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 flipping a coin. air.
In the July-August 1999 issue of the Harvard Business Review, an article titled “Hiring Without Layoff” identified that 30% to 50% of all executive-level appointments end in layoff 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 take up the most face-to-face interview time. As such, one would expect that the people hired for executive positions would have been the most vetted candidates, but still between a third and a half of those appointments have a very short “useful life”.
The Harvard article and Professor Hunter’s study would undoubtedly lead one to conclude that better methods need to be employed to evaluate not just executive candidates, but all job candidates. The question is: “What 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 usefulness of selection methods in personnel research: practical and theoretical implications of 85 years of research results “, Psychological Bulletin, 124, 262-274), which helped focus my approach to the interview. Based on the meta-analytical 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 Tests of general mental capacity (R = .51)
o Structured interviews (R = .51)
o Peer rating (R = .49)
o Labor knowledge tests (R = .48)
o Coherence of the behavior 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)
o Age (R = .01).
The best-known conclusion from this 1998 research project is that for companies hiring candidates who have no prior work experience, the most valid predictor of future performance and learning on the job is general mental capacity (i.e. intelligence or 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 research of this study regarding GMA revealed the following validity results for different levels of complexity per position:
o Professional and managerial jobs (R = .58)
o Complex high-level technical jobs (R = .56)
o Medium Complexity Jobs (R = .51) (This represents 62% of jobs in the US economy, which includes mid-level clerical jobs such as clerical and clerical positions and skilled manual jobs).
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 position increases. However, other factors such as behaviors, experience, etc. cannot be ruled out. and its importance in helping predict job success.
This study presents solid 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, there is no “miracle” 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 his or her intuition and experience to make the best possible hiring decision.