The Reactive to Proactive Roadmap: How to Build a Sewer Inspection Program Without Increasing Crew Size

Who this is for: Public Works and utility directors, engineers, field and operations supervisors, asset management leads, and GIS staff at small and mid-sized wastewater utilities that have never systematically inspected their collection system, own little or no CCTV equipment, and would rather contract the fieldwork than build a large crew. If you are starting with little or no inspection history and need a defensible plan for where to begin, this roadmap is for you.

What you will learn: A six-phase roadmap that takes a utility from reactive, emergency-driven repair to a proactive, data-driven maintenance program: how to build a risk-based prioritization model with data you already have, how to procure a simple CCTV-only contractor, how AI defect coding standardizes every inspection, how to establish your first pipeline health baseline and capital plan, and how to scale to full-system coverage and make proactive management permanent.

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Contents

Where the Roadmap Starts

This roadmap is written for a common situation: a utility that has never systematically inspected its collection system, owns no CCTV vehicles or equipment, and would rather contract the fieldwork than build a crew. That starting point shapes the whole program. All fieldwork is contracted, with zero capital investment in trucks or cameras. The contractor captures clean video but does not code defects. Every inspection is coded to NASSCO PACP centrally through AiDetect, so grading stays consistent across every crew you ever hire.

Each role owns part of running it. The Public Works Director is the executive sponsor and owns the proactive-management commitment. The Engineer leads risk-model design and reviews the coded data. The Field and Operations Supervisor coordinates contractor access and traffic control. The Asset Management Lead feeds condition scores into the CIP and CMMS. The GIS Lead builds the sewer network layer and publishes risk data to Esri ArcGIS. ITpipes runs the AiDetect coding, QA/QC, and reporting.

The Six-Phase Roadmap

The roadmap moves through six repeatable phases. Here is what each one accomplishes. The full guide includes the risk factors, contractor scope, pricing structure, PACP grade actions, KPIs, and the year-by-year implementation timeline.

Phase 1: Build the Risk-Based Prioritization Model

With no inspection record to draw on, you build a defensible order of work from data you already have. A weighted model of condition and consequence factors produces a tiered work plan, so the highest-risk pipe gets inspected first. The guide details the specific data factors, how to weight them, and the four-tier schedule.

Phase 2: Procure a CCTV-Only Contractor

The contractor’s job is clean footage and accurate metadata, nothing more. Keeping defect coding out of the field scope widens the bid pool and keeps grading consistent across every crew you hire. The guide provides the full scope of work, required metadata, and a contract and pricing structure you can adapt.

Phase 3: Process Inspections Through AI for Accurate, Standardized Coding Results

Every inspection runs through the same coding engine, which makes condition data comparable over time and defensible in front of a council, a regulator, or a court. AiDetect auto-codes defects to NASSCO PACP with certified experts reviewing low-confidence segments, so reviewer-to-reviewer variance disappears from the record. The guide walks through the full upload-to-export workflow.

Phase 4: Establish the Health Baseline and Capital Plan

The first full pass creates your first objective pipeline health baseline, where PACP structural grades map directly to capital plan actions. This is also where you calibrate the model against what the camera actually found. The guide includes the complete grade-to-action table and the calibration loop.

Phase 5: Scale to Full System Coverage

Each year repeats the same steps, better informed than the last, until the whole system has a first-pass baseline and the program shifts to a cyclical re-inspection schedule. The guide covers the annual loop and the coverage math for reaching a full baseline.

Phase 6: Institutionalize Proactive Management

What keeps the program from lapsing is measurement and a budget that funds it. The guide lays out the five KPIs that prove the reactive-to-proactive shift is working, plus the single budget move that makes proactive assessment permanent.

Start with the Phase You Are On

Whether you are assembling risk layers or already sitting on unprocessed footage, ITpipes SmartVision, AiDetect, CoreVision, and FieldVision fit the roadmap. AiDetect is the coding engine, CoreVision is the system of record where condition data, media, GIS, and rehab history live together, and SmartVision delivers the complete field-to-office solution. The absence of an inspection history is not a reason to wait. It is the reason to start with a defensible plan today.

