In today’s fast paced procurement environments, organizations face growing pressure to streamline supplier evaluation processes to save time and improve consistency. Manual methods often introduce inefficiencies, errors, and delays, highlighting the need for structured and data-driven improvement strategies. This study applies the DMAIC methodology to enhance the supplier evaluation process within a chemical sourcing team. The original method was highly manual, requiring an average of 5.69 hours to generate evaluation tables and involving repetitive formatting, hardcoded formulas, and inconsistency across projects. The primary objectives were to reduce table creation time to under 30 minutes, automate over 90% of the process, and validate improvements using control charts and process capability analysis. In the Define phase, Voice of the Customer (VOC) data was translated into measurable Critical to Quality (CTQ) targets. The Measure phase revealed high variability in completion times, while the Analyze phase identified key root causes including non-scalable design and excessive manual effort. Two solutions were tested using PDSA cycles: an Excel-based method and a Python-coded system. The coding solution reduced average creation time to 46 seconds. Control charts confirmed process stability, and capability indices supported consistent performance. A Sigma Level of 4.29 further validated long-term capability. The project exceeded its CTQ goals, achieving a 99.77% time reduction and demonstrating the impact of Lean Six Sigma tools in administrative workflows. Future work includes developing a user interface and integrating the system with sourcing platforms to support digital transformation.