Recibido: 10/01/2026 Aprobado:15/02/2026
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DOI: https://doi.org/10.70208/3007.8245.v6.n1.355
Process Optimization and Its Impact on Customer
Satisfaction in an Automotive After-Sales Service Department
Gabriel Téllez Muñoz
te463651@uaeh.edu.mx
https://orcid.org/0009-0006-8252-4132
Universidad Autónoma del Estado de Hidalgo
México
Emilio Antonio Gómez Alvarado
go401358@uaeh.edu.mx
https://orcid.org/0009-0007-6552-2642
Universidad Autónoma del Estado de Hidalgo
México
Erick Uriel Morales Cruz
erick_morales@uaeh.edu.mx
https://orcid.org/0009-0008-2071-9713
Universidad Autónoma del Estado de Hidalgo
México
Lidia Ramírez Quintanilla
lidia_ramirez@uaeh.edu.mx
https://orcid.org/0009-0006-6270-0469
Universidad Autónoma del Estado de Hidalgo
México
Estella María Esparza Zúñiga
estella_esparza@uaeh.edu.mx
https://orcid.org/0009-0008-2603-1311
Universidad Autónoma del Estado de Hidalgo
México
ABSTRACT
An automotive dealership conducted a study after experiencing a 19% decrease in customer
satisfaction over a three-month period. The problem was analyzed using a Pareto diagram, which
identified the after-sales service process as the primary source of dissatisfaction, mainly due to
excessive waiting times. A quasi-experimental pretest–posttest design was applied to evaluate the
impact of the intervention. The study sample consisted of services performed on an average of 30
vehicles per month. To address the problem, the PDCA and SMART methodologies were implemented
and complemented with a continuous time-and-motion study, which revealed a bottleneck in the
vehicle washing stage. As corrective actions, follow-up procedures were standardized through an APS
monitoring format, schedules were reorganized, personnel performance was evaluated through key
performance indicators (KPIs), and an additional washer was hired. As a result, waiting times were
significantly reduced, productivity in the washing process doubled, and the Customer Satisfaction Index
(CSI) increased from 77.8% in January to 95.6% during the following quarter. These results demonstrate
that process optimization and systematic monitoring can significantly enhance operational efficiency
and customer satisfaction in automotive service departments.
Keywords: Customer satisfaction, productivity, time management, process optimization, time and
motion study
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Optimización de procesos y su impacto en la satisfacción del cliente en un
departamento de servicio posventa automotriz
RESUMEN
Un concesionario automotriz realizó un estudio tras experimentar una disminución del 19 % en la
satisfacción del cliente durante un período de tres meses. El problema fue analizado mediante un
diagrama de Pareto, el cual identificó el proceso de servicio posventa como la principal fuente de
insatisfacción, principalmente debido a tiempos de espera excesivos. Se aplicó un diseño cuasi
experimental de pretest–postest para evaluar el impacto de la intervención. La muestra del estudio
estuvo conformada por servicios realizados a un promedio de 30 vehículos por mes. Para abordar el
problema, se implementaron las metodologías PDCA y SMART, complementadas con un estudio
continuo de tiempos y movimientos, el cual reveló un cuello de botella en la etapa de lavado de
vehículos. Como acciones correctivas, se estandarizaron los procedimientos de seguimiento mediante
un formato de monitoreo APS, se reorganizaron los horarios, se evaluó el desempeño del personal a
través de indicadores clave de desempeño (KPI) y se contrató un lavador adicional. Como resultado,
los tiempos de espera se redujeron significativamente, la productividad en el proceso de lavado se
duplicó y el Índice de Satisfacción del Cliente (CSI) aumentó de 77.8 % en enero a 95.6 % durante el
trimestre siguiente. Estos resultados demuestran que la optimización de procesos y el monitoreo
sistemático pueden mejorar significativamente la eficiencia operativa y la satisfacción del cliente en
los departamentos de servicio automotriz.
Palabras clave: satisfacción del cliente, productividad, gestión del tiempo, optimización de procesos,
estudio de tiempos y movimientos
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Optimización de procesos y su impacto en la satisfacción del cliente en un
departamento de servicio posventa automotriz
RESUMEN
Un concesionario automotriz realizó un estudio tras experimentar una disminución del 19 % en la
satisfacción del cliente durante un período de tres meses. El problema fue analizado mediante un
diagrama de Pareto, el cual identificó el proceso de servicio posventa como la principal fuente de
insatisfacción, principalmente debido a tiempos de espera excesivos. Se aplicó un diseño cuasi
experimental de pretest–postest para evaluar el impacto de la intervención. La muestra del estudio
estuvo conformada por servicios realizados a un promedio de 30 vehículos por mes. Para abordar el
problema, se implementaron las metodologías PDCA y SMART, complementadas con un estudio
continuo de tiempos y movimientos, el cual reveló un cuello de botella en la etapa de lavado de
vehículos. Como acciones correctivas, se estandarizaron los procedimientos de seguimiento mediante
un formato de monitoreo APS, se reorganizaron los horarios, se evaluó el desempeño del personal a
través de indicadores clave de desempeño (KPI) y se contrató un lavador adicional. Como resultado,
los tiempos de espera se redujeron significativamente, la productividad en el proceso de lavado se
duplicó y el Índice de Satisfacción del Cliente (CSI) aumentó de 77.8 % en enero a 95.6 % durante el
trimestre siguiente. Estos resultados demuestran que la optimización de procesos y el monitoreo
sistemático pueden mejorar significativamente la eficiencia operativa y la satisfacción del cliente en
los departamentos de servicio automotriz.
Palabras clave: satisfacción del cliente, productividad, gestión del tiempo, optimización de procesos,
estudio de tiempos y movimientos
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INTRODUCTION
The quality of repair, maintenance, and after-sales services can be considered one of the fundamental
pillars for achieving customer loyalty in the automotive sector, whether in a dealership or in an
independent repair shop. In a highly competitive environment in which different companies offer
products with similar technological features and performance, differentiation and customer preference
are increasingly determined by customer experience, both during the purchase process and during the
provision of maintenance or repair services.
For this reason, after-sales service, which includes preventive maintenance, corrective repairs, and
warranty claims—has become an essential component of the overall value offered by automotive
companies. These services contribute directly to customer satisfaction and loyalty by providing a
support experience that differentiates the company from its competitors and promotes long-term
customer relationships (Kotler & Keller, 2016).
Specialized literature in quality management has consistently demonstrated that customer satisfaction
is a critical indicator of organizational performance and long-term success (Hernandez, 2025).
According to Parasuraman et al. (1998), service quality can be defined as the gap between customer
expectations and their perception of the service received. In automotive service environments, this gap
tends to increase when communication between service providers and customers is inadequate,
particularly with regard to delivery times and service progress.
A realistic delivery commitment must therefore be established while considering all operational factors
that may affect service completion, as well as any potential additional repairs that could generate extra
costs for the customer. Consequently, customer experience management involves not only the
technical execution of mechanical work but also the coordination of all operational stages, from vehicle
reception to final delivery, ensuring transparency and reliability throughout the entire service process.
