Abstract
Background and Understanding: Cape Fear Public Utility Authority (CFPUA) is a public water and wastewater utility that was created in July 2007 as a merger of the City of Wilmington, North Carolina and New Hanover County water and wastewater systems. CFPUA has a service population of over 200,000 customers and owns and operates two major water treatment plants and two wastewater treatment facilities with combined capacities of 42 mgd and 28 mgd respectively. To facilitate data driven decision making for utility operations and planning the Authority maintains a variety of enterprise software systems containing critical data, which reside either within on-premises IT architecture or in externally hosted environments. Through the Authority's strategic planning process, CFPUA identified the development of a Data Management Master Plan as an opportunity to establish a framework for data architecture that prepared the utility to effectively and efficiently leverage their data moving forward. This presentation documents the Data Management Master Planning process, including the drivers, the planning processes, road map to implementation, and lessons learned. An objective of the master planning process was to take a holistic look at existing utility data, data storage, and data security to develop a plan to unify the large volumes of utility data from a variety of sources to build an enterprise-wide business intelligence reporting platform. The goal of the reporting platform was to track key performance indicators and to identify relationships and patterns that are predictive of administrative and operational success. The data management planning process involves CFPUA's review of existing infrastructure and data management processes and development of standard procedures and infrastructure that support best practices of information and data management. Implementation of the data management plan would ultimately result in data analytics infrastructure that will enable the utility to understand the impact of processes, programs, and actions to allocate and prioritize resources effectively for the success of the utility. Master Planning Approach: Five core pillars defined as data governance, data quality, data integration, data storage and management, and data analytics, were identified as the foundation of an effective data management system. Each of the pillars needed to be addressed in the planning processes and measures of success were established early in the planning process to guide the evaluation of potential data frameworks. The Authority chose to approach the data management process in two phases, the first phase being the development of the master plan and a road map for implementation and the second phase being the actual implementation of the plan developed in Phase One. By clearly separating planning and implementation, CFPUA ensured that the vision and framework for the data architecture was in place and vetted prior to the implementation of the plan. Phase One of the master planning process was further divided into four key steps; understanding stakeholders, establish a data inventory, conduct a needs and gap assessment, and finally pulling it all together in the formalization of a master plan document. The first step in the process was understanding the data needs, vision, and concerns of CFPUA staff and end users. The Authority recognized that the ability to leverage insights from data universally impacted staff across disciplines and functional areas and therefore developed a user survey that was distributed to all staff, to provide an opportunity to participate in the planning process. The survey results provided useful insights about data uses, needs, and current limitations that were carried forward throughout the master planning process. To supplement the broadly distributed survey that was shared Authority wide, a more detailed survey was sent out to a focused audience of known stakeholders in the CFPUA data management system, including department leaders, IT staff, and data analysts. The more detailed survey went beyond feedback on end uses of data and evaluated business intelligence process needs and implementation timelines that were carried forward into the master planning process. The next step in the process was to establish a data inventory and understanding of the current data systems and architecture. This process began with discussions with IT representatives to map the current system architecture and develop a base of understanding of the current system. Understanding how data flows within the current system was the next step and was accomplished through group and individual meetings with key users of each individual software system used in the Authority. A day-long workshop was conducted to gather information from each department in the Authority and to provide stakeholders the ability to detail how they use existing software systems, the data that they use to inform their operations, and their current challenges in obtaining data or data flows. After a system architecture map was developed for current systems showing the current data pathways and flows, it was easier to visualize how data was being used across the Authority. It was also an instrumental component of performing the next step of the planning process which was conducting a data needs and gap assessment. Based on the information that was already gathered for key stakeholder and end user data needs, the master planning team could identify where gaps existed in the existing infrastructure that prevented or limited efficient and effective transfer and use of data across the organization. Recommendations for approaches to remedy these data gaps were then developed in a manner that the core pillars such as data quality and security were maintained. The final step in the planning process was the documentation of the results of the planning process in a formal document and distributing across the organization. The master plan provides a unified data management framework for generation and maintenance of quality, accessible data and advanced analytics. It includes illustrations of the current and desired states, a gap-analysis informed roadmap, and best practice policy and process references. When fully executed, the plan will enable analytic scripts, measures, visualizations, and applications tailored to CFPUA's departmental needs and workflows. The implementation Phase of this project is a future step that involves the establishment of the actual network infrastructure followed by training. The implementation schedule will be executed in accordance with the master plan which will prioritize implementation steps based on user need, cost, and overall benefit to the Authority. Each implementation step will also include a training plan including a recommended audience and training aids. Challenges and Lessons Learned: This presentation will conclude with challenges faced by the Authority as part of the data management planning process and lessons learned from how the Authority worked to address those challenges. One example is that the existing enterprise data systems presented the Authority with numerous challenges in data quality control, infrastructure maintenance, usability, accessibility, cybersecurity, and overall efficiency. Data was difficult to share, and staff had difficulty transmitting information across the utility. CFPUA faced challenges in maintaining their existing data infrastructure and data management processes as a result of growing volumes of data, siloed data, and increasingly diverse enterprise systems. With these challenges, CFPUA recognized the need for a Data Management Master Plan to provide a resilient, secure, maintainable data management system. Another key challenge faced by the Authority through the data management planning process was a resistance or hesitancy of staff to accept changes to the data management system. One example of this was a recommended transition from locally stored share file systems to cloud based storage systems. The presentation will address the methods and approaches of how CFPUA encouraged acceptance and the effectiveness of these techniques.
This paper was presented at the WEF/AWWA Utility Management Conference, February 13-16, 2024.
Author(s)E. Severt1, C. Bolton1, T. Devine2, M. Turner2, B. Stanford2
Author affiliation(s)Cape Fear Public Utility Authority 1; Hazen & Sawyer 2;
SourceProceedings of the Water Environment Federation
Document typeConference Paper
Print publication date Feb 2024
DOI10.2175/193864718825159281
Volume / Issue
Content sourceUtility Management Conference
Word count19