Enhancing Supply Chain Management: A Hybrid Approach for Smart Decisions and Performance

Supply chains (SC) are essential for the operation of companies, evolving with changes in the market and the parties involved. Effective Supply Chain Management (SCM) is key to success and competitive advantage, yet SCM faces challenges such as collaboration, adoption of emerging technologies (including Artificial Intelligence, AI), and best practices. The Supply Chain Operations Reference (SCOR) model is a powerful tool for evaluating and comparing SC activities that aims to reduce the challenges in achieving an effective SCM. This chapter explores the integration of AI in SCM using the SCOR model. A diagnostic methodology based on the SCOR model is designed, and a hybrid model is developed to improve decision making and the performance of SCM. Resulting in a treatment with mathematical tools and optimization methods that seeks a uniform, efficient and effective process. An important feature of the proposed methodology is its applicability to various industries. The methodology is expected to automate decisions, standardize processes, eliminate unnecessary activities, and offer future adaptability. The methodology is reproducible and applicable in virtually any SC, providing intelligent management that optimizes the effectiveness of SCM, positively impacting performance indicators, increasing benefits, and providing flexible responses to changes.