What Drives Successful Six Sigma Implementation? A Data-Driven Multidisciplinary Analysis

Charles Chikwendu Okpala¹ and Chukwudi Emeka Udu²

¹ Professor: Industrial/Production Engineering Department, Nnamdi Azikiwe University, Awka, Nigeria.

² Researcher: Industrial/Production Engineering Department, Nnamdi Azikiwe University, Awka, Nigeria.    

Abstract

Despite its widespread adoption across manufacturing and service industries, Six Sigma has, over the years, continued to produce uneven implementation outcomes, which raises critical questions about the factors that truly drive its success in contemporary organizations. This study investigates the multidimensional determinants of successful Six Sigma implementation using a large, cross-industry dataset and a novel data-driven analytical approach. Drawing on insights from operations management, organizational behavior, data analytics, and sustainability science, the study integrates structural equation modeling with explainable machine learning to examine both causal relationships and nonlinear interaction effects. With the application of data from 412 organizations across multiple sectors and countries, the results reveal that leadership and strategic alignment, data and analytics maturity, human capital capability, and sustainability integration jointly explain a substantial proportion of variation in Six Sigma performance outcomes. Importantly, Six Sigma initiatives that explicitly incorporate sustainability objectives deliver significantly higher financial returns, stronger operational improvements, and measurable reductions in energy and material intensity when compared to traditional cost-focused projects. Methodologically, the study advances the Six Sigma literature through the demonstration of the value of the combination of causal and predictive analytics in the analysis of complex socio-technical systems. Substantively, it reframes Six Sigma as a strategic, data-driven mechanism for sustainable value creation, rather than a narrowly defined quality improvement tool. The findings offer actionable insights for managers, policymakers, and researchers who are aiming at aligning operational excellence with long-term sustainability goals.      

Keywords: Six Sigma, Sustainability performance, Data-driven analytics, Operational excellence, Organizational capability, Explainable machine learning, Process improvement  

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