictive analytics for candidates fit to role and culture.
By using a 20-minute online survey, important insights can be gained that can inform decisions about future hires. Within seconds, large groups of candidates can be depicted in user-friendly and accurate reports.
How TalentAIM Works
TalentAIM uses scientific survey-based analysis to give employers results that provide huge cost savings in rapid candidate analytics, and financial gains due to increases employee retention and engagement. It combines a services engagement coupled with a SaaS based tool that provides predictive analytics for candidates fit to role and culture.