There is a version of sewer management that feels familiar to most utilities: respond to a blockage, clean the line, move on. Respond to an overflow, document it, repair what failed, move on. The cycle repeats, the backlog grows, and the system deteriorates faster than the maintenance program can address it.
That model has a cost, and it is not only the direct cost of emergency response and EPA penalties, real as those are. It is the compounding cost of deferred conditions becoming active failures, of infrastructure declining faster than budgets can support, and of regulatory relationships that grow more confrontational over time.
Charlotte Water shows what the alternative looks like. Managing a 4,400-mile sanitary sewer system serving more than a million people, the utility entered an administrative order with the EPA after a record number of SSOs. Over the following decade, using data-driven inspection to direct root control, follow-up inspections, and trenchless rehabilitation, Charlotte Water reduced annual reported SSOs from 500 to 155. ITpipes serves as the CCTV inspection and data management backbone of that program, with inspection data integrated into the utility’s work order system so that events can trigger automatic work assignments. The decline was not accidental. It was the outcome of a sustained, structured program built around knowing the system.
Full story: Driving Down Overflows: Charlotte Water’s Data-Driven Sewer Strategy
Risk Assessment Is the Starting Point
A proactive program does not treat all infrastructure equally, because not all infrastructure carries equal risk. Pipes that are older, near sensitive waterways, carrying higher flow, or built from materials known to deteriorate are more likely to produce an SSO than newer infrastructure in low-risk service areas.
A structured risk assessment assigns inspection and maintenance priority based on those factors, and it gives the utility a defensible basis for resource allocation. When budget questions arise, the answer shifts from “why are we spending money on this pipe” to “here is what the data shows about risk in this area, and here is how we are addressing it.” The output is an inspection prioritization framework: which areas get inspected most often, which get routine attention, and which can run on a longer cycle. A general starting point:
- High-risk areas: annually or bi-annually
- Medium-risk areas: every 3 to 5 years
- Low-risk areas: every 5 to 10 years
These are starting parameters, not rigid rules, and they should be adjusted as inspection data accumulates and conditions evolve.
What a Cleaning and Inspection Program Actually Requires
Risk-based prioritization tells you where to focus. Executing the program requires consistent processes, trained staff, and the tools to capture and use what inspections reveal.
CCTV pipeline inspection remains the primary tool for internal condition assessment, producing the visual record that supports defect coding, rehabilitation planning, and trend analysis. Cleaning programs, whether jet-vac, mechanical, or chemical depending on the condition, keep capacity available and prevent the FOG and debris accumulation that creates blockage conditions.
The most common failure point in inspection programs is not execution. It is what happens to the collected data afterward. Footage reviewed once and filed, defect codes stranded in a spreadsheet disconnected from work orders, and condition assessments that never reach capital planning all represent a return on investment that never materializes.
Turning Footage Into a Prioritized Action List
Inspection footage only reduces SSOs if it produces decisions. The bridge between the two is standardized condition coding, and for most North American collection systems that standard is NASSCO’s Pipeline Assessment Certification Program (PACP).
PACP scores each observed defect on a 1 to 5 scale, where a grade 1 is minor and a grade 5 represents a defect at or near failure. Critically, it separates structural defects, such as cracks, fractures, and collapses, from operations and maintenance defects, such as roots, grease, and debris. That separation matters because the two point to different responses. A segment dominated by grade 4 and 5 structural defects is a rehabilitation or replacement candidate. A segment with high O&M scores from roots or grease is a cleaning and root-control candidate, often resolved without capital spend.
This is what makes condition coding actionable rather than archival. Instead of a binary “inspected or not,” engineers can rank segments by quick structural and O&M ratings, target the worst grades first, and build a defensible work plan that distinguishes a high-cost lining project from a routine jet-vac pass. When those scores are tracked over time, they also reveal deterioration rates, which is the input capital planning needs to forecast failures before they become overflows.
The practical challenge is consistency. PACP coding is only as reliable as the coder, and manual review of large volumes introduces variability and backlog. AI-assisted inspection coding addresses both by flagging and pre-coding defects automatically, keeping grading consistent across crews and letting a smaller team process more footage without sacrificing the score integrity that prioritization depends on.
Data Management as an Operational Function
Modern inspection data management platforms centralize what would otherwise live in silos. Inspection records, defect coding histories, work order status, GIS integration, and asset management data become accessible in a single environment that can be queried to surface trends, identify deteriorating assets, and support capital prioritization.
This changes how maintenance decisions get made. Instead of relying on crew memory of which areas have historically been problematic, supervisors can query the system. Instead of building capital lists from what failed last year, engineers can identify assets approaching the end of their serviceable life before they fail.
Connecting Inspection Data to a Defensible Capital Plan
The long-term goal is not to eliminate every SSO immediately, which is not realistic given the deterioration in most collection systems. The goal is continuous improvement: to know more about the system each year, allocate resources to the highest-risk areas, and reduce the frequency and severity of overflows over time.
That improvement depends on the connection between inspection data and capital investment, and this is where many programs fall short. Capturing condition scores is not the same as producing a fundable capital plan. The strongest programs close that gap by pairing condition data with deterioration and hydraulic modeling, which turns a snapshot of current condition into a forecast of future risk and the most accurate path from inspection results to a board-ready capital plan. Pipe defect trends and failure forecasts feed directly into rehabilitation and replacement project planning, and the spending becomes traceable to condition data rather than reactive to failures, which is exactly what regulators and governing boards want to see.
Public Transparency Is Part of the Program
Ratepayers fund the capital investments a serious SSO reduction program requires, and that funding relationship depends on trust. Utilities that communicate proactively about system condition, the challenges they are managing, and the progress they are making are in a far stronger position when rate increases become necessary. Public dashboards, annual infrastructure reports, and community meetings convert inspection data and capital plans into accessible information, and they reinforce that SSO management is a shared commitment to public health and the environment rather than a compliance exercise.
The Program Never Ends, and That Is the Point
A proactive SSO reduction program is not a project with a completion date. It is an ongoing commitment that gets more effective as data accumulates and processes mature. Utilities that sustain the effort, even when SSO counts are low, keep the system knowledge that prevents backsliding.
The investment is real: staff time, inspection equipment, data management tools, and the discipline to keep the program running. But the comparison is not a program with no investment. It is constant emergency response, mounting fines, consent decrees, and infrastructure that deteriorates faster than the budget can address. As Charlotte Water’s decade of results shows, the math consistently favors prevention.
Next step: See how ITpipes connects CCTV inspection, PACP condition coding, and capital planning in one environment. Talk with our team about building the inspection-to-capital-plan feedback loop your collection system needs.
