Abstract

Enterprise Resource Planning (ERP) systems are essential for managing business operations, yet inefficiencies in workflows often remain hidden, leading to suboptimal performance. Process mining techniques have emerged as a powerful approach to analyzing ERP event logs, identifying bottlenecks, and improving workflow transparency. This explores advances in process mining techniques and their role in enhancing ERP outcomes. Traditional process mining methods, including discovery, conformance checking, and enhancement, provide valuable insights into business operations. However, recent advancements have introduced artificial intelligence (AI) and machine learning (ML) integration, enabling predictive process mining and automated anomaly detection. Additionally, hybrid approaches that combine rule-based and data-driven techniques allow for more precise identification of inefficiencies. The shift towards real-time process mining, leveraging streaming data analysis, enhances proactive decision-making and workflow optimization. Key applications of advanced process mining in ERP systems include detecting bottlenecks, analyzing process deviations, and uncovering inefficiencies hidden within unstructured data. These techniques improve decision-making by providing data-driven insights, optimizing resource allocation, and enhancing compliance with industry regulations. Real-world case studies in financial services, manufacturing, supply chain management, and human resource operations demonstrate the tangible benefits of process mining in optimizing ERP performance. Despite its advantages, process mining faces challenges such as data privacy concerns, scalability limitations, and resistance to adoption. Addressing these challenges requires investing in secure data governance, scalable infrastructure, and user-friendly visualization tools. Future directions in process mining include AI-driven self-learning systems, blockchain integration for enhanced transparency, and cloud-based process mining solutions for scalability and real-time analytics. By leveraging these advances, organizations can maximize ERP efficiency, streamline operations, and drive continuous business improvement. This highlights the importance of process mining in modern ERP ecosystems and provides strategic recommendations for businesses looking to enhance operational transparency and efficiency.