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 Fire” 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 also the positions that require the most face-to-face interview time. As such, one would expect the people hired for executive positions to have been the most vetted candidates, yet between a third and a half of those appointments have very short “shelf lives.”
The Harvard article and Professor Hunter’s study would certainly lead to the conclusion that better methods should be used to evaluate not just executive candidates, but all job candidates. The question is, “Which methods are the best?”
In searching for the best methods, I came across 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 for predicting job performance. The procedures with the greatest validity 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 Behavior Consistency of Training 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 finding from 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 predictive ability of GMA listed above at R = .51 is the validity score for jobs that fall in the middle 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 Works (R = .56)
o Jobs of Medium Complexity (R = .51) (This represents 62% of jobs in the US economy, which includes mid-level white-collar jobs, such as clerical and administrative jobs, 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 strong evidence suggesting that GMA together with positive indicators from other evaluation methods will present a high correlation of success in more complex positions.
The truth is that there is no such thing as a “silver bullet” selection method and this research does not suggest one method over other methods. As with any decision-making process, a manager must 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.