Digital transformation is within reach for many wastewater systems
Key Highlights
- Prioritize data quality and establish governance practices to maintain accurate, reliable, and usable information over time.
- Engage staff early in the process by making data accessible and useful, fostering trust and facilitating adoption of digital workflows.
- Adopt a phased, crawl-walk-run approach to incrementally build digital twin capabilities, reducing risk and avoiding operational disruption.
- Focus on continuous improvement, leveraging existing data and systems to enhance visibility, analysis, and predictive capabilities over time.
Most utility managers are aware of the benefits digital twins can provide: reducing sanitary sewer overflows, service interruptions, and permit violations while improving energy efficiency and long-term capital planning. But they often fear implementation will be too complex. They’re unsure if their existing systems produce the volume of data they need to make a digital twin useful. Even if they have the data they need, it is likely spread across multiple applications in different formats with varying naming conventions. Bringing it all together accurately can feel like an overwhelming task.
The good news is that most utilities have enough data in their current systems to get value out of a digital twin right now, and they can scale their systems over time to increase the value. Early on, the primary benefit of their digital twin is increased visibility into plant performance. Data quality is validated, and it becomes more accessible. Operators develop greater confidence in the information available to them; teams spend less time searching for information and more time acting on it. Over time, a utility can integrate more data into the digital twin and see operational patterns take shape. They can perform more sophisticated analysis of their existing operational challenges, making real gains in efficiency and cost reduction through more-informed decisions.
Eventually, they will be able to predict potential challenges (rather than merely reacting to them), using the digital twin’s capabilities in predictive analytics, scenario evaluation, and operational forecasting. But utilities do not have to accomplish all these goals at once. Following a phased approach like the one presented here can help utilities make meaningful progress as their budget and capacity allow. This is critical because the importance of data will only grow as expectations around resilience, regulatory compliance, operational efficiency, and workforce continuity evolve. The sooner utilities start their path toward digital transformation, the more prepared they will be.
Start with the problem to solve, not technology
A common mistake that an organization can make when beginning a digital initiative is starting with the technology itself rather than the operational outcomes that they are trying to achieve. For some plants, the priority may be improving process consistency or reducing permit compliance risk. Others may be focused on energy consumption, aeration optimization, nutrient removal performance, asset reliability, workforce continuity, or improving visibility into plant operations. Some utilities may simply want operators and supervisors to spend less time searching for information and more time using it.
Clearly defining and communicating operational goals and the priority of each goal creates alignment across departments and helps ensure that future investments in technology and a digital twin remain tied to measurable outcomes rather than becoming isolated technology projects. Not every system or process needs to be digitized immediately or integrated into a digital twin right away. In many facilities, focusing on a few high-value operational areas can provide meaningful early improvements while helping staff become more comfortable with digital focused data-driven workflows.
Build trust in the data
Before advanced analytics or digital twin capabilities can provide value, utilities must first trust the information being used. For many, this is the most important step in the entire process. SCADA systems already provide significant operational insight, but data quality and structure vary widely between facilities. Tags may be inconsistently labeled, sensors may not be routinely validated, and historical data may not be retained in a useful format. Operators may rely heavily on institutional knowledge because system data does not always reflect real-world conditions accurately.
Improving confidence in operational data often begins with relatively straightforward activities, such as:
- Taking an inventory of the items, hardware, processes and software that capture the data
- Reviewing sensor reliability and calibration practices
- Standardizing naming conventions across systems
- Cleaning up duplicate or outdated tags
- Ensuring historical data retention is sufficient for analysis
- Verifying that critical process information can be exported or integrated when needed
- Aligning operational data with laboratory results and process conditions
Laboratory information is particularly important in wastewater treatment because it provides context for process performance that operational systems alone may not capture. Yet lab data frequently exists separately from SCADA and operational trends. Connecting these pieces begins creating a more complete operational picture.
Asset and maintenance data also play a major role. Maintenance systems often contain valuable information about equipment condition, recurring failures, and lifecycle trends. Integrating operational and maintenance perspectives can support more proactive decision-making and help utilities better understand how process conditions affect equipment performance over time.
At this stage, the objective is not perfection. The goal is foundationally understanding what data is available and then creating enough consistency, structure, and confidence that the information can reliably support operational decisions.
Integrating operational and maintenance perspectives can support more proactive decision-making and help utilities better understand how process conditions affect equipment performance over time.