From a theoretical perspective, this study is framed within the philosophy of Total Quality Management
(TQM), which emphasizes the importance of involving all organizational personnel in continuous
process improvement. According to Oakland (2014), individual actions within an organization directly
influence the overall performance of products and services. TQM integrates three fundamental
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INTRODUCTION
The quality of repair, maintenance, and after-sales services can be considered one of the fundamental
pillars for achieving customer loyalty in the automotive sector, whether in a dealership or in an
independent repair shop. In a highly competitive environment in which different companies offer
products with similar technological features and performance, differentiation and customer preference
are increasingly determined by customer experience, both during the purchase process and during the
provision of maintenance or repair services.
For this reason, after-sales service, which includes preventive maintenance, corrective repairs, and
warranty claims—has become an essential component of the overall value offered by automotive
companies. These services contribute directly to customer satisfaction and loyalty by providing a
support experience that differentiates the company from its competitors and promotes long-term
customer relationships (Kotler & Keller, 2016).
Specialized literature in quality management has consistently demonstrated that customer satisfaction
is a critical indicator of organizational performance and long-term success (Hernandez, 2025).
According to Parasuraman et al. (1998), service quality can be defined as the gap between customer
expectations and their perception of the service received. In automotive service environments, this gap
tends to increase when communication between service providers and customers is inadequate,
particularly with regard to delivery times and service progress.
A realistic delivery commitment must therefore be established while considering all operational factors
that may affect service completion, as well as any potential additional repairs that could generate extra
costs for the customer. Consequently, customer experience management involves not only the
technical execution of mechanical work but also the coordination of all operational stages, from vehicle
reception to final delivery, ensuring transparency and reliability throughout the entire service process.
From a theoretical perspective, this study is framed within the philosophy of Total Quality Management
(TQM), which emphasizes the importance of involving all organizational personnel in continuous
process improvement. According to Oakland (2014), individual actions within an organization directly
influence the overall performance of products and services. TQM integrates three fundamental
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principles: customer focus, continuous improvement, and employee involvement. Applying these
principles to the after-sales service area aims to transform organizational culture from a reactive
approach to a proactive system in which each employee assumes responsibility for the quality of
service delivered.
This research also incorporates elements of the Lean Service approach derived from the Toyota
Production System, which focuses on eliminating waste and reducing activities that do not add value
to the customer. In practical terms, this approach involves minimizing idle time, rework, and delays
caused by insufficient coordination among operational areas. For this reason, one of the specific
objectives of this study was to analyze the distribution of operational time across the different stages of
the service process, including vehicle reception, mechanical work, washing, and detailing, in order to
identify opportunities for process improvement.
In the automotive industry, particularly in Mexico, customer satisfaction has become a critical
performance indicator required by automotive manufacturers and corporate standards. Dealerships are
therefore required not only to meet operational targets related to vehicle sales or service profitability
but also to maintain specific satisfaction indicators such as the Customer Satisfaction Index (CSI) for
service operations and the Sales Satisfaction Index (SSI) for vehicle purchases. These indicators are
periodically evaluated to determine whether dealerships qualify for incentives, performance bonuses,
or certification programs.
Within this context, the automotive dealership analyzed in this study, located in Tulancingo de Bravo,
Hidalgo, experienced a 19% decrease in the Customer Satisfaction Index (CSI) during the October
2024 to January 2025 period. This decline directly affected the dealership’s ability to achieve the
performance objectives established by the automotive brand. The reduction in customer satisfaction
not only compromises operational performance indicators but also increases the risk of losing repeat
customers and limits the acquisition of new clients, generating estimated economic losses exceeding
50,000 Mexican pesos.
Addressing this issue is particularly important because after-sales services represent not only a
significant source of revenue for automotive dealerships but also a key element in building long-term
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principles: customer focus, continuous improvement, and employee involvement. Applying these
principles to the after-sales service area aims to transform organizational culture from a reactive
approach to a proactive system in which each employee assumes responsibility for the quality of
service delivered.
This research also incorporates elements of the Lean Service approach derived from the Toyota
Production System, which focuses on eliminating waste and reducing activities that do not add value
to the customer. In practical terms, this approach involves minimizing idle time, rework, and delays
caused by insufficient coordination among operational areas. For this reason, one of the specific
objectives of this study was to analyze the distribution of operational time across the different stages of
the service process, including vehicle reception, mechanical work, washing, and detailing, in order to
identify opportunities for process improvement.
In the automotive industry, particularly in Mexico, customer satisfaction has become a critical
performance indicator required by automotive manufacturers and corporate standards. Dealerships are
therefore required not only to meet operational targets related to vehicle sales or service profitability
but also to maintain specific satisfaction indicators such as the Customer Satisfaction Index (CSI) for
service operations and the Sales Satisfaction Index (SSI) for vehicle purchases. These indicators are
periodically evaluated to determine whether dealerships qualify for incentives, performance bonuses,
or certification programs.
Within this context, the automotive dealership analyzed in this study, located in Tulancingo de Bravo,
Hidalgo, experienced a 19% decrease in the Customer Satisfaction Index (CSI) during the October
2024 to January 2025 period. This decline directly affected the dealership’s ability to achieve the
performance objectives established by the automotive brand. The reduction in customer satisfaction
not only compromises operational performance indicators but also increases the risk of losing repeat
customers and limits the acquisition of new clients, generating estimated economic losses exceeding
50,000 Mexican pesos.
Addressing this issue is particularly important because after-sales services represent not only a
significant source of revenue for automotive dealerships but also a key element in building long-term
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customer loyalty. According to Heskett, Sasser, and Schlesinger (2008), the service-profit chain
establishes a direct relationship between customer satisfaction and organizational profitability, as
satisfied customers are more likely to make repeat purchases, recommend the company to others, and
contribute to business stability.
The main objective of this study is to evaluate the effect of optimizing the after-sales service process
on improving the Customer Satisfaction Index (CSI) in an automotive dealership through the
implementation of continuous improvement methodologies.
To achieve this objective, the following specific goals were established:
• To analyze the operational performance of the after-sales service process through a time-and-
motion study to identify operational bottlenecks.
• To implement improvement strategies based on the PDCA and SMART methodologies, as well
as additional quality tools aimed at reducing waiting times.
• To compare customer satisfaction indicators and operational process times before and after the
intervention in order to determine the impact of the implemented actions.
Despite the importance of after-sales service in the automotive industry, many dealerships face
operational inefficiencies that negatively affect customer satisfaction levels, so this article presents the
methodologies applied to address the identified problem. Using time-and-motion analysis and quality
management tools, several internal operational factors that negatively affected customer satisfaction
were identified. The relevance of this research lies in the replicability of the proposed solution, as it
addresses systemic operational issues commonly observed in after-sales service processes across
multiple automotive dealerships with similar organizational structures.
The objective of this study is to evaluate the impact of process optimization strategies on customer
satisfaction in the after-sales service department of an automotive dealership. As a result, this study
provides a dual contribution. On the one hand, it offers empirical evidence regarding the effectiveness
of quality management tools in the automotive service sector. On the other hand, it proposes a
replicable operational improvement model that may be applied in other dealerships facing similar
service management challenges. Improving customer satisfaction not only enhances operational
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customer loyalty. According to Heskett, Sasser, and Schlesinger (2008), the service-profit chain
establishes a direct relationship between customer satisfaction and organizational profitability, as
satisfied customers are more likely to make repeat purchases, recommend the company to others, and
contribute to business stability.
