Abstract
{ "background": "The drive for industrialisation in developing economies necessitates robust, context-appropriate methods for evaluating manufacturing systems. In Rwanda, a lack of empirical, comparative performance data hinders evidence-based investment and operational improvements in the engineering sector.", "purpose and objectives": "This study aimed to develop and apply a quasi-experimental methodology to measure and compare operational efficiency gains across a sample of manufacturing plants, isolating the effect of systematic interventions from external confounding factors.", "methodology": "A comparative, quasi-experimental design was implemented, pairing four treatment plants undergoing a defined lean manufacturing system intervention with four matched control plants. Performance was tracked via a composite efficiency metric over multiple periods. The core treatment effect was estimated using a difference-in-differences model: $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, with inference based on cluster-robust standard errors.", "findings": "Plants implementing the systematic intervention demonstrated a significant positive treatment effect. The estimated average efficiency gain attributable to the intervention was 18.7 percentage points (95% CI: 12.4, 25.0). Control plants showed no statistically significant change over the same period.", "conclusion": "The applied quasi-experimental design proved effective for isolating causal efficiency gains in a real-world manufacturing context, providing stronger evidence than observational benchmarks. Systematic interventions can yield substantial performance improvements.", "recommendations": "Manufacturing firms should adopt structured, evidence-based system evaluations. Policymakers and industry bodies are encouraged to support the deployment of such methodological frameworks to guide targeted industrial development strategies.", "key words": "quasi-experimental design, manufacturing systems, operational efficiency, difference-in-differences, industrial policy, lean production", "contribution statement": "This paper provides a novel application of a quasi-experimental, difference