Predictability of Employee Selection Methods

In 1988, Professor John Hunter of Michigan State determined that the typical employment interview is only 57% effective in predicting subsequent success in a job, which means that the typical interview is only slightly better than flipping a coin.

In the July-August 1999 edition of the Harvard Business Review, an article titled “Hiring Without Firing” identified that 30% to 50% of all executive-level appointments end in firing or resignation. This turnover statistic is significant when one considers that executive-level positions are not only the most important positions in the organization, but the positions that command the largest amount of face-to-face interview time. As such, one would expect that people hired for executive positions would have been the most heavily vetted candidates, but yet a third to one half of those appointments have a very short “shelf life.”

The article from Harvard and the study from Professor Hunter would certainly lead one to conclude that better methods need to be employed in assessing, not just executive candidates but, all candidates for employment. The question is, “What methods are the best?”

In searching for the best methods, I found a 1998 study (Schmidt, F.L. and Hunter, J.E. (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 to focus my approach to interviewing. On the basis of meta-analytic findings, this study presented the validity (R) of 19 selection procedures for predicting job performance. The procedures with the highest validity for predicting on-the-job performance were:
o Work Sample Tests (R = .54)
o General Mental Ability Tests (R = .51)
o Structured Interviews (R = .51)
o Peer Rating (R = .49)
o Job Knowledge Tests (R = .48)
o Training & Experience Behavioral Consistency (R = .45).

At the lower end of the validity scale were the following procedures:
o Unstructured Interviews (R = .38)
o Traditional Reference Checking (R = .26)
o Years of Job Experience (R = .18)
o Years of Education (R = .10)
o Interests (R = .10)
o Age (R = .01).

The most well known conclusion of this 1998 research project is that for companies that hire candidates who have no prior experience in the job, the most valid predictor of future performance and on-the-job learning is general mental ability (i.e., intelligence or general cognitive ability).

A note must 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 rating for jobs that rank in the middle range of complexity. The actual research from this study regarding GMA revealed the following validity results for different levels of complexity by position:
o Professional & 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 U.S. economy, which includes mid-level white-collar jobs such as clerical and administrative positions and skilled blue-collar jobs.)
o Semi-skilled Jobs (R = .40)
o Unskilled Jobs (R = .23).

This data indicates that GMA becomes an important predictor of job performance as the level of complexity increases in a position. However, one cannot discount other factors such as behaviors, experience, etc. and their significance in helping to predict success in a job.

This study presents strong evidence to suggest that GMA in conjunction with positive indicators from other assessment methods will present a high correlation of success in higher level complexity positions.

The truth is that there is no “silver bullet” selection method and this research is not suggesting 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 his/her intuition and experience to make the best possible hiring decision.

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