This article investigates how process mining catalyzes the digital transformation of enterprise logistics toward circular and sustainable supply‑chain performance. Using a systematic analysis of academic research from 2019–2025, triangulated with industry implementations and technology assessments, the study explains how process mining reshapes logistics decision‑making across discovery, conformance, enhancement, prediction, and operational support. Findings show organizations implementing process mining achieve 20–40% operational cost reductions while advancing environmental objectives. Convergence with Industry 4.0—artificial intelligence, IoT, blockchain, and digital twins—creates end‑to‑end visibility and optimization across multi‑tier networks. Object‑centric process mining, commercialized in 2022, overcomes classical limitations by jointly analyzing orders, shipments, and invoices, exposing many‑to‑many relations typical of logistics flows. The research extends the Resource‑Based View by positioning process‑mining capabilities as VRIN assets and applies Dynamic Capabilities to explain sensing, seizing, and transforming behaviors enabled by real‑time process intelligence. An integrated framework combines process mining with circular‑economy principles and sustainability metrics; evidence indicates a positive correlation (r=0.34) between process‑mining adoption and sustainable supply‑chain performance. A five‑level maturity model structures the pathway from reactive operations to autonomous, AI‑driven supply chains. Implementation analysis highlights the centrality of enterprise integration and identifies data‑quality remediation—about 80% of effort—together with organizational resistance and skills gaps as critical challenges. Enterprise contexts emphasize SAP integration for real‑time analysis, reinforcing the need for strong data governance and cloud‑native scalability. Cross‑industry cases report 25–50% cycle‑time reductions, 40–60% error decreases, and 15–30% environmental‑impact reductions. The framework operationalizes value measurement through balanced KPIs spanning process efficiency, utilization, conformance, emissions accounting, material circularity, and financial outcomes, while a staged roadmap details assessment, foundation, pilot, scale, and continuous optimization phases. Future research should examine the interplay of process mining with quantum optimization, generative AI, 5G and edge computing, digital twins, hyperautomation, and blockchain as these capabilities enable real‑time, trusted, and prescriptive analytics at scale. Overall, the study shows that process mining provides the visibility to diagnose actual operations and the intelligence to optimize for multiple objectives, equipping enterprises with the structures, metrics, and governance needed to progress toward circular and sustainable supply‑chain performance.
Тарас Муха (Wed,) studied this question.