Process mining in humanitarian procurement: a scoping review
Nour Damer, Luay Anaya, Fadi Qutaishat, Hana ArrfouPurpose
Despite its strong potential to optimize business processes, process mining remains largely unexplored in humanitarian operations. Therefore, this study aims to systematically examine the state of research across process mining in procurement and humanitarian procurement analytics and identify complementarities between the two streams.
Design/methodology/approach
A scoping review methodology was applied to systematically analyze peer-reviewed studies published between January 2015 and August 2025. Following a structured search and screening procedure, 43 studies were analyzed across two themes: process mining in procurement and humanitarian procurement analytics.
Findings
The study reveals a clear methodological divergence between the two themes. Process mining studies mainly provide descriptive and diagnostic insights using real event-log data, yet rarely extend to predictive or prescriptive analytics. In contrast, humanitarian procurement research advances prescriptive models but mainly relies on simulated or parameterized data. Predictive applications remain underdeveloped across both themes, while prescriptive models in humanitarian procurement are rarely validated using operational data. The comparison shows that process-mining capabilities, including compliance checking, bottleneck analysis, anomaly detection and process-variant analysis, could provide empirical evidence to complement existing decision-oriented models.
Originality/value
The main contribution of this work is the identification of four cross-cutting themes: compliance and transparency, efficiency and performance, risk, resilience and sustainability and methodological robustness. By linking process-mining capabilities to specific humanitarian procurement challenges and identifying practical conditions for their application, the review provides a foundation for developing more integrated and empirically grounded approaches.