Lean Six Sigma implementation: modelling the interaction among the enablers

Abstract

Lean Six Sigma (LSS) methodology has been acquiring a prominent position in organisations. The aim of this study is to demonstrate an approach to LSS implementation in organisations using the development of a hypothetical model based on interpretive structural modelling (ISM) and fuzzy Matriced Impacts Croisés Multiplication Appliquée á un Classement (fuzzy MICMAC) analysis phenomenon. Seventy Lean Six Sigma enablers (LSSEs) have been identified through extensive literature review and out of which 40 most important LSSEs were finalised through opinions of experts both from industry and academia. Furthermore, the valuable expert opinions have been applied to determine contextual relationships between these significant LSSEs and a hierarchical model has been created based on an ISM. The fuzzy MICMAC analysis has also been utilised to classify the enablers based on the dependence and driving power, and validate the created ISM-based model. The developed hierarchical model will assist to understand interrelationships and interdependencies among the identified LSSEs. Having high driving and low dependence power, the LSSEs have strategic significance because of their driving character. On the other hand, having high dependence and low driving power, LSSEs are more performance orientated. The mutual influence, driving and dependence power of LSSEs render valuable information to top management to distinguish between independent and dependent LSSEs. An organisation desiring of adopting LSS may get benefited by the understanding of LSSEs and their interactions.

Keywords:

• Lean Six Sigma
• interpretive structural modelling
• fuzzy MICMAC
• Lean Six Sigma enablers

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Shruti J. Raval

S. J. Raval has about 10 years of teaching experience at graduate and post graduate levels. She has completed her graduation in Production Engineering and post-graduation in Advance Manufacturing Systems. She is pursuing her Ph.D. in the area of Lean Six Sigma from Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India. Her interests of areas are Lean Six Sigma, Advanced Manufacturing and Optimisation.

Ravi Kant

Dr. Ravi Kant is Assistant Professor at the Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India. His areas of research interest include Knowledge Management, Operations & Supply Chain, Lean & Six Sigma. He has about 11 years of experience in industry, teaching and research. He has co-authored more than 150 research papers in international journals and conferences and three books.

Ravi Shankar

 Dr. Ravi Shankar is the ‘Amar S. Gupta Chair Professor of Decision Science’ at Department of Management Studies, Indian Institute of Technology (IIT) Delhi, India. He is also the Honorary Visiting Professor of Decision Science at School of Economics and Management, Loughborough University, UK. His areas of interest include Decision Sciences, Business Analytics and Big Data, Operations and Supply Chain Management, Sustainable Freight Transportation, Project Management, Total Quality Management and Six Sigma, Strategic Technology Management, etc. He has co-authored more than 400 research papers and six books.