Establish data governance
As wastewater facilities improve their operational data, some questions arise that need to be addressed. Who is responsible for maintaining data quality? Who updates naming standards? Who validates instrumentation? Who ensures that process changes are reflected consistently across systems? Who manages historical information retention? Without clear ownership and documented and enforced governance, data quality often degrades over time.
Many utilities already have capable staff managing these responsibilities informally, but successful long-term digital strategies require greater structure and consistency. Establishing governance does not need to become bureaucratic or overly complex. Often, the most effective governance models are practical and operationally focused.
Simple improvements such as the following can make a significant difference:
- Assigning responsibility for maintaining specific systems or datasets
- Establishing standard naming conventions
- Creating procedures for updating operational tags and records
- Defining how data is validated and reviewed
- Aligning departments around shared operational information
- Ensuring licensed products are up to date and allow access (such as through an open API)
- Establishing a communication cadence to ensure all departments are aware of each other’s data responsibilities and outcomes.
The goal is to ensure that information remains accurate, usable, and sustainable over time. Utilities that establish even modest governance practices early often progress much more smoothly as they expand digital capabilities later.
Include your team in the process for operational alignment
Technology initiatives in wastewater facilities succeed or fail largely based on how well they fit into daily operations. The most successful digital efforts are those that help staff focus on higher-value operational work, reduce uncertainty, and make decisions more confidently rather than introducing additional complexity. Operators, maintenance personnel, laboratory staff, engineering teams, and supervisors all interact with information differently. If new systems or workflows increase complexity without providing obvious value, adoption becomes difficult.
For this reason, preparing for a digital twin must include the people who operate and maintain the facility. An effective approach is to focus on making information easier to access, easier to understand, and more useful in everyday work. For operators, that may mean improved visibility into process trends, alarms, and process responses. For maintenance teams, it may involve better understanding of equipment performance patterns and recurring operational issues. For supervisors and managers, it may provide clearer reporting, stronger situational awareness, and improved planning insight. When digital tools are implemented thoughtfully, they can help reduce guesswork, improve consistency, and make day-to-day operations more manageable. Teams spend less time searching for information, manually compiling reports, or reacting to unexpected issues and more time focusing on proactive operational improvements.
Utilities should also recognize the workforce realities facing the industry. Many wastewater facilities are managing staffing shortages while also preparing for the retirement of experienced personnel who possess decades of institutional knowledge. In many plants, critical operational understanding still exists primarily in the experience of long-time operators rather than in accessible systems or documented workflows. Improved data practices and connected digital workflows can help preserve that operational knowledge and make it easier to transfer to newer staff. Historical trends, process responses, alarm histories, and maintenance patterns become easier to understand and use when information is organized and accessible. This can significantly reduce onboarding time for newer personnel while improving operational consistency across shifts and departments.
This is another reason phased adoption is so important. As staff become more familiar and comfortable with data-driven tools, confidence grows naturally. Over time, teams begin relying less on disconnected spreadsheets or tribal knowledge and more on accessible operational insight. Digital transformation becomes less about implementing technology and more about improving how people work.
Scale using a crawl-walk-run approach to digital readiness
Because a digital twin is a long-term operational asset rather than a static implementation, a crawl-walk-run framework provides a practical path for ongoing growth, refinement, and expanded functionality over time. This allows utilities to build capability incrementally while reducing risk and avoiding disruption.
Crawl: Establish reliable operational visibility
The crawl phase focuses on strengthening the operational foundation while beginning to connect available systems and data sources into the digital twin wherever practical. At this stage, utilities concentrate on improving data quality, organizing information, validating instrumentation, standardizing naming conventions, and increasing confidence in existing systems. Operational visibility becomes the priority, but the effort is already contributing to the long-term digital twin environment rather than creating standalone or temporary workflows.
Facilities may begin developing dashboards, trend reporting, and simplified performance views that help operators and managers better understand plant conditions in near real time. Existing SCADA, GIS, hydraulic model, sensor, or asset information can begin feeding the digital twin incrementally as systems become validated and ready for integration. Most importantly, the organization begins creating trust in the information. This phase often delivers immediate operational value because teams spend less time searching for information and more time acting on it. Operators and supervisors develop greater confidence in the information available to them, supporting faster, more consistent, and more proactive operational decision-making while laying the groundwork for continued digital twin maturity over time.
