Weighted Application Blank Scoring System - Essay Example

Weighted Application Blank Scoring System of the of the Weighted Application Blank Scoring System Q. How is the scoring system developed for a weighted application blank? Provide an example of how this works. The weighted application blank is generally developed with the help of industrial psychologists that scores candidates on desired attributes. For example if it is desired to reduce turnover on a specific job, we will first have to choose the appropriate criterion, specify groups of related characteristics, specify item response categories, assign them weights, prepare the application blanks, decide on a cutoff point for selection and finally administer them to subjects to test their validity and reliability (Dawson et al.

, 1984, 120). Of course the real test would be if turnover had really reduced on the job and by what percentage after the correctional measures were employed. Measures that Can Predict Employee TurnoverScoringCRITERION Yes No Not Sure Feeling Undervalued/ Unappreciated at Work 3 2 1Inadequacy of Time off/ Vacation 3 2 1Low Salary compared to Workload 3 2 1Low Salary compared to Competing Organizations 3 2 1Workload needs to be distributed more fairly 3 2 1Maximum Score Possible 15 10 5One can see here that if a cutoff point of 10 points is established, and the majority of scores are above 10 we can say that these factors really have an impact on employee turnover.

To note which factors are the most important we can similarly rate each factor by calculating the highest score given to a particular criterion as well as the number of responses that selected it. In this way it is hoped that turnover can be reduced in the organization. Weighted application blanks have long been used successfully in the selection of employees with appreciable results. ReferencesDawson, D.B; King, A.S and Catalenello, R.F.(1984). Developing and Using Weighted Application Blanks: An Experiential Exercise.

Developments in Business Simulation and Experiential Learning, Volume 11, pp 120-123.