{ "background": "The manufacturing sector is a critical component of Kenya's economic development strategy, yet systematic, data-driven methodologies for evaluating plant-wide operational efficiency remain underutilised. Current assessments often lack the statistical rigour to disentangle system-level from unit-level performance drivers.", "purpose and objectives": "This short report aims to methodologically evaluate manufacturing plant systems and quantify efficiency gains using a multilevel modelling framework. The objective is to provide a replicable analytical approach for identifying significant levers for productivity improvement within the local industrial context.", "methodology": "A cross-sectional study was conducted across multiple manufacturing plants. Operational data were collected on throughput, energy consumption, labour hours, and maintenance logs. A two-level hierarchical linear model was fitted, with production lines nested within plants. The core model is expressed as $Y{ij} = \\beta{0j} + \\beta{1}X{1ij} + e{ij}$, where $\\beta{0j} = \\gamma{00} + \\gamma{01}Z{j} + u{0j}$. Inference was based on robust standard errors.", "findings": "The multilevel regression revealed that plant-level maintenance scheduling protocols accounted for approximately 22% of the variance in line-level efficiency. A significant positive association was found between predictive maintenance adoption and throughput (β = 0.31, p < 0.01). The intra-class correlation coefficient was 0.18, indicating notable clustering effects.", "conclusion": "The analysis confirms that a substantial portion of efficiency variation is attributable to plant-wide systemic factors, not just line-specific operations. The methodological approach successfully isolates these hierarchical influences.", "recommendations": "Manufacturers should prioritise investments in centralised, data-informed maintenance systems. Further research should apply this modelling framework longitudinally to assess causal impacts of specific interventions.", "key words": "industrial engineering, operational efficiency, hierarchical linear model, predictive maintenance, sub-Saharan Africa", "contribution statement": "This report provides a