Organizations executing multiple concurrent projects frequently face operational risks due to material shortages, idle inventory, emergency procurement, and fragmented decision-making. While traditional ERP systems optimize procurement within individual projects, they offer limited support for structured cross-project redistribution under uncertainty. This study proposes CIRIS (Cross-Inventory Reallocation & Intelligence System), a risk-aware framework designed to enhance supply chain resilience and reduce capital inefficiencies through structured decision modeling.

CIRIS is implemented as a hybrid desktop–cloud architecture with offline-first capability and centralized synchronization. The framework is built on a configurable multi-factor reallocation model, where candidate resource transfers are evaluated using weighted parameters including urgency, item criticality, historical usage trends, geographical proximity, transfer cost, and expected risk reduction. These parameters are normalized and aggregated into a composite priority score to rank feasible redistribution actions. The system further integrates three analytical components: a Shortage Probability Predictor, an Idle Capital Risk Index, and a Cross-Project Resilience Indicator. An event-driven workflow with QR-enabled chain-of-custody tracking ensures traceability and auditability.

Prototype validation is conducted using synthetic multi-project datasets under simulated disruption scenarios, including demand spikes and supply delays. The results indicate that CIRIS effectively identifies surplus–shortage relationships, prioritizes reallocation decisions, and improves internal resource utilization while reducing dependency on emergency procurement.

CIRIS extends conventional inventory systems into a structured risk intelligence framework for multi-project environments, providing a scalable foundation for enterprise deployment and future empirical validation.