{ "background": "Power-distribution infrastructure in many developing nations suffers from chronic inefficiencies, leading to substantial technical and commercial losses. Systematic evaluation of interventions to modernise this infrastructure is often hindered by a lack of robust, quasi-experimental analytical frameworks within engineering project assessment.", "purpose and objectives": "This case study aims to methodologically evaluate the impact of a large-scale equipment modernisation programme on the technical efficiency of a national power-distribution network. Its objective is to quantify causal efficiency gains attributable to the intervention using a rigorous econometric approach adapted for engineering systems analysis.", "methodology": "A difference-in-differences (DiD) model is employed, treating the phased rollout of new transformers and switchgear as a natural experiment. The core statistical model is $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\cdot \\text{Post}t) + \\epsilon{it}$, where $Y{it}$ is the technical loss percentage for substation $i$ at time $t$. Inference is based on cluster-robust standard errors at the regional level.", "findings": "The DiD estimator ($\\delta$) indicates a statistically significant reduction in average technical losses of 4.2 percentage points (95% CI: 3.1 to 5.3) in treated substations relative to the control group. This represents a 22% relative improvement from the pre-intervention mean loss level in the treatment group.", "conclusion": "The application of the difference-in-differences model provides credible, causal evidence that the targeted equipment modernisation substantially improved the technical efficiency of the distribution network. The methodology demonstrates the value of quasi-experimental design for isolating the impact of engineering interventions in complex, real-world infrastructure systems.", "recommendations": "Future infrastructure upgrade programmes should incorporate phased implementation to facilitate rigorous impact evaluation. Engineers and project planners should adopt