Creating Job Families Based on Relative Importance versus Absolute Time Spent Ratings,

Abstract

Job classification is an important aspect of personnel psychology that serves as a foundation for a variety of personnel functions. Positions are classified into jobs, which in turn are classified into higher levels called job families. The literature reports a wide range of objectives and potential uses of job families such as job placement, personnel classification, career development and training, and job evaluation for broadbanding and determining pay structures (Pearlman, 1980). Job classification has also been applied to the problem of combining samples across jobs to obtain a large enough sample size for validation studies and to the problem of applying previous validity results to new jobs or situations such as validity generalizations (Pearlman, 1980). Aggregating jobs into higher level job families simplifies personnel work by bringing out the similarities and differences between job attributes so that general statements can be made about broader groups of jobs (Pearlman, 1980). These broader job groupings or families may then serve as the unit of analysis for developing selection tests, training or development plans, or performance standards. For example, instead of developing unique performance standards for every employee in the organization, job analysis data can be used to identify groups of jobs that share similar tasks or competencies. Based on similarity, a common appraisal form may then be developed for each job family or group, thereby reducing the number of appraisal standards needed.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA362086

Entities

People

  • Brian S. O'leary
  • Paul D. Usala
  • Rita Patel

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Applied Psychology
  • Classification
  • Data Sets
  • Factor Analysis
  • Human Resources
  • Job Analysis
  • Management Personnel
  • Personnel Management
  • Personnel Selection
  • Program Management
  • Psychology
  • Q Factor
  • Social Sciences
  • Statistical Analysis
  • Supervisors
  • Surveys
  • Training

Readers

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