SUPPLIER PERFORMANCE EVALUATION IN ERP SYSTEMS USING DATA ANALYTICS, BUSINESS INTELLIGENCE, AND ARTIFICIAL INTELLIGENCE FOR CONTRACT OPTIMIZATION

Abstract

To be successful and stay ahead of the competition in today's fast-paced business environment, where technology is evolving swiftly and the globe is becoming more connected, supply chains need to be efficient and adaptable. Checking how well suppliers are performing and making contracts better in a smart way are both vital parts of excellent supply chain management. These steps have a direct impact on the quality of products and services, the efficiency of the business, its ability to manage expenses, and its ability to lower risks. Enterprise Resource Planning (ERP) systems are the main tools that businesses use to keep track of critical tasks like buying products and interacting with suppliers. They also keep a lot of essential data. This data is getting bigger and more complicated, thus we need to employ new analytical approaches to uncover meaningful information. Business intelligence (BI), data analytics, and artificial intelligence (AI) are powerful technologies that can convert raw ERP data into meaningful information. This makes it a lot easier to check how well suppliers are doing and make contracts better. This paper reviews the current literature and explores the integration of data analytics, BI, and AI within ERP systems for supplier performance evaluation and contract optimization, examining key methodologies, benefits, challenges, and future research directions, drawing insights from recent academic research and industry reports.