Abstract
{ "background": "Manufacturing systems in developing economies face significant operational risks, yet rigorous methodological frameworks for evaluating systemic interventions are scarce. The Senegalese industrial sector, a key regional hub, lacks empirical studies quantifying the efficacy of engineering-led risk reduction programmes.", "purpose and objectives": "This study aims to develop and apply a quasi-experimental econometric model to methodologically evaluate the causal impact of a structured engineering safety and maintenance protocol on operational risk within manufacturing plants.", "methodology": "A difference-in-differences (DiD) model was employed, leveraging panel data from treatment and control groups of plants. The core specification is $Y{it} = \\alpha + \\beta (Treati \\times Postt) + \\gammai + \\deltat + \\epsilon{it}$, where $Y_{it}$ is the plant-level risk index. Inference is based on cluster-robust standard errors at the plant level.", "findings": "Implementation of the protocol caused a statistically significant reduction in the composite risk index. The average treatment effect on the treated (ATT) was an 18.5% reduction (95% CI: 12.1% to 24.9%). The parallel trends assumption was validated using pre-intervention data.", "conclusion": The methodological application of DiD provides robust, causal evidence that the engineered system intervention substantially mitigated operational risks. This confirms the value of quasi-experimental designs for post-hoc evaluation in structural engineering management.", "recommendations": "Manufacturing plant managers should adopt similar evidence-based protocols. Policymakers and engineering practitioners are encouraged to integrate quasi-experimental evaluation frameworks into the planning stages of systemic interventions to rigorously measure impact.", "key words": "difference-in-differences, operational risk, quasi-experimental design, manufacturing systems, safety protocol, causal inference", "contribution statement": "This paper provides the first application of a difference-in-differences model to isolate the causal effect of an engineering system intervention on operational risk in a West African manufacturing