Lessons Learned: Integrating 'Dirty Data' into Cartegraph

The City of Plano has approximately 1,000 linear miles sewer lines and has been conducting routine inspections system using in-house crews over the last 5 years for 12-inch and smaller lines. These activities were tracked and logged through the City's work order system, Cartegraph, and downloaded to our CCTV data management system, GraniteNet, but that is where the data stopped. Unless there was a significant issue, the inspection was complete and the crews went on to the next task. While this process worked well, we were was gaining very little insight into the condition of our sewer system. As part of our recent Wastewater Master Plan, we were asked for records and data relating to the condition of our system for a risk-based assessment (RBA). We provided the inspection data we had and the work order data that had been linked to GIS and the consultant performed their analysis. When the analysis was presented, we had two immediate thoughts: - We can and need to have this information in Cartegraph. - Data is missing. We have completed much more rehabilitation and inspection work than is showing in the results. These observations started us on a journey of linking our data and maximizing our current investment in tools and technology. Through our collaboration with our consultant, we were able to recreate the RBA condition assessment in Cartegraph and utilize their critically assessment to develop a prioritized work plan for our crews and a business process for maximizing the results of our data. The condition assessment uses information related to an asset's age or material unless an inspection has been completed in which case the NASSCO PACP structural index is used for the condition score. The age and material data was already populated in Cartegraph and we were able to build generic degradation curves for our various materials to calculate an estimated condition score. We were also able to track our rehabilitation work in Cartegraph and use our relining projects to reset the estimated condition score of our lines. After reviewing the available data in GraniteNet, we identified the relevant inspection data to import into Cartegraph for a measured condition score. A review of the Cartegraph and consultant's condition assessments identified very similar condition score distributions with most of our system in good or better condition. This gave us a high degree of confidence that our process was working. Since the Master Plan, we have hired a contractor to help us inspect 12-inch and larger lines. Their inspection data is imported into our GraniteNet data and syncing with our assessment process. The critically assessment in our RBA evaluated various parameters including the pipe's location and diameter to score the pipe. This assessment was something we could not recreate in Cartegraph, but since it is something that rarely changes, we could import the results into our system. Combing the condition and critically assessments in Cartegraph identified one major basin as a priority for future inspections. The same basin was also identified from the Master Plan as the priority for future inspection work, further increasing our confidence in the process. As we continue to consume more data sources into our assessment, we are continuing to evaluate our parameters to ensure we maximize our investments in people, technology, and infrastructure.