This thesis presents the development and pilot implementation of a Power BI-based decision support model to enhance quality analysis and risk management in public procurement. The system aims to enable more transparent, data-driven, and audit traceable decision making processes across the procurement life cycle through the integration of Quality Function Deployment (QFD) and Failure Modes, Effects, and Criticality Analysis (FMECA). The research addresses the institutional need for mechanisms that go beyond compliance and cost minimization, providing structured approaches for supplier quality evaluation, operational risk prioritization, and stakeholder-aligned decision-making. The system is supported by a PostgreSQL backend and integrates both internal and external data sources (e.g., TED, MEPA).