Process-control systems are critical for optimising infrastructure project delivery, yet rigorous methodological frameworks for evaluating their cost-effectiveness in developing economies are scarce. This study aims to develop and apply a panel-data econometric model to methodologically evaluate the cost-effectiveness of process-control systems implemented in civil engineering projects. A longitudinal dataset of project metrics was constructed. Cost-effectiveness was estimated using a two-way fixed effects model: $C_{it} = \alpha + \beta P_{it} + \mu_i + \lambda_t + \epsilon_{it}$, where $C_{it}$ is normalised cost and $P_{it}$ is a process-control index. Inference was based on cluster-robust standard errors. The adoption of advanced process-control systems was associated with a statistically significant 18.5% reduction in average project cost overruns (95% CI: 12.2% to 24.8%). This relationship was robust to model specification and heterogeneity across project types. The panel-data approach provides a rigorous methodological framework for evaluation, confirming that systematic process control is a significant determinant of financial performance in project delivery. Project sponsors and contractors should prioritise investment in integrated process-control technologies. Further research should standardise the core metrics used in the evaluation index. project management, econometric analysis, fixed effects, infrastructure, West Africa This paper provides a novel panel-data methodology for engineering project evaluation, creating a transferable model for quantifying the return on investment in process-control technologies.