The main objective of this study is to evaluate the effect of optimizing the after-sales service process
on improving the Customer Satisfaction Index (CSI) in an automotive dealership through the
implementation of continuous improvement methodologies.
To achieve this objective, the following specific goals were established:
• To analyze the operational performance of the after-sales service process through a time-and-
motion study to identify operational bottlenecks.
• To implement improvement strategies based on the PDCA and SMART methodologies, as well
as additional quality tools aimed at reducing waiting times.
• To compare customer satisfaction indicators and operational process times before and after the
intervention in order to determine the impact of the implemented actions.
Despite the importance of after-sales service in the automotive industry, many dealerships face
operational inefficiencies that negatively affect customer satisfaction levels, so this article presents the
methodologies applied to address the identified problem. Using time-and-motion analysis and quality
management tools, several internal operational factors that negatively affected customer satisfaction
were identified. The relevance of this research lies in the replicability of the proposed solution, as it
addresses systemic operational issues commonly observed in after-sales service processes across
multiple automotive dealerships with similar organizational structures.
The objective of this study is to evaluate the impact of process optimization strategies on customer
satisfaction in the after-sales service department of an automotive dealership. As a result, this study
provides a dual contribution. On the one hand, it offers empirical evidence regarding the effectiveness
of quality management tools in the automotive service sector. On the other hand, it proposes a
replicable operational improvement model that may be applied in other dealerships facing similar
service management challenges. Improving customer satisfaction not only enhances operational
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performance indicators but also strengthens the perceived value of the brand and supports the long-
term sustainability of the dealership as a business organization.
METHODOLOGY
The study was conducted using a quantitative applied research approach, complemented by
descriptive qualitative elements aimed at optimizing processes within the automotive after-sales
service area. The quantitative approach enabled the measurement of operational times and
movements within the service process, the establishment of performance indicators, and the evaluation
of the impact of the corrective actions implemented. The qualitative component allowed for the
analysis of customer and employee perceptions, as well as cultural and organizational factors that
influence service delivery.
The methodological framework of this research is based on the application of quality management
tools and continuous improvement methodologies that have proven effective in both industrial and
service environments. Among these tools, the time-and-motion study, process simulation, Ishikawa
cause-and-effect analysis, and the PDCA cycle (Plan, Do, Check, Act) proposed by Deming played a
particularly important role. These tools facilitated the identification of operational bottlenecks, the
optimization of resources, and the establishment of process controls aimed at improving customer
satisfaction.
The research design followed a quasi-experimental pretest–posttest structure without a control group,
in which operational results and satisfaction indicators were evaluated before and after the
implementation of improvement strategies. This design allowed for the observation of changes in
operational performance and customer satisfaction without the need for a separate control group.
Because the intervention affected the entire operational system, the unit of analysis was organizational
rather than individual.
The population consisted of all vehicles serviced within the dealership’s after-sales department during
the study period. Prior to the intervention, the service department processed an average of 10 to 14
vehicles per day. After the implementation of the optimization strategies, the average increased to 21
vehicles per day.
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performance indicators but also strengthens the perceived value of the brand and supports the long-
term sustainability of the dealership as a business organization.
METHODOLOGY
The study was conducted using a quantitative applied research approach, complemented by
descriptive qualitative elements aimed at optimizing processes within the automotive after-sales
service area. The quantitative approach enabled the measurement of operational times and
movements within the service process, the establishment of performance indicators, and the evaluation
of the impact of the corrective actions implemented. The qualitative component allowed for the
analysis of customer and employee perceptions, as well as cultural and organizational factors that
influence service delivery.
The methodological framework of this research is based on the application of quality management
tools and continuous improvement methodologies that have proven effective in both industrial and
service environments. Among these tools, the time-and-motion study, process simulation, Ishikawa
cause-and-effect analysis, and the PDCA cycle (Plan, Do, Check, Act) proposed by Deming played a
particularly important role. These tools facilitated the identification of operational bottlenecks, the
optimization of resources, and the establishment of process controls aimed at improving customer
satisfaction.
The research design followed a quasi-experimental pretest–posttest structure without a control group,
in which operational results and satisfaction indicators were evaluated before and after the
implementation of improvement strategies. This design allowed for the observation of changes in
operational performance and customer satisfaction without the need for a separate control group.
Because the intervention affected the entire operational system, the unit of analysis was organizational
rather than individual.
The population consisted of all vehicles serviced within the dealership’s after-sales department during
the study period. Prior to the intervention, the service department processed an average of 10 to 14
vehicles per day. After the implementation of the optimization strategies, the average increased to 21
vehicles per day.
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For the measurement of customer satisfaction, monthly averages of the Customer Satisfaction Index
(CSI) were calculated based on a sample of 30 surveys administered to customers who received
service. For the comparative analysis, three monthly measurements were considered prior to the
intervention (November, December, and January) and three measurements after the intervention
(February, March, and April), forming two temporal groups (n₁ = 3; n₂ = 3).
With regard to personnel, the operational sample included four mechanical technicians, two washers,
and three Professional Service Advisors (APS), who participated in diagnostic activities, service follow-
up, and the implementation of improvement strategies. This selection followed a purposive sampling
approach, since the individuals involved were directly responsible for the operational processes under
analysis.
The independent variables of the study consisted of the implementation of washing process
optimization strategies, the PDCA improvement cycle, SMART goal planning, the redistribution of
operational workloads, and the standardization of service procedures. The primary dependent variable
was the monthly average of the Customer Satisfaction Index (CSI), expressed as a percentage.
Secondary dependent variables included the average number of vehicles serviced per day and the
operational processing times within the service workflow.
Finally, descriptive statistics (mean and standard deviation) were used to summarize the monthly CSI
averages for both the pre- and post-intervention periods. To evaluate the difference between the two
groups, an independent samples Student’s T-test was applied using a significance level of α = 0.05. This
analysis made it possible to determine whether the increase in CSI observed after process optimization
was statistically significant.
RESULTS AND DISCUSSION
General Results
The initial diagnosis showed that the main factors associated with customer dissatisfaction were delays
in delivery times and the lack of effective communication during the service process. Through the time
and motion study conducted between January 30 and February 6, it was identified that the greatest
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For the measurement of customer satisfaction, monthly averages of the Customer Satisfaction Index
(CSI) were calculated based on a sample of 30 surveys administered to customers who received
service. For the comparative analysis, three monthly measurements were considered prior to the
intervention (November, December, and January) and three measurements after the intervention
(February, March, and April), forming two temporal groups (n₁ = 3; n₂ = 3).
With regard to personnel, the operational sample included four mechanical technicians, two washers,
and three Professional Service Advisors (APS), who participated in diagnostic activities, service follow-
up, and the implementation of improvement strategies. This selection followed a purposive sampling
approach, since the individuals involved were directly responsible for the operational processes under
analysis.
The independent variables of the study consisted of the implementation of washing process
optimization strategies, the PDCA improvement cycle, SMART goal planning, the redistribution of
operational workloads, and the standardization of service procedures. The primary dependent variable
was the monthly average of the Customer Satisfaction Index (CSI), expressed as a percentage.
