Key performance indicators to explain energy & economic efficiency across water utilities, and identifying suitable proxies

Water companies consume up to 8% of global energy demand, at billions of dollars cost. Benchmarking of performance between utilities can facilitate improvements in efficiency; however, inconsistencies in benchmarking practices may obscure pathways to improvement. The aspiration was to conduct an unbiased efficiency comparison within a sample of 17 water only companies and water and sewerage companies in England and Wales, accounting for exogenous factors, whilst evaluating the accuracy of common proxies. Proxies were tested, and bias-corrected energy and economic efficiency scores with explanatory factors were analysed using a double-bootstrap data envelopment method. Bias correction altered the rankings of two companies for energy efficiency only. Results imply that on average, companies could reduce energy inputs by 91.7%, and economic inputs by 92.3%, which was symptomatic of the companies specialising in drinking water supply considerably out-performing combined water and sewerage companies. As exogenous influences were likely to be a factor in the disparity between the companies, five indicators were evaluated. The results varied but of note were average pumping head height, which displayed a significant negative effect for energy efficiency, and proportion of water passing through the largest four treatment works, that exhibited a significant negative effect on economic efficiency. Within proxy performance, population served for drinking water was an adequate replacement for volume of water produced, with results matching the core variable apart from two companies changing rank in the economic analysis. Conversely, length of water mains performed poorly when replacing capital expenditure, implying companies were on average 12.6% more efficient, resulting in ten companies changing their rank and causing explanatory variables to contradict direction of influence and significance. The findings contribute new insights for benchmarking, including how different types of water companies perform under bias-correcting methods, the degree to which factors affect efficiency and how appropriate some proxies are.