{ "background": "The adoption of advanced process-control systems in industrial infrastructure is a key development strategy, yet rigorous empirical evidence of their efficiency impact in sub-Saharan contexts is limited. Existing evaluations often lack robust counterfactuals, making causal attribution difficult.", "purpose and objectives": "This study aimed to quantify the causal effect of implementing modern process-control systems on operational efficiency within Uganda's industrial infrastructure sector, using a quasi-experimental design to isolate the intervention's impact.", "methodology": "A difference-in-differences design was employed, comparing efficiency metrics from six treatment sites before and after system installation against six matched control sites. Operational efficiency was measured via a composite index of energy consumption, throughput, and material waste. The primary analysis estimated the average treatment effect on the treated (ATT) using the model $Y{it} = \\beta0 + \\beta1 (\\text{Treat}i \\times \\text{Post}t) + \\beta2 \\text{Treat}i + \\beta3 \\text{Post}t + \\epsilon{it}$, with inference based on cluster-robust standard errors.", "findings": "The intervention yielded a statistically significant positive ATT of 17.3 percentage points (95% CI: 12.1, 22.5) on the composite efficiency index. The most pronounced gain was a 22% reduction in specific energy consumption, with material waste also decreasing substantially.", "conclusion": "Modern process-control systems can generate substantial and measurable efficiency improvements in the studied context. The quasi-experimental approach provides credible causal evidence often absent in technical appraisals.", "recommendations": "Infrastructure developers and policymakers should prioritise investments in process-control technologies, supported by robust monitoring and evaluation frameworks. Future system designs should be adapted to local operational constraints to maximise gains.", "key words": "process control, industrial infrastructure, quasi-experimental design, operational efficiency, difference-in-differences, sub-Saharan Africa", "contribution statement":