Secondary dependent variables included the average number of vehicles serviced per day and the
operational processing times within the service workflow.
Finally, descriptive statistics (mean and standard deviation) were used to summarize the monthly CSI
averages for both the pre- and post-intervention periods. To evaluate the difference between the two
groups, an independent samples Student’s T-test was applied using a significance level of α = 0.05. This
analysis made it possible to determine whether the increase in CSI observed after process optimization
was statistically significant.
RESULTS AND DISCUSSION
General Results
The initial diagnosis showed that the main factors associated with customer dissatisfaction were delays
in delivery times and the lack of effective communication during the service process. Through the time
and motion study conducted between January 30 and February 6, it was identified that the greatest
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delays occurred in the washing and detailing stages, where accumulated waiting times exceeded 60
minutes per vehicle. This created a chain of delays that affected the final delivery to the customer.
The records indicated that the total average service time, from reception to delivery, exceeded 6 hours,
while the brand standard established a maximum of 4 hours and 30 minutes. This deviation had a direct
impact on customer satisfaction, as the surveys reflected dissatisfaction regarding the failure to meet
the promised delivery time and the lack of timely information during the process.
It was also observed that the washing and detailing staff began their activities one hour after the
workshop opened, which created a bottleneck between 8:00 and 9:00 a.m., precisely when the service
advisors were starting to bring vehicles into the technical area. The workload analysis revealed that an
average of 16 to 19 vehicles were serviced per day, which required a more efficient redistribution of
schedules and personnel.
Deming Cycle (PDCA)
The methodological structure of the study was organized into four main phases aligned with the PDCA
continuous improvement cycle (Plan, Do, Check, Act) proposed by Deming (1986).
Plan (Process Diagnosis)
As a starting point for this phase, improvement objectives were established using the SMART
methodology. According to Doran (1981), this method provides an effective framework for defining
goals by ensuring they are Specific, Measurable, Achievable, Relevant, and Time-bound. Based on this
framework, the after-sales area was defined as the specific focus, with the goal of increasing customer
satisfaction and survey response rate by 15 percent. The objective was considered achievable through
the application of specific strategies, relevant because of its alignment with brand objectives, and time-
bound to a one-month period. Based on the above, the main objective formulated was as follows:
“Increase customer satisfaction and survey response rate in the after-sales area by 15 percent within a
one-month period, complying with the established brand standards.”
Once the SMART objective of the study was established, an analysis of customer complaints and
service performance was conducted in order to describe the problem. The results obtained are
presented in Table 1.
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delays occurred in the washing and detailing stages, where accumulated waiting times exceeded 60
minutes per vehicle. This created a chain of delays that affected the final delivery to the customer.
The records indicated that the total average service time, from reception to delivery, exceeded 6 hours,
while the brand standard established a maximum of 4 hours and 30 minutes. This deviation had a direct
impact on customer satisfaction, as the surveys reflected dissatisfaction regarding the failure to meet
the promised delivery time and the lack of timely information during the process.
It was also observed that the washing and detailing staff began their activities one hour after the
workshop opened, which created a bottleneck between 8:00 and 9:00 a.m., precisely when the service
advisors were starting to bring vehicles into the technical area. The workload analysis revealed that an
average of 16 to 19 vehicles were serviced per day, which required a more efficient redistribution of
schedules and personnel.
Deming Cycle (PDCA)
The methodological structure of the study was organized into four main phases aligned with the PDCA
continuous improvement cycle (Plan, Do, Check, Act) proposed by Deming (1986).
Plan (Process Diagnosis)
As a starting point for this phase, improvement objectives were established using the SMART
methodology. According to Doran (1981), this method provides an effective framework for defining
goals by ensuring they are Specific, Measurable, Achievable, Relevant, and Time-bound. Based on this
framework, the after-sales area was defined as the specific focus, with the goal of increasing customer
satisfaction and survey response rate by 15 percent. The objective was considered achievable through
the application of specific strategies, relevant because of its alignment with brand objectives, and time-
bound to a one-month period. Based on the above, the main objective formulated was as follows:
“Increase customer satisfaction and survey response rate in the after-sales area by 15 percent within a
one-month period, complying with the established brand standards.”
Once the SMART objective of the study was established, an analysis of customer complaints and
service performance was conducted in order to describe the problem. The results obtained are
presented in Table 1.
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Table 1. Customer satisfaction and response rate Oct-24 to Jan-25
With the information obtained, it was found that over the last three months customer satisfaction and
response rate have decreased by 19 percent at the branch located in the municipality of Tulancingo,
Hidalgo. During the period from October 2024 to January 2025, fifteen dissatisfaction surveys were
received, in which two customers stated that they would not return to have their service performed at
the dealership.
This raises the question: what problem does the customers’ decision not to return actually represent?
According to the data collected in Table 2, it was projected that for the year 2025 the economic losses
could increase up to 53,913.60 pesos if the issue is not addressed. As mentioned previously, a satisfied
customer represents a network of potential new customers, while dissatisfied customers not only
choose not to return but also reduce the possibility of attracting new clients.
Table 2.- Annual economic loss in 2024
To identify the root cause of the problem, a feedback strategy was implemented through satisfaction
surveys administered at the end of each service. During the period from October 2024 to January 2025,
fifteen satisfaction surveys were collected. The results revealed five distinct types of complaints: work
follow-up, delivery times, work performed, customer service, and maintenance cost.
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Table 1. Customer satisfaction and response rate Oct-24 to Jan-25
With the information obtained, it was found that over the last three months customer satisfaction and
response rate have decreased by 19 percent at the branch located in the municipality of Tulancingo,
Hidalgo. During the period from October 2024 to January 2025, fifteen dissatisfaction surveys were
received, in which two customers stated that they would not return to have their service performed at
the dealership.
This raises the question: what problem does the customers’ decision not to return actually represent?
According to the data collected in Table 2, it was projected that for the year 2025 the economic losses
could increase up to 53,913.60 pesos if the issue is not addressed. As mentioned previously, a satisfied
customer represents a network of potential new customers, while dissatisfied customers not only
choose not to return but also reduce the possibility of attracting new clients.
Table 2.- Annual economic loss in 2024
To identify the root cause of the problem, a feedback strategy was implemented through satisfaction
surveys administered at the end of each service. During the period from October 2024 to January 2025,
fifteen satisfaction surveys were collected. The results revealed five distinct types of complaints: work
follow-up, delivery times, work performed, customer service, and maintenance cost.
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Figure 1.- Complains during period
Once the results were collected, a Pareto Chart was used to prioritize the complaints with the greatest
impact on customer satisfaction. The analysis determined that both follow-up and delivery times
accounted for approximately 20 percent of the causes responsible for 80 percent of the recorded
dissatisfaction.
Do (Implementation of Improvement Strategies)
With the problem identified and the causes defined, the study proceeded to the next stage of the PDCA
cycle. Corrective measures were proposed for the two complaints with the highest impact, and as
shown in Figure 1, the most frequent complaint was related to work follow-up, so efforts focused on
mitigating this issue.
