Predictability of employee selection methods
In 1988, Michigan State professor John Hunter determined that the typical job interview is only 57% effective in predicting later success in a job, which means that the typical interview is only slightly better than tossing a coin. air.
In the July-August 1999 issue of the Harvard Business Review, an article titled “Hire without Firing” identified that 30% to 50% of all executive-level appointments end in firing or resignation. This turnover statistic is significant when you consider that executive-level positions are not only the most important positions in the organization, but the positions that require the most face-to-face interview time. As such, one would expect that people hired for executive positions would have been the most vetted candidates, yet between one-third and one-half of those appointments have a very short “shelf life.”
The Harvard article and Professor Hunter’s study would certainly lead to the conclusion that better methods must be used to assess not just executive candidates, but all job candidates. The question is, “Which methods are the best?”
In searching for the best methods, I found a 1998 study (Schmidt, FL and Hunter, JE (1998), “The Validity and Utility of Selection Methods in Personnel Research: Practical and Theoretical Implications of 85 Years of Research Findings”, Psychological Bulletin, 124, 262-274), which helped focus my approach to the interview. Based on the meta-analytic findings, this study presented the validity (R) of 19 selection procedures to predict job performance. The most valid procedures for predicting job performance were:
o Work sample tests (R = .54)
o General tests of mental ability (R = .51)
o Structured interviews (R = .51)
o Peer rating (R = .49)
o Job knowledge tests (R = .48)
o Consistency of Training Behavior and Experience (R = .45).
At the lower end of the validity scale were the following procedures:
o Unstructured interviews (R = .38)
o Traditional reference check (R = .26)
o Years of Work Experience (R = .18)
o Years of Education (R = .10)
o Interest (R = .10)
or Age (R = .01).
The best-known conclusion of this 1998 research project is that for companies that hire candidates with no prior on-the-job experience, the most valid predictor of future performance and on-the-job learning is general mental ability (i.e., intelligence or general knowledge). cognitive ability).
A note should be made here about the practical relevance of general mental ability (GMA) in this study. The GMA predictive ability listed above at R = .51 is the validity rating for jobs that fall in the mid-range of complexity. The actual investigation of this study regarding GMA revealed the following validity results for different levels of complexity per job:
o Professional and managerial jobs (R = .58)
o High Level Complex Technical Jobs (R = .56)
o Medium Complexity Jobs (R = .51) (This represents 62% of jobs in the US economy, which includes mid-level white-collar jobs such as white-collar and administrative positions and qualified blue collar).
o Semi-skilled jobs (R = .40)
o Unskilled jobs (R = .23).
These data indicate that GMA becomes an important predictor of job performance as the level of complexity in a job increases. However, other factors such as behaviors, experience, etc. cannot be ruled out. and its importance in helping to predict success in a job.
This study presents solid evidence suggesting that GMA together with positive indicators of other evaluation methods will present a high correlation of success in more complex positions.
The truth is that there is no “silver bullet” selection method and this research does not suggest one method over other methods. As with any decision-making process, a manager should collect as much data as possible about a candidate and then use the candidate’s intuition and experience to make the best possible hiring decision.