"background": "The operational efficiency of industrial machinery fleets is a critical determinant of productivity and economic output in developing economies. In Nigeria, a lack of robust, quantitative methodologies for evaluating the impact of systematic interventions on fleet performance has hindered evidence-based asset management. ", "purpose and objectives": "This study aims to develop and apply a rigorous econometric framework to quantify the causal effect of a structured maintenance and telematics implementation programme on the operational efficiency of selected industrial machinery fleets. ", "methodology": "A quasi-experimental difference-in-differences (DiD) model was employed. Panel data from treatment and control groups of heavy machinery fleets were analysed. The core model is specified as Y{it = \0 + \1 + \2 + \ (\) +, where Yit is the efficiency metric. Inference is based on cluster-robust standard errors. ", "findings": "The DiD estimator (\) indicated a statistically significant positive effect of the intervention. Fleets under the programme demonstrated a 17. 5% increase in overall equipment effectiveness (OEE) compared to the control group, with the effect significant at the 1% level (95% CI: 12. 1% to 22. 9%). ", "conclusion": "The application of a DiD model provides a credible methodological advance for isolating the causal impact of engineering management interventions in an industrial setting, confirming that structured programmes can yield substantial efficiency gains. ", "recommendations": "Industrial asset managers should adopt causal inference techniques like DiD for programme evaluation. Policymakers are encouraged to support the rollout of integrated telematics and preventative maintenance frameworks, informed by such empirical analysis. ", "key words": "Difference-in-differences, causal inference, fleet efficiency, maintenance engineering, industrial machinery, Nigeria", "cont
C. A. C. Okonkwo (Mon,) studied this question.