The efficiency and quality of air conditioning installation processes are critical to ensuring customer satisfaction and operational excellence. However, inefficiencies such as supply chain delays, high rework rates, and process inconsistencies significantly impact service performance. This study applies the Lean Six Sigma (LSS) methodology to identify, analyze, and mitigate inefficiencies in the installation process at a company specializing in thermal solutions. A mixed-method approach integrating SIPOC diagrams, Value Stream Mapping (VSM), and root cause analysis was used to diagnose process bottlenecks. Key performance indicators were evaluated, including installation time, defect rates, and customer satisfaction metrics. The findings reveal that implementing LSS tools led to a measurable reduction in installation times, a 33% decrease in defects, and an increase in overall process efficiency. These results highlight the effectiveness of data-driven decision-making in service optimization, offering a replicable framework for similar industries. Future research should explore Industry 4.0 integrations like IoT-based monitoring and predictive analytics to enhance automation and operational agility further.