Manufacturing plants in Ethiopia have been identified as critical sectors for economic growth. However, yield improvements often face challenges due to varying operational conditions and environmental factors. The study employs a mixed-method approach combining quantitative data from multiple plants with qualitative insights from interviews. Statistical models are used to analyse yield data while accounting for potential confounders. A significant proportion (72%) of the variance in yield improvement was explained by plant-specific operational parameters, highlighting the importance of tailored interventions rather than generic solutions. The quasi-experimental design proved robust in detecting meaningful yield improvements across different Ethiopian manufacturing environments. Future research should validate these findings with larger datasets. Manufacturing managers and policymakers are encouraged to adopt a data-driven approach informed by the insights from this study, particularly for targeting yield enhancement strategies effectively. Quasi-Experimental Design, Yield Improvement, Manufacturing Plants, Ethiopia The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.