Design of Supply Chain Performance Measurement Using A Hybrid of SCOR Model and Multi Criteria Decision Making Method in the Seaweed Industry

Supply Chain Performance (SCP) is a crucial aspect of supply chain management (SCM). It allows the company to maintain competitiveness by assessing and improving its supply chain. This study aims to quantify SCP and incorporate the results into a monitoring and evaluation dashboard. The research combined the SCOR Model Version 12 with Multi-Criteria Decision Making (MCDM) methods, specifically the Analytic Hierarchy Process (AHP) and TOPSIS. It evaluated 45 Key Performance Indicators (KPIs), resulting in an average SCP score of 0.494, classified as sufficient. A sensitivity analysis was performed to verify the consistency of the weighting results. The SCP dashboard visually presents each criterion’s performance, helping decision-makers identify process issues and make quick, measurable improvements. Key areas identified for improvement include raw material planning, employee skills, information exchange with suppliers and consumers, and machinery maintenance. For future research, it is recommended to expand this approach to assess SCP and evaluate suppliers for other industries, such as salt, fish, and coffee processing. Additionally, exploring other MCDM methods, like Fuzzy AHP and Fuzzy TOPSIS, could enhance further comprehensive understanding of decision-making.