Risk-Based Asset Ranking: Smarter Infrastructure Assessment
Since the 1970s, directors and managers of water utilities have honed the skill of creating forward-thinking plans to deliver needed services, create new capacity, and support community growth and prosperity. And since the 1990s, almost all utilities have focused on building substantial digital assets: geographic information systems (GIS), hydraulic models, and more. Today, utility leaders are focusing their time and energy on maintaining operational sustainability and avoiding that next catastrophic break.
All those skills and investments, developed over decades, can now come together to answer the biggest questions many utility directors and managers have: “I have records in many locations, I’m swimming in field books and tie cards, and I’ve got lots of GIS data and even some models, but how do I get all of this in one place and make it searchable and available to my key staff? How do I capture the institutional knowledge of my operators and carry that information forward? How do I understand the condition of pipes that have been in the ground for decades before my time? How do I predict which of my pipes are likely to break next?”
The key to unlocking this mystery is risk-based asset ranking.
This practice takes advantage of all the digital capital that utilities have developed over the past decade, along with the latest software applications, to provide actionable guidance. Using existing break and leak data, the analysis can calculate the failure probability associated with a variety of pipe characteristics. Then those findings are examined alongside other information like hydraulic criticality, soil conditions, groundwater levels, the location of critical users, and a variety of stakeholder priorities. The result is an electronic tool that essentially says, “Here’s the next set of pipes I suggest that you focus on replacing.”
The Boston Water and Sewer Commission (BWSC) was one of the first in the industry to implement a risk-based data analysis for this water distribution system. In the late-2000s, BWSC enhanced its capital planning process, driven by institutional knowledge, with a statistically-informed process using risk-based asset ranking. A risk matrix/ranking of existing infrastructure, developed in collaboration with CDM Smith, allowed BWSC to prioritize projects based on that analysis. The results were somewhat surprising: it turned out that some of BWSC’s circa-1800s cast iron pipes were more durable than anticipated, while some of the newer pipes in the system serving sensitive customers or placed in corrosive soils were of greater concern. This information immediately saved BWSC $6 million in the first year after the risk-based analysis was implemented, by showing that more-resilient-than-expected pipes could successfully operate longer without being lined, thereby reducing the pipe-lining budget from $17M to $11M.
Using the data you already have on hand to analyze the durability of your system can yield surprising and fruitful insights. Often, pipe material is a bigger driver of replacement priority than pipe age.
Communities around the country are also seeing the value of this approach. Palm Beach County, Boca Raton and Miami-Dade County, Florida are currently undertaking projects in collaboration with CDM Smith that define the best practices in risk-based analysis. The first step is a desktop analysis project, based on existing data, to pinpoint representative pipe assets for inspection. Because pipe inspections for drinking water conveyance systems are time intensive, expensive and intrusive, using analysis first helps minimize the amount of inspection needed. Each utility will be able to use the analysis tool in the context and form that’s right for their team, whether it’s a standalone software package or within an existing GIS platform. Based on the analysis, a targeted series of inspections will be carried out on high-risk spots of good-quality pipes. Soon, each of these communities will have a wealth of useful information about its most critical assets, allowing for smarter prioritization of future investments. And just as importantly, reducing the risk of costly, high-profile breaks.
From here, more exciting possibilities are at hand. Utilities can realize huge savings when water, wastewater/stormwater and roadway infrastructure managers interlock their systems and dovetail one department or utility’s critical repair with another’s near-critical repair—rather than having to dig up a fairly new stretch of road because a main underneath is reaching terminal status. This kind of “full street planning” is the next frontier.
What’s clear today is that risk-based data analysis provides answers to many of the questions that utility leaders are urgently asking. The only question remains, are you using it yet?