The theme of ACE26 was superheroes.
I thought about that a lot while I was in DC last week, considering some of my favorite characters are superheroes. The imagery of capes and extraordinary power. The idea that somewhere out there is someone capable of saving the day.
But the people I met at the Innovation Hub were not looking for a superhero.
They were looking for something more useful. They were looking for clarity.
Why it starts with the ground beneath us
Every city has a story that nobody tells at press conferences or ribbon cuttings. It is the story of what is buried under the streets. The pipes put in the ground 80, 90, sometimes over 100 years ago by people who could not have imagined the city above them today. The water mains running under the same asphalt that has been repaved a dozen times. The galvanized service lines installed before most of the buildings they serve were built.
That story does not get told until something goes wrong.
A main fails. A street buckles. A boil water notice goes out. A neighborhood wakes up to a problem that has been building for decades and arrives without warning at 2am on a Tuesday.
This is the quiet crisis underneath every city. And it is the reason the conversations at ACE this year felt different to me.
What I heard on the floor
Over four days, I had the privilege of sitting across from engineers, operations managers, capital planners, and utility executives from water systems across the country. Large systems and small ones. Urban and rural. Some with sophisticated GIS platforms and real-time data pipelines. Some still running critical planning decisions from spreadsheets.
What surprised me was not the range of technology they were using. It was how consistent the underlying challenge was regardless of the tools.
Nearly every conversation came back to the same question. Not which pipe broke last. But which pipe is most likely to break next.
That distinction sounds simple. It is not.
Most utilities today make replacement decisions based on a combination of break history, pipe age, and material. Those inputs are real and they matter. But they only describe what has already happened. They are a record of the past, not a map of the future. And in a system with hundreds or even thousands of miles of distribution pipe, the vast majority of mains have never broken. A model built purely on break history is making educated guesses about the mains that matter most.
One operations manager told me his team recently implemented a new mains process. He was proud of it and he should be. Progress takes courage and resources and organizational will. But when I asked how the sequence of replacements was determined, the answer was familiar. Experience. Engineering judgment. The pipes that had caused the most recent problems. The projects that aligned with road resurfacing.
These are not bad answers. They are human answers. They are what thoughtful professionals do when the data runs out.
BlueConduit exists for the moment when the data does not have to run out anymore.
The superhero myth
The ACE conference theme was meant to celebrate the people who show up every day to keep water flowing. And that is right and worth celebrating. Utility workers are underappreciated, underfunded, and often invisible until something breaks.
But I want to challenge the frame slightly.
The superhero model assumes that somewhere out there is an individual capable of seeing everything, responding to anything, and saving the day through extraordinary personal capability. That model puts enormous weight on individual judgment, institutional memory, and the kind of experience that takes decades to build and retires when the person who carries it does.
The utilities making the most lasting progress I saw this week were not the ones waiting for a hero. They were the ones building systems that made good decisions the default rather than the exception.
One principal engineer told me his team was interested in the Capital Planner because they wanted to move beyond the spreadsheet. Not because spreadsheets are wrong. But because a spreadsheet cannot weigh failure probability against consequence of failure against budget constraints against road coordination schedules and output a ranked, defensible plan that a director can walk into a council meeting with and stand behind.
A consultant stopped by who works with dozens of small systems across a single state. She said the price point for individual system deployments was probably too high for the smallest utilities she serves. Then she paused and said something that stayed with me. “But what if one platform could serve all of them together?”
That is not a product question. That is a resilience question.
What resilience actually looks like
Resilience in water infrastructure is not about building pipes that never break.
Pipes will break. That is not a failure of planning. It is physics, time, and soil chemistry doing what they do. The question is whether your system can tell you which pipes are most likely to break next, how serious the consequences will be when they do, and what a prioritized, budget-aware response plan looks like before the emergency happens rather than during it.
Several conversations this week touched on a concept we call consequence of failure. Not just the probability that a pipe will fail, but the severity of what happens when it does. A main that serves a data center now drawing the power equivalent of tens of thousands of homes carries a fundamentally different consequence score than it did five years ago. A main that runs beneath a hospital or a school carries weight that age and material alone cannot capture.
One engineer asked how our model handles systems where breaks are limited. Where the historical record is thin because the pipes have been holding. That is the question at the center of everything we do. Because the mains most likely to cause the next crisis are often the ones with no documented history at all. They have not broken yet. That does not mean they are safe. It means the data has not caught up with the risk.
92% recall on never-broken mains. That is the number our data science team has validated. Compared to around 56% for a break-history-only model. The gap between those two numbers is not a marketing claim. It is the space where preventable emergencies live.
The conversation that stuck with me most
Near the end of the conference, I found myself in a conversation with a business finance manager who had come to the conference with her operations colleague. She was not an engineer. She was not a GIS analyst. She was the person responsible for making the numbers work and explaining capital decisions to leadership.
