Integrating Digital Project Controls and Risk Mitigation Frameworks to Improve Decision-Making in Complex Civil Engineering Projects

Effective decision-making in complex civil engineering projects increasingly depends on the integration of digital project controls with advanced risk mitigation frameworks. This study investigates how unified cost schedule monitoring, real-time analytics, and automated risk evaluation improve project performance, forecasting accuracy, and operational resilience. Using multi-phase performance data, the research demonstrates consistent improvements in Cost Performance Index (CPI) and Schedule Performance Index (SPI), alongside significant reductions in risk exposure and performance variance after digital risk integration. The findings show that digitally enabled, feedback-driven control environments strengthen early-warning capabilities, reduce decision cycle times, and enhance cross-functional alignment across engineering and management teams. The study further identifies managerial, organizational, and technological enablers necessary for successful implementation, as well as policy and industry considerations related to data governance, interoperability standards, and regulatory compliance. Limitations associated with methodology, contextual applicability, and data constraints are acknowledged, and future research directions highlight the potential of advanced analytics, AI- driven risk prediction, and adaptive real-time decision systems. The study demonstrates that integrated digital project controls provide a robust foundation for improving decision-making, predictability, and risk resilience in complex civil engineering projects.