This paper presents a methodological advancement in water utility efficiency assessment through Mamdani fuzzy inference, designated AFLEE. Building upon Eldidy (2012) research, the method addresses the failure of conventional metrics to account for socioeconomic context. The study extends the said research formulation in three directions: expanded classification with four-category output membership functions in the Demand FIS providing monotonic income-elastic allocation, integration of Debt-to-Revenue as an exogenous efficiency input, and validation across seven utilities on four continents. Results reveal exogenous efficiency ranging from 40.2% (SONEB) to 73.5% (Ghana Water) before debt adjustment, declining further when financial leverage is incorporated. The Tariff Index emerges as the dominant exogenous determinant, while the Debt-to-Revenue ratio exposes channels through which leverage conceals Non-Revenue Water. These findings demonstrate that meaningful benchmarking requires integration of economic reality within methods capable of handling linguistic uncertainty. This preprint is submitted ahead of peer-reviewed journal publication. The AFLEE methodology, FIS design, data interpretation, and all scientific conclusions are entirely the author's own. Full reproducibility is supported through the formal mathematical specification and algorithmic implementation provided in the appendices.
Nezar Eldidy (Sun,) studied this question.