Walk: Integrate systems and improve analysis
As the operational foundation becomes more reliable, the utility focuses on expanding system connectivity, increasing data flow into the digital twin, and improving operational analysis capabilities. Additional systems such as laboratory information management systems, maintenance platforms, asset management tools, and process data sources are integrated and aligned. Dashboards, alerts, and reporting become increasingly valuable because the underlying information is more consistent, connected, and trusted across the organization.
With more systems contributing to the digital twin environment, utilities can begin identifying operational patterns and relationships that were previously difficult to detect. This may include process inefficiencies, recurring maintenance concerns, energy usage trends, operational responses to changing conditions, or subtle indicators that suggest emerging issues before they escalate into larger operational or compliance challenges.
At this stage, the digital twin begins transitioning from primarily a visibility tool into a more active operational support system. Utilities typically gain stronger situational awareness, improved collaboration across teams, and more informed decision-making capabilities. Staff confidence also tends to increase significantly during the walk phase as the practical value of connected data and improved operational insight becomes more evident in day-to-day operations.
Run: Enable advanced digital twin capabilities
As systems mature and data quality improves, more advanced capabilities become possible. Facilities can begin exploring predictive analytics, scenario evaluation, operational forecasting, and more dynamic representations of plant behavior. Historical and real-time information can be leveraged together to support more proactive operations. This is where digital twin capabilities truly begin to emerge.
Rather than functioning as a separate technology project, the digital twin becomes an enduring part of the utility’s operational strategy, continuously improving as additional systems, data sources, and insights are incorporated.
This steady progression allows organizations to improve operational maturity in a way that fits naturally within existing workflows while demonstrating meaningful value early in the process.
Sustainable progress is more important than rapid deployment
A common concern surrounding digital transformation is the belief that utilities must modernize everything quickly in order to realize value. In practice, a phased and incremental approach often proves more practical and sustainable, allowing wastewater facilities to strengthen operations, improve data quality, and expand capabilities over time without overwhelming staff or disrupting critical plant operations.
This steady progression allows organizations to improve operational maturity in a way that fits naturally within existing workflows while demonstrating meaningful value early in the process. It also gives utilities the flexibility to prioritize investments based on operational needs and long-term objectives rather than reacting to technology trends. This approach is particularly important for small and mid-sized wastewater utilities that may face staffing, funding, or infrastructure constraints.
Meaningful progress does not require implementing every possible digital tool immediately. Many facilities can create substantial value simply by improving data organization, increasing operational visibility, and aligning workflows across departments. As maturity increases, additional capabilities can be introduced strategically and sustainably.
Prepare for the future without overcomplicating the present
Digital technology in the wastewater industry continues to evolve rapidly especially with the popular spread of ideas and capabilities such as artificial intelligence. Expectations around resilience, regulatory compliance, operational efficiency, sustainability, and workforce continuity are increasing. Data will continue playing a larger role in how treatment facilities operate and make decisions.
Digital twins will likely become increasingly common within the industry, but utilities do not need to view them as an all-or-nothing initiative. Facilities that focus today on improving data quality, operational visibility, governance, and staff alignment are already taking meaningful steps toward future readiness. These efforts provide immediate operational benefits while also positioning organizations to adopt more advanced capabilities when the timing is right.
Most importantly, this approach reduces risk while helping utilities build long-term organizational confidence in digital practices. Rather than viewing digital transformation as a major technology initiative owned only by IT or engineering, facilities begin treating data and operational visibility as part of everyday plant management. Instead of introducing disruptive technology projects that strain already limited resources, utilities can progress at a pace that aligns with their operational realities and organizational capacity.
For wastewater utilities, the journey toward a digital twin begins long before advanced modeling, predictive analytics, or artificial intelligence enter the conversation. It begins with an understanding of existing data and a prioritized plan to improve operational visibility, organize information, establishing ownership, and help staff build confidence in more connected workflows.
By focusing on readiness rather than rushing toward technology, wastewater facilities can make practical improvements today that strengthen operations while laying the groundwork for more advanced digital capabilities in the future. The result is a more informed, connected, and resilient operation capable of adapting to the increasing demands facing the wastewater industry.
About the Author
Melissa Rohland
Director of Strategic Programs, HRG
Melissa Rohland, PE, PMP, is the director of strategic programs at Herbert, Rowland & Grubic, Inc. (HRG), where she leads digital strategy initiatives focused on helping utilities improve operations through data, technology, and process alignment. She works with water and wastewater organizations to implement practical, scalable approaches to digital transformation and operational modernization.