To begin reducing this complaint, an internal follow-up form was implemented, which the Service
Advisors (APS) were required to complete. This form served as a means of standardizing the process.
The structure of the form is illustrated in Figure 2.
Figure 2.- Follow-up form for APS
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Figure 1.- Complains during period
Once the results were collected, a Pareto Chart was used to prioritize the complaints with the greatest
impact on customer satisfaction. The analysis determined that both follow-up and delivery times
accounted for approximately 20 percent of the causes responsible for 80 percent of the recorded
dissatisfaction.
Do (Implementation of Improvement Strategies)
With the problem identified and the causes defined, the study proceeded to the next stage of the PDCA
cycle. Corrective measures were proposed for the two complaints with the highest impact, and as
shown in Figure 1, the most frequent complaint was related to work follow-up, so efforts focused on
mitigating this issue.
To begin reducing this complaint, an internal follow-up form was implemented, which the Service
Advisors (APS) were required to complete. This form served as a means of standardizing the process.
The structure of the form is illustrated in Figure 2.
Figure 2.- Follow-up form for APS
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To address the issue related to the complaints received regarding delivery times, a procedure divided
into three stages was implemented: 1. A time and motion study of the service process. 2. Simulation of
three possible scenarios. 3.Follow-up on surveys and reminder messages for customers
In the first stage, a study of the general service process was carried out between January 30 and
February 6, 2025. The average times obtained are described in Table 3.
Table 3.- Execution times for the general service process
According to Table 3, which presents the record of one of the samples used in this study, an estimate
of the average times of the general service process before the improvement actions were implemented
can be observed. The table also shows that vehicle reception took place between 07:50 and 10:40 a.m.,
with the analyzed vehicle arriving at 08:58 a.m. and experiencing a waiting time of 8 minutes and 31
seconds due to the constant flow of vehicles during that period.
Afterward, the unit remained in the waiting line to enter the mechanical area for approximately 1 hour
and 17 minutes, a duration that reflects process saturation and the need for improved operational
scheduling. The mechanical work lasted 1 hour, which corresponds to a standard service from the
program known as the Gold Service, a more complete and detailed maintenance procedure.
Once this stage was completed, the vehicle was moved to the washing area, where a waiting time of
more than 3 hours was recorded. This delay was caused by the imbalance between the number of
technicians (4) and washers (2) available at the time. The washing activity lasted approximately 1 hour,
followed by the detailing stage, which took an average of 7 minutes. Finally, the ICC staff performed
the quality inspection to verify the final condition of the vehicle and authorize its delivery to the
customer.
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To address the issue related to the complaints received regarding delivery times, a procedure divided
into three stages was implemented: 1. A time and motion study of the service process. 2. Simulation of
three possible scenarios. 3.Follow-up on surveys and reminder messages for customers
In the first stage, a study of the general service process was carried out between January 30 and
February 6, 2025. The average times obtained are described in Table 3.
Table 3.- Execution times for the general service process
According to Table 3, which presents the record of one of the samples used in this study, an estimate
of the average times of the general service process before the improvement actions were implemented
can be observed. The table also shows that vehicle reception took place between 07:50 and 10:40 a.m.,
with the analyzed vehicle arriving at 08:58 a.m. and experiencing a waiting time of 8 minutes and 31
seconds due to the constant flow of vehicles during that period.
Afterward, the unit remained in the waiting line to enter the mechanical area for approximately 1 hour
and 17 minutes, a duration that reflects process saturation and the need for improved operational
scheduling. The mechanical work lasted 1 hour, which corresponds to a standard service from the
program known as the Gold Service, a more complete and detailed maintenance procedure.
Once this stage was completed, the vehicle was moved to the washing area, where a waiting time of
more than 3 hours was recorded. This delay was caused by the imbalance between the number of
technicians (4) and washers (2) available at the time. The washing activity lasted approximately 1 hour,
followed by the detailing stage, which took an average of 7 minutes. Finally, the ICC staff performed
the quality inspection to verify the final condition of the vehicle and authorize its delivery to the
customer.
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Taken together, these times reflect the presence of significant bottlenecks in the operational flow prior
to the implementation of the improvement strategies, particularly in the washing waiting stage, which
directly affects customer satisfaction and the dealership’s ability to meet promised delivery times.
Various corrective actions were implemented, including adjustments to schedules and rest days for the
washing staff while respecting their rights and modifying shifts only with their approval to avoid
conflicts; standardization of a digital follow-up form for the Service Advisors (APS); development of a
skills matrix for technical personnel; and the addition of a new team member to the washing area. All
this information is presented in Table 4.
Table 4.- Times with 4 Technicians and 2 Washers
A time study was then conducted on different days under different scenarios, such as the case with 4
technicians and 2 washers, which was the most common scenario in the dealership given the number
of employees. Under this configuration, a maximum of 12 service units and 2 previous appointments
were handled per day, for a total of 14 units from Monday to Friday. This resulted in leftover units being
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Taken together, these times reflect the presence of significant bottlenecks in the operational flow prior
to the implementation of the improvement strategies, particularly in the washing waiting stage, which
directly affects customer satisfaction and the dealership’s ability to meet promised delivery times.
Various corrective actions were implemented, including adjustments to schedules and rest days for the
washing staff while respecting their rights and modifying shifts only with their approval to avoid
conflicts; standardization of a digital follow-up form for the Service Advisors (APS); development of a
skills matrix for technical personnel; and the addition of a new team member to the washing area. All
this information is presented in Table 4.
Table 4.- Times with 4 Technicians and 2 Washers
A time study was then conducted on different days under different scenarios, such as the case with 4
technicians and 2 washers, which was the most common scenario in the dealership given the number
of employees. Under this configuration, a maximum of 12 service units and 2 previous appointments
were handled per day, for a total of 14 units from Monday to Friday. This resulted in leftover units being
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carried over to the next day, creating a bottleneck. On Saturdays, a total of 8 service units and 2
previous appointments were washed, for a total of 10 units. Additional scenarios were then analyzed,
such as 3 technicians and 3 washers, as well as 4 technicians and 3 washers. The latter proved to be
the best scenario due to the increase in the number of units washed, as shown in Table 5.
Table 5.- Times with 4 Technicians and 3 Wahers
In Table 5, the increase in washed units can be clearly observed. In a single day, 16 service units and 5
previous appointments were handled, for a total of 21 units from Monday to Friday. On Saturdays, 12
service units and 7 previous appointments were handled. Additionally, a 15 percent buffer time was
available for the washing process, allowing the reception of more units or enabling team members to
assist each other when a vehicle required extra cleaning due to its condition, without exceeding the
expected time.
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carried over to the next day, creating a bottleneck. On Saturdays, a total of 8 service units and 2
previous appointments were washed, for a total of 10 units. Additional scenarios were then analyzed,
such as 3 technicians and 3 washers, as well as 4 technicians and 3 washers. The latter proved to be
the best scenario due to the increase in the number of units washed, as shown in Table 5.
