Viable and Agile Model for Improving the Quality Area in an Automotive Company in Mexico
The automotive industry is a key driver of global economic growth. However, traditional management approaches, relying on statistical tools and continuous improvement methodologies from the 1990s, lack the agility needed to address today’s complex challenges. This study proposes the Agile Viable Mod...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/5/343 |
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| Summary: | The automotive industry is a key driver of global economic growth. However, traditional management approaches, relying on statistical tools and continuous improvement methodologies from the 1990s, lack the agility needed to address today’s complex challenges. This study proposes the Agile Viable Model (AVM), which integrates Viable System Model (VSM), Soft Systems Methodology (SSM), and Agile Methodologies to enhance responsiveness, resilience, and strategic decision-making in quality management. Applied to the Problem Resolution Process in Quality Control, the study identified low network connectivity, confirming that the system operates under a Supercritical Regime, limiting efficiency. Analyst involved and his leader emerged as critical nodes, with 68% of interactions being conflictual, revealing the need for improved communication and collaboration. To address these challenges, agile tools such as virtual boards, product logs, and daily meetings were integrated, optimizing process flexibility. CATWOE analysis facilitated the development of conceptual models aligned with organizational objectives. The Problem Resolution Process is vital both pre- and post-sale, influencing customer satisfaction and warranty costs. Strengthening connectivity and collaboration will lead to faster problem resolution, reduced costs, and enhanced reputation. The AVM offers a structured yet adaptive solution, improving operational efficiency and decision-making in automotive quality management. |
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| ISSN: | 2079-8954 |