Statistical thinking and its impact on operational performance in manufacturing companies: an empirical study

Fabiane Letícia Lizarelli, Jiju Antony, José Carlos Toledo

Research output: Contribution to journalArticle

Abstract

Statistical thinking (ST) is a concept that has been discussed in the literature as principles and concepts disseminated in companies to conduct a statistical approach and it is often associated with using continuous improvement programs (CIPs), such as Six Sigma and Lean Six Sigma since the 1990s. There is a lack of empirical studies in the literature that address this topic concerning the impacts generated by ST in operational performance (OP) of industrial companies, as well as the relationships between ST and CIPs. The paper proposes and tests the hypothesis that the use of ST principles is positively associated with OP in manufacturing companies in the context of CIPs. The empirical research was conducted in a sample of 243 manufacturing companies and used structural equation modelling—partial least squares for data analysis. Positive and statistically significant relationships between ST and OP were observed. ST principles can reduce non-conformities, lower production costs and increase the stability of the process. The findings also support that CIPs have a positive effect on the use of ST principles and a positive effect on OP. This indicates the managerial importance of implementing CIPs, including Six Sigma, Lean Six Sigma, lean and total quality management, and the emphasis on developing mechanisms that operationalize the understanding and practice of the ST principles and statistical techniques for better OP in the manufacturing environment.

Original languageEnglish
JournalAnnals of Operations Research
Early online date24 Sep 2020
DOIs
Publication statusE-pub ahead of print - 24 Sep 2020

Keywords

  • Improvement programs
  • Manufacturing companies
  • Operational performance
  • Partial least squares
  • Statistical techniques
  • Statistical thinking
  • Structural equation modelling

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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