Table 5.- Times with 4 Technicians and 3 Wahers
In Table 5, the increase in washed units can be clearly observed. In a single day, 16 service units and 5
previous appointments were handled, for a total of 21 units from Monday to Friday. On Saturdays, 12
service units and 7 previous appointments were handled. Additionally, a 15 percent buffer time was
available for the washing process, allowing the reception of more units or enabling team members to
assist each other when a vehicle required extra cleaning due to its condition, without exceeding the
expected time.
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Table 6.- Tracking
As an additional action, more frequent follow-ups were carried out on customers’ vehicles through a
database (Excel) that was constantly updated with the technicians’ comments. This was done by the
controller, who is responsible for assigning jobs to the technicians, and then reviewed by the Service
Advisors (APS), who informed customers if their vehicles required anything beyond the scheduled
maintenance service. It was then up to the customer to decide whether to authorize the additional
work.
Verify (Evaluation of Results)
The monthly averages of the Customer Satisfaction Index (CSI) corresponding to the period from
November to January (Table 2) were analyzed and compared with the averages obtained during the
period from February to April presented in Table 7, following the implementation of the after-sales
washing process optimization. The data was obtained directly from the corporate platform exclusively
available to dealerships and provided by the Nissan brand, which consolidates the official CSI results.
Table 7.- Overall Satisfaction Indicator
The pre-intervention monthly average was 83.67 percent (SD = 5.16), while the post-intervention
average was 95.50 percent (SD = 1.90), reflecting an absolute increase of 11.83 percentage points,
equivalent to a relative increase of 14.14 percent. An independent samples Student’s t-test indicated
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Table 6.- Tracking
As an additional action, more frequent follow-ups were carried out on customers’ vehicles through a
database (Excel) that was constantly updated with the technicians’ comments. This was done by the
controller, who is responsible for assigning jobs to the technicians, and then reviewed by the Service
Advisors (APS), who informed customers if their vehicles required anything beyond the scheduled
maintenance service. It was then up to the customer to decide whether to authorize the additional
work.
Verify (Evaluation of Results)
The monthly averages of the Customer Satisfaction Index (CSI) corresponding to the period from
November to January (Table 2) were analyzed and compared with the averages obtained during the
period from February to April presented in Table 7, following the implementation of the after-sales
washing process optimization. The data was obtained directly from the corporate platform exclusively
available to dealerships and provided by the Nissan brand, which consolidates the official CSI results.
Table 7.- Overall Satisfaction Indicator
The pre-intervention monthly average was 83.67 percent (SD = 5.16), while the post-intervention
average was 95.50 percent (SD = 1.90), reflecting an absolute increase of 11.83 percentage points,
equivalent to a relative increase of 14.14 percent. An independent samples Student’s t-test indicated
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that the difference between periods was statistically significant (t = 3.73; df = 4; p < 0.05), confirming
that the intervention had a positive effect on customer satisfaction levels.
Additionally, operational productivity showed an increase in the average number of vehicles serviced
per day, rising from 10 to 14 units before the intervention to 21 units after process optimization
As previously mentioned, the project implemented a digital follow-up form for the Service Advisors
(APS), which made it possible to establish a more transparent and efficient communication channel.
This tool allowed customers to be informed about the progress of their vehicle as well as any issues,
such as required parts or other considerations. The correct completion of these forms was verified
daily, generating a digital record with the collected information. This record included: customer contact
details, the vehicle entered for service, the names of the staff who attended to the customer, the entry
time for each stage of the general service process, and any additional comments.
Subsequently, the delivery time and customer satisfaction indicators were compared before and after
the implementation of the improvements, using operational risk analyses and service surveys. The
comparative analysis of the service process, conducted before and after the implementation of the APS
format, revealed the need to establish a skills matrix for the staff involved, which is described in the
following stage.
Act (Standardization and Follow-up)
As indicated in Deming’s methodology (1987), the “Act” stage presents two possible paths. If the results
are partial or insufficient, the process must return to the “Plan” stage with the newly acquired feedback.
This was not the case here. The goals were achieved as expected after implementing the APS format.
However, it was still necessary to standardize the changes, update the procedure, and establish controls
that promote a culture of continuous improvement. In this context, a skills matrix was implemented as
an evaluation tool for personnel involved in the general service process, and KPIs were established to
support the assessment.
The skills matrix integrated the key competencies required for operational excellence in the after-sales
service and, consequently, for improved customer satisfaction. It was structured into the following
phases:
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that the difference between periods was statistically significant (t = 3.73; df = 4; p < 0.05), confirming
that the intervention had a positive effect on customer satisfaction levels.
Additionally, operational productivity showed an increase in the average number of vehicles serviced
per day, rising from 10 to 14 units before the intervention to 21 units after process optimization
As previously mentioned, the project implemented a digital follow-up form for the Service Advisors
(APS), which made it possible to establish a more transparent and efficient communication channel.
This tool allowed customers to be informed about the progress of their vehicle as well as any issues,
such as required parts or other considerations. The correct completion of these forms was verified
daily, generating a digital record with the collected information. This record included: customer contact
details, the vehicle entered for service, the names of the staff who attended to the customer, the entry
time for each stage of the general service process, and any additional comments.
Subsequently, the delivery time and customer satisfaction indicators were compared before and after
the implementation of the improvements, using operational risk analyses and service surveys. The
comparative analysis of the service process, conducted before and after the implementation of the APS
format, revealed the need to establish a skills matrix for the staff involved, which is described in the
following stage.
Act (Standardization and Follow-up)
As indicated in Deming’s methodology (1987), the “Act” stage presents two possible paths. If the results
are partial or insufficient, the process must return to the “Plan” stage with the newly acquired feedback.
This was not the case here. The goals were achieved as expected after implementing the APS format.
However, it was still necessary to standardize the changes, update the procedure, and establish controls
that promote a culture of continuous improvement. In this context, a skills matrix was implemented as
an evaluation tool for personnel involved in the general service process, and KPIs were established to
support the assessment.
The skills matrix integrated the key competencies required for operational excellence in the after-sales
service and, consequently, for improved customer satisfaction. It was structured into the following
phases:
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● Process follow-up: Aligned with the Voice of the Customer (VOC) and the Customer
Satisfaction Index (CSI), ensuring compliance with the standards defined through customer
feedback. Responsibilities for each position were verified to ensure proper execution of
assigned tasks.
● Customer service: Focused on service sales and identifying opportunities for additional sales,
with the aim of optimizing both customer experience and business performance.
● Profitability: Considered as a cross-functional element in all activities related to service or
additional sales. The team’s actions were compared with their economic efficiency and
financial impact.
● Attitude: Based on two core values within after-sales service. Empathy, defined as the ability
to fully understand the customer to provide genuine service and respect, which promotes
courteous and considerate treatment of all individuals while adapting sales methods within a
professional framework.
Finally, adjustments were made to the methods previously proposed to address complaints related to
delivery times. The new times obtained are presented in Table 8.
Table 8.- Time results after improvement
The comparative analysis between Table 3 and Table 8 shows a significant reduction in waiting time
between the mechanical and washing stages, decreasing from 3 hours and 3 minutes to 1 hour and 12
minutes, which represents a reduction of 61 percent. This improvement resulted from the integrated
application of the strategies designed within the PDCA cycle, the implementation of quality
methodologies such as SMART and 5S, and the use of operational control tools. Overall, the most
relevant actions included rescheduling the washers’ working hours, adjusting their days off according
632 | Página
● Process follow-up: Aligned with the Voice of the Customer (VOC) and the Customer
Satisfaction Index (CSI), ensuring compliance with the standards defined through customer
feedback. Responsibilities for each position were verified to ensure proper execution of
assigned tasks.
