"background": "Manufacturing systems in developing economies often face chronic inefficiencies, yet rigorous, field-based evidence on the efficacy of targeted interventions remains scarce. Prior studies in the region have largely relied on observational data, limiting causal inference. ", "purpose and objectives": "This study aimed to quantify the causal impact of a structured process optimisation protocol on production efficiency within Ugandan manufacturing plants. The primary objective was to measure the treatment effect on overall equipment effectiveness (OEE). ", "methodology": "A randomised field trial was conducted across 62 medium-scale manufacturing facilities. Plants were randomly assigned to treatment (implementation of a lean manufacturing protocol) or control groups. Efficiency was measured using OEE over a six-month period. The treatment effect was estimated using a linear mixed-effects model: Y{it = \0 + \1 Treatmenti + \ Xit + \ +, where \ denotes plant-level random effects. Robust standard errors were clustered at the plant level. ", "findings": "The intervention yielded a statistically significant increase in mean OEE. Treated plants achieved a 14. 2 percentage point gain in OEE (95% CI: 9. 8, 18. 6; p < 0. 001) relative to the control group. The largest efficiency improvements were observed in the performance and quality components of the OEE metric. ", "conclusion": "The randomised trial provides robust causal evidence that systematic process interventions can generate substantial efficiency gains in this industrial context. The results demonstrate the viability of field-experimental methods for engineering research in manufacturing systems. ", "recommendations": "Manufacturing practitioners should adopt evidence-based, incremental process protocols. Policymakers supporting industrial productivity programmes should incorporate randomised evaluation designs to validate intervention efficacy before scaling. ", "key words": "randomised controlled trial, manufacturing efficiency, lean production, overall equipment effectiveness, industrial engineering, sub-Saharan Africa", "contribution statement": "This paper provides the first
Nakato Kigozi (Thu,) studied this question.