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Management Model Applying Lean Six Sigma to Improve the Performance of an SME in the Professional Services Sector.

Authors :
Díaz Guevara, Axel
Perez Reyes, Mariel
Chavez-Ugaz, Rafael
Source :
Proceedings of the International Conference on Industrial Engineering & Operations Management; 2/12/2024, p560-572, 13p
Publication Year :
2024

Abstract

The concepts of Lean Manufacturing and Six Sigma have been applied in manufacturing companies with greater frequency. However, there are few records of its implementation in companies in the service sector. This sector in Peru represents more than 50.6% of the country's Gross Domestic Product and it is composed mainly of small and medium-sized enterprises (SMEs). Nevertheless, this kind of businesses are characterized by having low productivity, lack of organization and monitoring of performance indicators to make good decisions. Therefore, different techniques are required to maintain their efficiency and productivity over time to meet the expectations of the consumers. In this research, the objective is to propose a management model by applying Lean Six Sigma in order to improve the performance of an SME in the professional services sector. Through the DMAIC process, a diagnosis of the company was carried out, finding the root causes of its main problems, Lean tools such as 5s and virtual Kanban were applied in a pilot test in the organization. After implementation, 100% efficiency was obtained, a productivity improvement of 75.56% and a decrease in order delivery time of 42.30%. Finally, the pilot test was validated using a statistical analysis of variance test and demonstrated consistency with the management model applying lean six sigma. This work contributes to practical knowledge with the application of a lean six sigma tool model and to be expanded in future work in companies in the service sector. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21698767
Database :
Complementary Index
Journal :
Proceedings of the International Conference on Industrial Engineering & Operations Management
Publication Type :
Conference
Accession number :
177833245
Full Text :
https://doi.org/10.46254/AN14.20240136