● Customer service: Focused on service sales and identifying opportunities for additional sales,
with the aim of optimizing both customer experience and business performance.
● Profitability: Considered as a cross-functional element in all activities related to service or
additional sales. The team’s actions were compared with their economic efficiency and
financial impact.
● Attitude: Based on two core values within after-sales service. Empathy, defined as the ability
to fully understand the customer to provide genuine service and respect, which promotes
courteous and considerate treatment of all individuals while adapting sales methods within a
professional framework.
Finally, adjustments were made to the methods previously proposed to address complaints related to
delivery times. The new times obtained are presented in Table 8.
Table 8.- Time results after improvement
The comparative analysis between Table 3 and Table 8 shows a significant reduction in waiting time
between the mechanical and washing stages, decreasing from 3 hours and 3 minutes to 1 hour and 12
minutes, which represents a reduction of 61 percent. This improvement resulted from the integrated
application of the strategies designed within the PDCA cycle, the implementation of quality
methodologies such as SMART and 5S, and the use of operational control tools. Overall, the most
relevant actions included rescheduling the washers’ working hours, adjusting their days off according
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to peak demand, optimizing workflow between the mechanical and washing areas, and standardizing
processes through the order and discipline promoted by 5S. These measures helped balance the
workload, reduce idle times, and ensure a continuous flow of vehicles, contributing directly to meeting
promised delivery times and increasing customer satisfaction, as reflected in Table 7.
Theoretical discussion
The results obtained are in line with the approaches of Deming (1986) and Ishikawa (1989), who
highlight the importance of process control and staff participation as pillars of continuous improvement.
In this case, the application of the PDCA cycle allowed for a systematic approach to diagnosis, action,
and control, while the SMART methodology facilitated the management of achievable and measurable
objectives.
Similarly, the findings confirm Kotler and Keller's (2016) assertion that customer satisfaction depends
not only on the functional fulfillment of the service, but also on the emotional perception of support
and communication. The standardization of follow-up by APS strengthened this aspect, creating a more
reliable service experience.
On the other hand, the combination of tools such as flowcharts, Ishikawa diagrams, the 5S
methodology, and KPIs reflects an effective integration of quantitative and qualitative methods. This
synergy not only reduced time but also improved staff morale and discipline, which are essential
components for total quality sustainability (Oakland, 2014: Ham, 2025).
Finally, internal controls were established through weekly monitoring and evaluation, with the aim of
ensuring the sustainability of results and preventing setbacks in performance indicators. In addition,
interdepartmental coordination was strengthened, especially with the new vehicle area, respecting
internal agreements that establish that washers must service a maximum of four new units per day for
delivery to customers. This inter-area commitment made it possible to maintain operational balance
without affecting the efficiency or quality standards of the after-sales area.
However, the study presents several limitations that must be considered when interpreting the results.
First, the statistical analysis was conducted based on aggregated monthly averages, which reduced the
sample size for inferential testing and limited the possibility of analyzing variability at the individual
633 | Página
to peak demand, optimizing workflow between the mechanical and washing areas, and standardizing
processes through the order and discipline promoted by 5S. These measures helped balance the
workload, reduce idle times, and ensure a continuous flow of vehicles, contributing directly to meeting
promised delivery times and increasing customer satisfaction, as reflected in Table 7.
Theoretical discussion
The results obtained are in line with the approaches of Deming (1986) and Ishikawa (1989), who
highlight the importance of process control and staff participation as pillars of continuous improvement.
In this case, the application of the PDCA cycle allowed for a systematic approach to diagnosis, action,
and control, while the SMART methodology facilitated the management of achievable and measurable
objectives.
Similarly, the findings confirm Kotler and Keller's (2016) assertion that customer satisfaction depends
not only on the functional fulfillment of the service, but also on the emotional perception of support
and communication. The standardization of follow-up by APS strengthened this aspect, creating a more
reliable service experience.
On the other hand, the combination of tools such as flowcharts, Ishikawa diagrams, the 5S
methodology, and KPIs reflects an effective integration of quantitative and qualitative methods. This
synergy not only reduced time but also improved staff morale and discipline, which are essential
components for total quality sustainability (Oakland, 2014: Ham, 2025).
Finally, internal controls were established through weekly monitoring and evaluation, with the aim of
ensuring the sustainability of results and preventing setbacks in performance indicators. In addition,
interdepartmental coordination was strengthened, especially with the new vehicle area, respecting
internal agreements that establish that washers must service a maximum of four new units per day for
delivery to customers. This inter-area commitment made it possible to maintain operational balance
without affecting the efficiency or quality standards of the after-sales area.
However, the study presents several limitations that must be considered when interpreting the results.
First, the statistical analysis was conducted based on aggregated monthly averages, which reduced the
sample size for inferential testing and limited the possibility of analyzing variability at the individual
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survey level. Furthermore, the research was carried out in a single automotive dealership, which
restricts the generalizability of the findings to other organizational contexts with different operational
dynamics. Likewise, the post-intervention observation period was relatively short, preventing the
evaluation of seasonal effects or long-term fluctuations in service demand.
Regarding the sustainability of the results, there are potential risks associated with staff turnover,
variations in workload, changes in corporate guidelines, or a decrease in adherence to the implemented
controls. The absence of continuous supervision or a decline in operational discipline could lead to
regression toward previous practices, thereby affecting the achieved level of customer satisfaction.
Therefore, the institutionalization of standardized procedures and the continuous monitoring of key
performance indicators are essential to preserve the benefits obtained over time.
CONCLUSIONS
The implementation of PDCA, SMART, and 5S methodologies in the automotive after-sales area
yielded significant results in key operational and customer satisfaction indicators. Comparative records
show a 61% reduction in waiting time between the mechanical and washing stages, from 3:03:42 hours
to 1:12:55 hours, demonstrating effective workflow optimization and better coordination between
areas.
Similarly, satisfaction indicators showed a notable recovery: the CSI index rose from an average of
77.8% in January to 95.6% in the following quarter, accompanied by an increase in the survey response
rate. These improvements were achieved through the reconfiguration of schedules, the redistribution
of workloads, systematic customer follow-up, and the standardization of the work environment under
the principles of 5S.
The results obtained demonstrate that the disciplined application of quality tools can generate
measurable impacts on productivity and service perception, strengthening process reliability and end-
user satisfaction. From an industrial and process engineering perspective, this case reaffirms that
management based on continuous improvement methodologies allows operational data to be
transformed into effective decisions, consolidating more efficient, secure, and customer-oriented
systems.
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survey level. Furthermore, the research was carried out in a single automotive dealership, which
restricts the generalizability of the findings to other organizational contexts with different operational
dynamics. Likewise, the post-intervention observation period was relatively short, preventing the
evaluation of seasonal effects or long-term fluctuations in service demand.
