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Data envelopment analysis (DEA) has been used for decades to investigate utility efficiency- and management-specific features. DEA has been extended in various industries with different models that consume different types of production variables to meet industry-specific efficiencies. However, the discernment of production variables and proper DEA models is still a problem in the water industry. Ratio information has been used in DEA for absolute data to assess utility efficiency- and management-specific features; using ratios in DEA for absolute data produces wrong efficiency results because the convexity axiom of DEA for absolute data is not satisfied. This study presents a collection of information and an assessment of DEA for absolute and ratio data to identify the strengths of the production variables and the DEA model that are appropriate for assessing utility efficiency- and management-specific features. The analysis shows that the use of ratio variables in DEA for ratios improves utility economics, the working environment, and the social trust dimension. HIGHLIGHTS DEA models and production variable selection.; Proper utility benchmarking and DEA model choices.; Efficient utility benchmarking.; Using performance indicators as production variables in DEA.; Efficiency comparison.;