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FAQs

Start with prioritization. The fieldwork comes second. Before a single camera goes in a pipe, decide which pipes to inspect first using data you already have, such as paving schedules, overflow history, emergency repairs, tree density, restaurant density, and pipe age. From there the sequence is straightforward: procure inspection services or crews, capture standardized CCTV footage, code every defect to a NASSCO standard, build a condition baseline, and set a repeatable annual cycle. Starting with a risk-based plan gives you a defensible order of work on day one, even with no inspection history.
The recognized best practice is condition assessment coded to a national standard: capture continuous CCTV video from manhole to manhole and grade every defect using NASSCO's Pipeline Assessment Certification Program (PACP) for pipes, MACP for manholes, and LACP for laterals. Consistency is the key. Every inspection should be graded the same way, every time, so condition data is comparable across crews and across years. That consistency is what makes the data usable for prioritizing repairs, planning capital, and defending decisions to a council or regulator.
When you have no inspection history, build a risk-based prioritization model from indirect indicators of condition and consequence. Weight factors such as upcoming paving, recent overflows, emergency repair history, root intrusion risk, grease contribution, and pipe age, then rank the system into tiers. Two conditions usually justify immediate inspection regardless of score: a pipe under a street about to be repaved, and a line with a recent overflow. This puts limited budget where it reduces the most risk. Dynamic reporting in CoreVision helps you rank and re-rank the system as new data comes in.
It depends on scale and staffing. A utility with no equipment and no crew can outsource all fieldwork with zero capital investment in trucks or cameras, which is the fastest way to get started. Contracting a CCTV-only scope keeps the field work simple and the bid pool wide. Utilities that expect to inspect large footage continuously may eventually justify building in-house capacity, but many keep fieldwork contracted and focus their staff on reviewing data and planning repairs. Whether you collect inspection in-house or contract it out, AiDetect automates defect coding, so your staff can focus on collection, maintenance, and rehabilitation.
Look for clean, continuous manhole-to-manhole video and accurate metadata: manhole IDs, GPS, pipe diameter and material, direction of travel, and a footage counter. Require PACP-trained operators for consistent camera technique, a standard export format, and a defined turnaround. A useful practice is to keep defect coding out of the contractor scope and centralize it separately, so grading stays consistent no matter how many different crews you hire over the life of the program.
The best sewer inspection software captures standardized field data, codes defects to NASSCO PACP, stores condition data and media in one searchable system of record, and integrates with your GIS and asset management systems. ITpipes provides this as a connected suite: FieldVision for field capture, AiDetect for AI-assisted NASSCO coding, and CoreVision as the office system of record where condition data, inspection media, GIS, and rehab history live together, delivered together as SmartVision. The goal is a single source of truth that turns inspection footage into decisions your team can act on, all searchable in one place.
AI-assisted defect coding reviews inspection footage and proposes NASSCO PACP codes automatically, then routes low-confidence segments to certified professionals for review. ITpipes AiDetect increases coding speed by over 50 percent and removes reviewer-to-reviewer variability, so the same defect is graded the same way across every crew and every year. The result is faster, more consistent, defensible condition data with certified experts still in the loop.
Condition grades map directly to action. In practice, a Grade 5 (failure imminent) triggers immediate repair or rehab, a Grade 4 sets a rehab window of one to three years, a Grade 3 is monitored, and Grades 1 and 2 are routine. Ranking assets by grade gives asset management and engineering a defensible, condition-based capital improvement plan instead of a reactive repair list, and it lets you sequence spending by real risk rather than by whoever complained last. Compare these grades against your street maintenance schedule so pipe rehabilitation lines up with paving and other work you have already planned.
The core cost driver is price per linear foot inspected, which varies by pipe diameter, access, and cleaning needs. The bigger financial picture is the shift it enables: planned condition assessment costs far less than emergency response, which carries traffic control, bypass pumping, excavation, and restoration. Many utilities fund a proactive program by moving a defined share of their historical emergency-repair budget into a standing annual assessment line, which tends to lower total spend over time while making it predictable.
Track a small set of KPIs: sanitary sewer overflow (SSO) reduction year over year, cumulative percent of the system inspected, the ratio of emergency to planned repair spend, average pipe condition grade and its trend, and cost per linear foot inspected. The emergency-versus-planned spend ratio is the clearest proof point that a program is shifting a utility from reactive to proactive maintenance.