Regarding the sustainability of the results, there are potential risks associated with staff turnover,
variations in workload, changes in corporate guidelines, or a decrease in adherence to the implemented
controls. The absence of continuous supervision or a decline in operational discipline could lead to
regression toward previous practices, thereby affecting the achieved level of customer satisfaction.
Therefore, the institutionalization of standardized procedures and the continuous monitoring of key
performance indicators are essential to preserve the benefits obtained over time.
CONCLUSIONS
The implementation of PDCA, SMART, and 5S methodologies in the automotive after-sales area
yielded significant results in key operational and customer satisfaction indicators. Comparative records
show a 61% reduction in waiting time between the mechanical and washing stages, from 3:03:42 hours
to 1:12:55 hours, demonstrating effective workflow optimization and better coordination between
areas.
Similarly, satisfaction indicators showed a notable recovery: the CSI index rose from an average of
77.8% in January to 95.6% in the following quarter, accompanied by an increase in the survey response
rate. These improvements were achieved through the reconfiguration of schedules, the redistribution
of workloads, systematic customer follow-up, and the standardization of the work environment under
the principles of 5S.
The results obtained demonstrate that the disciplined application of quality tools can generate
measurable impacts on productivity and service perception, strengthening process reliability and end-
user satisfaction. From an industrial and process engineering perspective, this case reaffirms that
management based on continuous improvement methodologies allows operational data to be
transformed into effective decisions, consolidating more efficient, secure, and customer-oriented
systems.
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635 | Página
Consequently, this study provides practical evidence of how engineering applied to service
management can integrate technical analysis with organizational improvement, contributing to the
development of sustainable models of quality and efficiency in the automotive industry. The findings
confirm that the integration of PDCA methodology and time-motion analysis can effectively improve
operational efficiency and customer satisfaction in automotive after-sales services.
BIBLIOGRAPHIC REFERENCES
Acero, L. C. P. (2016). Ingeniería de métodos: Movimientos y tiempos (2nd ed.). Ecoe Ediciones.
Andrade, A. M., Del Río, C., & Alvear, D. L. (2019). A study on time and motion to increase the efficiency
of a shoe manufacturing company. Información Tecnológica, 30(3), 83–94.
https://doi.org/10.4067/S0718-07642019000300083
Arturo. (2025, January 31). ¿En qué consiste el modelo SERVQUAL de calidad de servicio? Aprende
Industrial. https://aprendeindustrial.com/modelo-servqual/
Attack. (2020, August 13). Diagrama de Ishikawa en servicios al cliente. Diagrama de Ishikawa.
https://diagramadeishikawa.com/diagrama-de-ishikawa-en-servicios-al-cliente/
Castillo Pinto, R. R., Parisaca Mancilla, P., Castillo Pinto, R. O., Ramos Vilca, W., & Huanacuni Mamani,
W. M. (2024). Análisis de productividad en construcción aplicando Lean Construction basado
en rendimientos de mano de obra en proyectos hospitalarios nivel I–IV. Horizonte Académico,
4(2), 250–270. https://doi.org/10.70208/3007.8245.v4.n2.43
Castillo-Vite, J. I., Juárez-Vite, A., Rivera-Gómez, H., & Corona-Armenta, J. R. (2025). Estrategias de
manufactura esbelta para aumentar la producción de transformadores eléctricos. Pädi Boletín
Científico de Ciencias Básicas e Ingenierías del ICBI, 13(Especial 2), 88–96.
https://doi.org/10.29057/icbi.v13iEspecial2.14691
Chuquivigel Ventura, A. O. (2024). Propuesta de mejora aplicando herramientas de manufactura esbelta
para incrementar la productividad en una empresa de lavado de autos (Tesis de licenciatura).
Universidad Privada del Norte.
https://repositorio.upn.edu.pe/bitstream/handle/11537/39909/Tesis%20Alexander%20Omar
%20Chuquivigel%20Ventura.pdf
635 | Página
Consequently, this study provides practical evidence of how engineering applied to service
management can integrate technical analysis with organizational improvement, contributing to the
development of sustainable models of quality and efficiency in the automotive industry. The findings
confirm that the integration of PDCA methodology and time-motion analysis can effectively improve
operational efficiency and customer satisfaction in automotive after-sales services.
BIBLIOGRAPHIC REFERENCES
Acero, L. C. P. (2016). Ingeniería de métodos: Movimientos y tiempos (2nd ed.). Ecoe Ediciones.
Andrade, A. M., Del Río, C., & Alvear, D. L. (2019). A study on time and motion to increase the efficiency
of a shoe manufacturing company. Información Tecnológica, 30(3), 83–94.
https://doi.org/10.4067/S0718-07642019000300083
Arturo. (2025, January 31). ¿En qué consiste el modelo SERVQUAL de calidad de servicio? Aprende
Industrial. https://aprendeindustrial.com/modelo-servqual/
Attack. (2020, August 13). Diagrama de Ishikawa en servicios al cliente. Diagrama de Ishikawa.
https://diagramadeishikawa.com/diagrama-de-ishikawa-en-servicios-al-cliente/
Castillo Pinto, R. R., Parisaca Mancilla, P., Castillo Pinto, R. O., Ramos Vilca, W., & Huanacuni Mamani,
W. M. (2024). Análisis de productividad en construcción aplicando Lean Construction basado
en rendimientos de mano de obra en proyectos hospitalarios nivel I–IV. Horizonte Académico,
4(2), 250–270. https://doi.org/10.70208/3007.8245.v4.n2.43
Castillo-Vite, J. I., Juárez-Vite, A., Rivera-Gómez, H., & Corona-Armenta, J. R. (2025). Estrategias de
manufactura esbelta para aumentar la producción de transformadores eléctricos. Pädi Boletín
Científico de Ciencias Básicas e Ingenierías del ICBI, 13(Especial 2), 88–96.
https://doi.org/10.29057/icbi.v13iEspecial2.14691
Chuquivigel Ventura, A. O. (2024). Propuesta de mejora aplicando herramientas de manufactura esbelta
para incrementar la productividad en una empresa de lavado de autos (Tesis de licenciatura).
Universidad Privada del Norte.
https://repositorio.upn.edu.pe/bitstream/handle/11537/39909/Tesis%20Alexander%20Omar
%20Chuquivigel%20Ventura.pdf
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David. (2022, March 11). TQM (Total Quality Management): Gestión de la calidad total. Lean
Manufacturing 10. https://leanmanufacturing10.com/calidad-total-tqm
Deming, W. E. (1986). Out of the crisis. MIT Press.
Doran, G. T. (1981). There’s a SMART way to write management’s goals and objectives. Management
Review, 70(11), 35–36.
Fuentes González, G. J. (2003). Estudio de tiempos y movimientos a las operaciones realizadas en una
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Sons.
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Scribd. https://es.scribd.com/document/658501384/Modelo-de-negocio-cadena-de-utilidad-
en-el-servicio-de-Heskett-y-Schlesinger
Vargas Crisóstomo, E. L., & Camero Jiménez, J. W. (2021). Aplicación del Lean Manufacturing (5S y
Kaizen) para el incremento de la productividad en el área de producción de adhesivos acuosos.
Industrial Data, 24(2), 249–271. https://doi.org/10.15381/idata.v24i2.19485