{ "background": "Process-control systems are critical for operational safety and efficiency in industrial and infrastructure projects. In Kenya, the adoption and performance of such systems have been variable, with a lack of robust empirical analysis quantifying their impact on engineering risk.", "purpose and objectives": "This study aims to methodologically evaluate the effectiveness of modern process-control systems in reducing operational risks within the Kenyan engineering sector. The primary objective is to quantify the causal impact of system implementation on a composite risk index.", "methodology": "A quasi-experimental difference-in-differences (DiD) model was employed, analysing panel data from 42 sites. The treatment group implemented upgraded control systems, while the control group did not. The core model is specified as $Risk{it} = \\beta0 + \\beta1 (Treati \\times Postt) + \\alphai + \\gammat + \\epsilon{it}$, where robust standard errors were clustered at the site level.", "findings": "Implementation of modern process-control systems caused a statistically significant reduction in the composite risk index by 18.7 percentage points (95% CI: 15.2 to 22.2). The parallel trends assumption was validated, and results were robust to several sensitivity checks.", "conclusion": "The methodological application of DiD provides credible evidence that modern process-control systems are highly effective for engineering risk mitigation in the studied context. This underscores their value as a critical component of structural and industrial safety programmes.", "recommendations": "Engineering firms and regulatory bodies should prioritise investment in and certification of advanced process-control systems. Further research should investigate the cost-benefit analysis of specific system components and their long-term performance degradation.", "key words": "process control, risk reduction, difference-in-differences, engineering safety, Kenya, industrial systems", "contribution statement": "This paper provides the first application of a quasi-experimental difference-in-differences framework to isolate the causal effect of process-control systems on engineering risk in an African