Web-based Performance Benchmarking Data Collection and Preliminary Analysis for Drinking Water and Wastewater Utility
High-quality drinking water and wastewater systems are essential to public health, business, and quality of life in the United States. Even though the current performance of these systems is moderate, the concern is about the future performance. Planning can be done for improvement once the current performance of utilities is evaluated, and areas with a scope of improvement are identified. Benchmarking and performance evaluation are key components in the process of continuous improvement for utility's performance. Benchmarking helps utilities make policies and programmatic decisions that reduce operational expenses and increase productivity by understanding areas of underperformance, understanding customer needs, developing future plans, and setting goals. This study establishes a strong case for implementing benchmarking methodologies among utilities to evaluate and improve performance.
There are many initiatives on performance benchmarking of utilities but a few of them focuses on one or few area of performance. There are a few initiatives which use subjective indicators. Additionally, consultants visit the utilities for performance evaluation. This research focuses on creating a web-based benchmarking platform for performance evaluation using holistic and quantitative indicators. Practical and robust methodologies are used and the research presents the current performance comparisons among utilities for areas that impact overall utility's performance. Web based benchmarking consists of two major parts -- data collection and result visualization. A major contribution from this study is the creation of an online performance benchmarking database. With time more data will be collected which will provide utilities an access to a better database for performance evaluation. The future work in this research will be analyzing the data and results for each participant for each set of indicators, and finding possible reasons for under performance, followed by suggesting solutions for improvement using the best practices.