She asked what the output actually looked like. Not in technical terms. In practical ones.
I told her it looks like a defensible answer. It looks like being able to walk into a budget meeting and say: this segment ranked first because of its failure probability, because of the consequence of failure to the surrounding community, and because replacing it now rather than later reduces total cost by coordinating with the road work that is already scheduled for that corridor. It looks like documentation that does not just justify the request but explains the reasoning in terms anyone can follow.
Her eyes changed when I said that.
That is the moment I keep coming back to. Not the technical capability. The human need underneath it.
Utility leaders are not looking for a superhero who swoops in with all the answers. They are looking for tools that make them more capable of doing the work they were already trying to do. They want to be the hero of their own story. They just need better information to work with.
The budget conversation we need to stop having
I want to name something directly because it came up in nearly every conversation at ACE this week.
Budget.
Not as a complaint. Not as an excuse. But as a genuine, structural constraint that shapes every decision a utility makes. Smaller systems worried their size put certain tools out of reach. Mid-size systems were managing deferred capital alongside current obligations. Even well-resourced utilities were being asked to justify every line item in front of councils and rate payers who are already stretched.
I understand that reality. And I want to offer a different frame for it.
The question is not whether a utility can afford predictive risk modeling. The question is what it costs when they cannot use it.
Consider what reactive infrastructure management actually looks like at scale. A main breaks at 2am. Emergency crews are dispatched. Traffic is rerouted. A boil water notice goes to the neighborhood. Street restoration follows the repair. Then, months later, a different main breaks two blocks away because the same corrosive conditions that failed the first one were never surfaced across the corridor. Two mobilizations. Two street cuts. Two community disruptions. The second one entirely preventable if the first one had triggered a look at what else was at risk nearby.
That is not a capital planning failure. That is a data problem masquerading as a budget problem.
Several people I spoke with this week described their current process as reactive by default. Not because anyone wanted it that way. Because without a risk-ranked replacement sequence, reactive is the only option available. You respond to what breaks. You schedule based on what road work is already planned. You defer everything else.
What I kept returning to in those conversations is that the waste in reactive infrastructure management is invisible until you add it up. Emergency labor premiums. Redundant mobilization costs. Asphalt cut twice where it could have been cut once. Capital spent on the most recently broken pipe rather than the highest-risk one. Replacement schedules built around convenience rather than consequence.
The Dig Once concept gets at this directly. When a high-risk water main and a lead service line share the same street corridor, coordinating those replacements into a single trench cut eliminates one mobilization, one asphalt restoration, and one community disruption entirely. That is not a feature. That is money that was already being spent, redirected toward the outcome it was supposed to produce.
There is a cross-departmental dimension to this that rarely gets discussed. Capital planning, operations, finance, and communications all touch these decisions in different ways. When the risk intelligence sits only in the engineering department, the finance manager preparing the budget justification is working from a different picture than the operations team scheduling the work. The communications team sending out boil water notices is operating completely downstream of both. The result is not just inefficiency. It is a system where every department is working hard and none of them are working from the same foundation.
Predictive risk modeling is not a technology expense. It is coordination infrastructure. It is what allows a capital planner to hand the finance team a ranked, defensible list instead of a prioritized guess. It is what allows the operations superintendent to tell the crew what comes next based on failure probability rather than what came across the radio last night. It is what allows a utility director to walk into a council meeting with documentation instead of experience alone.
The utilities that reframe this conversation move faster. Not because they have more money. Because they stop spending what they have on problems they did not see coming.
That shift, from reactive spend to proactive intelligence, is not a luxury for utilities with resources to spare. It is the most efficient use of the resources that every utility already has.
What comes next
Before the show, Sabrina wrote beautifully about what was on our minds heading into ACE. The preparation, the questions, the energy of being in a room where everyone is working on the same fundamental problem.
What I want to add on the other side of it is simpler.
We went to Washington not to announce anything. We went to listen.
And what we heard confirmed something we have believed for a long time. The water infrastructure crisis in this country is not primarily a funding problem or a technology problem or a workforce problem. It is a clarity problem. Utilities know they have aging systems. They know they cannot replace everything at once. What they need is a way to answer the question that keeps every director up at night.
Which one first?
That question has a data-driven answer now. Not a perfect one. Not one that removes the need for human judgment or local context or the kind of institutional knowledge that only comes from decades of walking the same system. But an answer that is smarter than gut instinct alone. One that is defensible, explainable, and built on the specific reality of the system it is meant to serve.
The superhero of this story is not a technology platform. It is the utility leader who combines what they know with what the data tells them and makes a decision they can stand behind for their community.
We just want to make sure they have what they need when they walk into that room.
About the author
Chris Rodriguez is Director of Business Development at BlueConduit. He writes about leadership, water infrastructure, and the human side of data-driven decisions. If this resonated with you, he would love to hear how your team is approaching capital planning and what clarity looks like for your system. Let’s talk.
