Abstract
Small to medium sized water utilities face serious challenges to meet broad sustainability objectives, because of technical, human and financial constraints and limited involvement in the inter-utility benchmarking. Most of these utilities are unable to address the performance gaps for various functional components, such as personnel, operational, financial, etc., of their water supply systems and rely on emergency response. Even if the information obtained from such benchmarking process is available, the outcome (indices) showing performance of these components, at the utility level, is useful for top level management. The operations management is more interested in the performance of sub-components (under each functional component) of the water supply systems within the utility. An intra-utility performance management model is conceptualized and developed for effective decision making at both the levels. A hierarchical based top-down approach initiates from overall sustainability objectives at the top, followed by primary and secondary performance measures of the sub-components, and indicators (basic building blocks) receive inputs from data/decision variables at the bottom. The model assesses the performance of each component and sub-component as ‘high’, ‘medium’, or ‘low’. Fuzzy based technique has been employed to deal with uncertainty issues due to data limitations and vagueness in expert knowledge. Sensitivity analysis helped to rank the indicators for their contribution in decision making. The model is implemented for a medium sized utility containing three sub-systems in the Okanagan Basin (BC, Canada). The results demonstrate the model's practicality to efficiently achieve sustainable performance in small to medium sized water utilities.
•We developed a model for performance management of small to medium sized water utilities.•The model can evaluate functional components of different water supply systems in a utility.•The model can handle the uncertainties in data variables and knowledge base.•Sensitivity analysis ranks the indicators for their contribution in a functional component.•The model results can help the utility managers to prioritize their investments.