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Recent research in job classification has focused on the appropriate data analysis model for analyzing the similarities and differences among jobs. In the present research, the data analysis model is held constant, and the type of job analysis data is varied to examine the effect on the resulting job classification decisions. Seven foremen jobs in a chemical processing plant were analyzed using three different levels of job analysis data: task-oriented, worker-oriented, and abilities-oriented. All three sets of data were analyzed using the same hierarchical clustering procedure. Results indicated that the number and type of resulting job clusters was clearly dictated by the type of job analysis data that was used to compare the foremen jobs. Practical implications of these findings are presented. THERE are many purposes for which industrial psychologists must determine the extent of similarities and differences among jobs. In designing selection or promotion systems, for example, the researcher must decide which job groups or job families can be combined for use with a single selection system. In wage and salary administration it is important to know which jobs are similar enough to be administered in the same range. In developing performance appraisal systems the personnel specialist is interested in knowing which jobs are similar enough to be combined and evaluated on the same performance evaluation form.There are two distinct decisions for any job classification problem.

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