Automation and Analysis: Data-Driven Strategies Improve Utility Processes and Analyze Performance at WSSC Water

Our world is driven by data across all industries, and the water sector is no exception. This ranges from enterprise systems that have been in place for decades to smart systems that are generating data at an exponential rate. It is increasingly important to incorporate practices to make sound decisions from these systems and implement controls to ensure trusted data. WSSC Water completed efforts to identify processes to improve their data-driven decision-making, and this abstract will present two strategies used to improve their performance across many departments through automation, standardization, and visualization of data. Strategy 1: Enterprise Data Warehousing: A large portion of the data used by decision makers resides in systems of record that are operated by their functional teams. While this data is usually accurate and up to date, it requires an expert from the team to extract it from the system or understand the data that is produced. It is also more granular than decision makers require, and the teams reporting on it consistently aggregate it to produce the intended results. To address these issues, WSSC Water automated the creation of datasets in these functional groups, all of which were a part of their Enterprise Data Warehouse. In the use case for this strategy, they will show the automated Commission Performance Report and Human Resources Dashboards. These items reduced the time spent developing recurring reports, leveraging Power Bi for automated and interactive reporting. Strategy 2: Non-Enterprise Data Management and Application Development: Unlike the enterprise data, WSSC Water identified many users who are managing critical data in their own spreadsheets or other tools. To standardize and automate some of the processes, they worked with these users to provide low-code platforms to manage data in their existing IT infrastructure. These tools included the development of SharePoint data-structures, Applications and Workflows to allow users to edit and maintain datasets in a collaborative environment, with the increased auditability that these tools provide. In the use cases for this strategy, they will show the Transition Plan Tracking Application and Community Investment/Engagement Application. These converted existing series of over ten spreadsheets into a single data source, provided a low-code application for the teams to enter data, and Power Bi Dashboards for reporting. The combination of these two strategies allows groups to take small steps into the world of data-driven decision making. Teams are beginning the process with Strategy 2 by standardizing their reporting, with the intent to be automated into an enterprise solution under Strategy 1 in the future. In the past, tools such as the ones outlined in these strategies were limited to IT Departments and professional programmers. With the advent of modern data management strategies, they are much simpler to implement and maintain, but still in line with IT standards and supported by their department once they are in production. In the end, WSSC Water identified significant time savings, data quality, and visualization capabilities as a result of taking a data-driven approach to managing some of their manual efforts.