An Integrated Framework for Achieving Process and Operational Excellence in the Automotive Industry

Márcio Vitor Tonhá Rodrigues, Engenheiro de Produçao

Doctoral thesis

Abstract:

In recent years, the automotive industry has undergone significant transformations driven by advancements in technology, changing consumer preferences, and evolving regulatory requirements. Amidst this dynamic landscape, achieving an operational excellence and a competitive advantage has become vital for automotive companies. In this thesis a tailored framework is developed to measure and leverage a process efficiency mainly within niched and highly specialized parts of automotive industry as opposed to standardized serial or mass productions these stand somewhat outside the major interest of scientists and practitioners. The tailored framework is based on a modification of the traditional Supply Chain Operations Reference model taking into account industry-specific considerations, emphasizing rapid response planning, streamlined sourcing, flexible vehicle assembly, expedited delivery, and enhanced real-time decision support. As a part of the framework it is also suggested to adopt customized key performance indicators including for example Error Rate, Lead Time or Customer Satisfaction Score to provide a more accurate performance measure. These indicators together with an application of Analytical Hierarchy Process enable a prioritization to align decisions with strategic goals more efficiently and also an aggregation significantly simplifying performance tracking. Using a case study methodology within a motorsport racing department of a real life car manufacturer operating in the Czech Republic, the framework is validated and its benefits are demonstrated consisting mainly of the significant improvements in the operational efficiency, accelerating the decision-making, and increasing the team performance. The proposed framework facilitates an easy comparison across different time periods and operational contexts, it helps teams to identify trends, measure a progress, and make informed decisions particularly in environments where quick and accurate performance assessments are essential for the success.

Abstract:

In recent years, the automotive industry has undergone significant transformations driven by advancements in technology, changing consumer preferences, and evolving regulatory requirements. Amidst this dynamic landscape, achieving an operational excellence and a competitive advantage has become vital for automotive companies. In this thesis a tailored framework is developed to measure and leverage a process efficiency mainly within niched and highly specialized parts of automotive industry as opposed to standardized serial or mass productions these stand somewhat outside the major interest of scientists and practitioners. The tailored framework is based on a modification of the traditional Supply Chain Operations Reference model taking into account industry-specific considerations, emphasizing rapid response planning, streamlined sourcing, flexible vehicle assembly, expedited delivery, and enhanced real-time decision support. As a part of the framework it is also suggested to adopt customized key performance indicators including for example Error Rate, Lead Time or Customer Satisfaction Score to provide a more accurate performance measure. These indicators together with an application of Analytical Hierarchy Process enable a prioritization to align decisions with strategic goals more efficiently and also an aggregation significantly simplifying performance tracking. Using a case study methodology within a motorsport racing department of a real life car manufacturer operating in the Czech Republic, the framework is validated and its benefits are demonstrated consisting mainly of the significant improvements in the operational efficiency, accelerating the decision-making, and increasing the team performance. The proposed framework facilitates an easy comparison across different time periods and operational contexts, it helps teams to identify trends, measure a progress, and make informed decisions particularly in environments where quick and accurate performance assessments are essential for the success.

Keywords

Business Process Management, Business Process Integration, Business Process Integration Management, Automotive industry, Motorsport racing, Operational excellence, Multi criteria decision making, Supply Chain Operations Reference model, Analytic Hierarchy Process

Language used: English

Date on which the thesis was submitted / produced: 30. 8. 2024

Thesis defence

• Supervisor: doc. Ing. Jakub Dyntar, Ph.D.

Technical University of Liberec

Faculty of Economics

Doctoral programme / field:
Economics and Management / Business Economics and Management