"background": "The optimisation of industrial machinery fleets is critical for productivity in developing economies, yet robust methods for quantifying the causal impact of fleet management interventions on operational yield are lacking. Existing evaluations often rely on simple before-and-after comparisons, which are vulnerable to confounding trends. ", "purpose and objectives": "This short report presents a methodological evaluation applying a quasi-experimental difference-in-differences (DiD) model to measure yield improvement from a systematic fleet management programme. The objective is to demonstrate a rigorous analytical framework for causal inference in industrial engineering contexts. ", "methodology": "We analyse panel data from processing plants, comparing yield (output per operating hour) in treatment and control groups before and after programme implementation. The core model is Y{it = \ + \1 + \2 + \ (\) +, where \ is the DiD estimator. Inference is based on cluster-robust standard errors. ", "findings": "The DiD estimator indicates a positive and statistically significant programme effect. The point estimate for \ is 8. 7 percentage points (95% CI: 5. 2, 12. 1), suggesting a substantial yield improvement attributable to the fleet management intervention. The parallel trends assumption, tested via lead terms, was not violated. ", "conclusion": "The difference-in-differences model provides a viable and more robust methodological alternative for evaluating capital-intensive engineering interventions compared to descriptive methods, effectively isolating the treatment effect from secular trends. ", "recommendations": "Industrial engineers and managers should adopt quasi-experimental evaluation designs, particularly DiD, for capital project appraisals. Future research should apply this model to different sectors and incorporate additional operational metrics. ", "key words": "difference-in-differences, causal inference, fleet management, operational yield, quasi-experimental design, industrial
Mwangi et al. (Wed,) studied this question.