The Quality Quotient: A Tool for Measuring Organizational Quality Performance.

Abstract

This research studied the relationship between hypothesized predictors of quality performance and a readily available performance indicator, the Oregon Productivity Matrix Score. The authors attempted to develop a formula for predicting quality performance, the Quality Quotient, as well as testing the discriminability of the predictors. To gather information, a survey developed specifically for this research was sent to each of the five Air Force Air Logistic Centers. The data were analyzed primarily using multiple regression analysis and discriminant analysis. The results of these analyses highlighted the ability of specific predictors for both prediction and discrimination using the Oregon Productivity score (standardized as a Z-score) as a dependent variable. In addition to providing strong predictive ability, two of the regression formula beta coefficients surprised the researchers by having a negative effect on the dependent variable (although stated to have a positive effect by quality experts). Survey participants who were members of the top performing organizations believed that their organizations' data collection systems were more complicated than necessary, and that statistical techniques should only be used by experts in the Quality field. Keywords: Quality, Productivity, Quality control, Quality assurance, Theses.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1989
Accession Number
ADA215373

Entities

People

  • Edward J. Hayman
  • Ruth E. Schneider

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Data Analysis
  • Data Mining
  • Data Science
  • Discriminant Analysis
  • Engineering
  • Industrial Engineering
  • Information Processing
  • Information Science
  • Knowledge Management
  • Logistics
  • Organizational Structure
  • Quality Control
  • Regression Analysis
  • Statistics
  • Surveys

Fields of Study

  • Education

Readers

  • Organizational Process Management (OPM).
  • Psychometric Testing or Psychological Assessment.
  • Regression Analysis.