<![CDATA[Although Business Process Management (BPM) and Process Mining (PM) have been extensively studied as distinct domains, limited research has systematically explored their convergence. this study presents a Systematic Literature Review (SLR) on the convergence between Business Process Management (BPM) and Process Mining (PM), focusing on journal publications indexed in SpringerLink from 2020 to 2025. The review aims to map current research trends, identify how PM techniques support the BPM lifecycle, and explore the main benefits and challenges of their integration within organizational contexts. Using the PRISMA methodology and the PICOS framework, thirteen high-quality studies were systematically analyzed. The findings reveal that BPM and PM are increasingly interdependent—BPM provides a structured lifecycle for continuous improvement, while PM introduces data-driven insights through process discovery, conformance checking, and performance monitoring. PM strengthens each phase of the BPM lifecycle by enhancing process transparency, real-time monitoring, and evidence-based decision-making. However, integration remains challenged by data quality issues, limited governance mechanisms, insufficient management support, and tool usability constraints. The study concludes that successful BPM–PM convergence requires not only technical advancements but also organizational readiness and strategic alignment. Future research should emphasize cross-organizational and longitudinal approaches to develop comprehensive frameworks for embedding process intelligence within digital transformation initiatives.]]>
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