INFORMATION RETRIEVAL IN THE PERSONNEL DEPARTMENT. A SURVEY OF METHODS USED IN SCIENTIFIC AND ENGINEERING ORGANIZATIONS.

Abstract

The present study was undertaken to determine the approach scientific and engineering organizations are taking to automate personnel records, the nature of such automated systems, the degree of success which has been encountered, and the efforts made toward developing a structure of technical skills. Questionnaires on automation and information retrieval in the personnel department were sent to 256 organizations. One hundred seven firms responded, 95 with completed questionnaires. After the results were summarized, the following conclusions were drawn: (1) An actual need for automation of personnel records was first seen as a firm approached 500 professional employees. (2) As continued growth occurred (up to 1000 professional employees), the need for automation was confirmed. However, automation actually was employed as a means for simplifying clerical tasks for each area of personnel separately, and these automated subsystems were not integrated into one working record system. (3) After clerical problems of preparing statistical reports were solved, in the 100 to 1500 group, firms began to load more detailed information about each employee into the system so that comprehensive lists of employees could be provided. (4) In the 1500 to 2000 group, all of the responding firms relied on automated records to some extent, even though the sample of firms in this category was very small. (5) In firms with 2000 or more professional employees, there was a trend to integrate several automated subsystems of personnel records. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1964
Accession Number
AD0601488

Entities

People

  • Leslie A. Hubbard
  • Olinda Elliott
  • Robert A. Dickmann

Organizations

  • Johns Hopkins University Applied Physics Laboratory

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Adaptive Control Systems
  • Adaptive Systems
  • Automation
  • Control Systems
  • Control Systems Engineering
  • Cooperation
  • Engineering
  • Information Retrieval
  • Interdisciplinary Science
  • Questionnaires
  • Surveys
  • Systems Engineering
  • Systems Science

Fields of Study

  • Business

Readers

  • Economics
  • Instructional Design and Training Evaluation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy