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Quality Improvement to Enhance Customer Satisfaction Using Lean Six Sigma (Case Study: XYZ Restaurant)

Authors: Djatmiko, Dimas Naufal; Yuanita Handayati;

Quality Improvement to Enhance Customer Satisfaction Using Lean Six Sigma (Case Study: XYZ Restaurant)

Abstract

Bandung was designated as a national culinary destination city in 2017 by the Ministry of Tourism due to its culinary diversity. The development of food and beverage businesses in Bandung, which increased from 524 in 2020 to 729 in 2021[4], shows that competition in the culinary business is quite intense. XYZ is one of the restaurants that can survive during the Covid-19 pandemic. However, XYZ often experiences complaints from customers regarding the quality of its products and services. Usually, this restaurant can receive 200-300 customers on weekdays and 400-600 customers on weekends. But until now, XYZ only receives 50% of its customers. This research will discuss the improvement of product and service quality using the DMAIC Lean Six Sigma methodology. The research uses primary data by distributing questionnaires to XYZ customers who visited in 2021 to 2023. From the results of the questionnaire, 4 out of 19 sub-variables customers feel that the performance is not good but has a high importance, namely in T1 (Taste), TX1 (Texture), E1 (Empathy), and R1 (Reliability). These four indicators need to be improved so that customers feel satisfied with the services and products provided by XYZ. Based on the main problems from the data obtained, quality improvement efforts that can be made such as employee training and quality control at suppliers. These efforts aim to improve and maintain the quality of XYZ for the long term so that an increase in the number of customers can be achieved, such as 200-300 visitors on weekdays and 400-600 on weekends.

Keywords

Customer Satisfaction, Lean, Restaurant, Six Sigma, SERVQUAL.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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