Enhancing the journey to six sigma excellence: identifying critical success factors

Anthony Bagherian, Mark Gerschon and Sunil Kumar

International Journal of Productivity and Performance Management, 2024, vol. 74, issue 3, 761-792

Abstract: Purpose - Numerous attempts at installing Six Sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. Research has highlighted that a considerable number of corporate Six Sigma initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions. Design/methodology/approach - To validate the influence of CSFs on Six Sigma accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. The analysis focused on 260 completed questionnaires, and statistical methods including SEM, EFA, and CFA were utilized for data analysis. Findings - The study acknowledged four essential components of CSFs that are imperative for sustaining the success of Six Sigma (SS): (1) Competence of Belt System employees; (2) Project management skills; (3) Organizational economic capability; and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of Six Sigma’s success. Practical implications - The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their Six Sigma practices. Originality/value - The investigation’s originality lies in its contribution to assessing critical success factors in Six Sigma deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

Keywords: Six sigma; Critical success factors; Structural equation modeling (SEM); Survey; EFA; CFA; Vehicle industry (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijppmp:ijppm-08-2023-0446

DOI: 10.1108/IJPPM-08-2023-0446

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