Future trends of lean six sigma and process excellence in business operations

Verma, Likhit (2025) Future trends of lean six sigma and process excellence in business operations. World Journal of Advanced Research and Reviews, 26 (2). pp. 4233-4243. ISSN 2581-9615

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Abstract

The evolution of Lean Six Sigma in the digital era represents a transformative shift in operational excellence paradigms across industries. This transition from traditional improvement methodologies to technology-enhanced frameworks has fundamentally altered how organizations identify inefficiencies, implement solutions, and sustain performance gains. The integration of artificial intelligence, hyperautomation, digital twins, and other emerging technologies with established Lean Six Sigma principles creates synergistic capabilities that transcend conventional process excellence limitations. Organizations implementing these integrated approaches experience substantial improvements in efficiency, quality, and responsiveness while developing unprecedented resilience against market disruptions. The emergence of real-time optimization, predictive analytics, and self-learning operational systems has redefined continuous improvement from periodic project-based interventions to embedded capabilities that autonomously sense, analyze, and enhance performance. This technological convergence enables organizations to address previously intractable operational challenges while simultaneously reducing resource requirements and accelerating implementation cycles. As quantum computing, augmented reality, and blockchain technologies mature, the next generation of process excellence will likely evolve toward increasingly autonomous, anticipatory, and interconnected systems that continuously optimize across organizational boundaries.

Item Type: Article
Official URL: https://doi.org/10.30574/wjarr.2025.26.2.2088
Uncontrolled Keywords: Lean Six Sigma; Artificial Intelligence; Hyperautomation; Digital Twin; Process Excellence
Depositing User: Editor WJARR
Date Deposited: 20 Aug 2025 11:54
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/3696