Future Forward Full Interview: Sensors Are Just a Part of Intelligent Water Systems
Albert H. Cho is vice president and general manager, Advanced Infrastructure Analytics, Xylem.
V1 Media: Please provide a brief background about your education and career?
Cho: I did my undergraduate degree at Harvard in social studies, which is basically a fusion of economics, sociology and political science. In graduate school at Oxford, I did a master’s in development economics and an MBA. Professionally, I worked at the UN Development Program (UNDP) on a global strategy to achieve the Millennium Development Goals, including water and sanitation. I went to go work for McKinsey & Company, and focused primarily on environmental markets and industrial technology. I did a lot of work on renewable power and the smart grid, remote sensing-based technologies and carbon markets.
After that I moved to technology company CISCO, where I was the chief strategy officer for an initiative that CISCO and NASA launched around public-sector cloud computing, using machine learning and data analytics for environmental sustainability. I then went to work for the U.S. State Department, where I served on Secretary Clinton’s Policy Planning Staff and worked as senior advisor to the Deputy Secretary of State, focusing in part on energy, economics, and the environment. In February 2013, I moved to Xylem and I have been there for the last seven years. For the first five years, I was responsible for strategy, and then I took over as the general manager for our new Advanced Infrastructure Analytics (AIA) organization about a year and a half ago.
V1 Media: What is “Advanced Infrastructure Analytics”?
Cho: Within Xylem, it’s an organization focused on the application of data analytics and decision intelligence solutions to solve major challenges in water infrastructure, including how to make systems more reliable, sustainable and resilient.
V1 Media: Xylem recently released a paper titled “Harness The Power of Decision Intelligence.” Can you describe its main topics and goals?
Cho: The purpose of the paper was to take some of the generality and confusion out of the whole conversation about “smart water.” Over the last couple years, the industry’s been inundated with people calling all their solutions “smart”, and that phrase includes everything from strapping a sensor onto a device, all the way to the most advanced real-time digital twins and decision support systems.
The point we’re trying to make is that information and intelligence creates value primarily when it supports better decision making around specific capital and operating challenges that infrastructure operators have. So we have tried to demonstrate how the future of water utility operations and management can be improved through the application of what we’re calling “decision intelligence” in six key areas: reducing system losses, proactive asset management, improving water quality from source to tap, managing the data deluge in infrastructure systems, water equity, and what we’re calling the intelligent urban watershed–the optimization of water collection and treatment networks.
That’s so important because the intelligence in the system only matters if it drives significant improvement in the affordability of making infrastructure investment, because if I look at all of the statistics I’ve seen about the significant infrastructure needs to maintain resilient infrastructure in the United States and globally, the numbers are so large they’re effectively a conversation stopper. Nobody can envision a world where we’re going to invest trillions of dollars more in infrastructure in the near term, so the only way we’re going to be able to maintain the resilience and function of aging infrastructure networks is by changing the paradigm, and making smarter decisions about how we deploy capital and manage the existing assets we have.
V1 Media: You mention six connected strategies. Might there be one in particular that you find most misunderstood or might be most capable of opening up the change we need?
Cho: I think the broader topic of asset management is one of the richest and most value-creating areas in the paper, because so much of the value of utility assets are locked up in buried assets that are difficult to visit, assess and manage. As a consequence, most people interact with their assets only when they fail or when there’s an emergency.
One of the core themes from the paper is that reacting to emergencies is one of the most-expensive and least-efficient ways to manage assets. In fact, it’s barely managing assets at all; and that’s not to underestimate the challenges of managing large and distributed infrastructure networks. With some of the technology advances in the last decade, there’s a better way to transition from managing assets out of the emergency room in a purely reactive mode, toward a model where we can gain control of assets by better understanding their current performance and how best to target the limited resources we have in the areas that need it most. Around the areas of asset assessment prioritization and hazard mitigation, we can improve the productivity of asset management, and that’s a multimillion dollar opportunity for utilities.
V1 Media: How can engineers develop better systems for asset management?
Cho: There have been a lot of studies trying to understand how likely assets are to fail, but it’s equally important to look at the criticality of each of those assets and what the consequence would be if they were to fail. So an important part of the asset-management puzzle is looking at asset risk in a comprehensive way to understand which hazards in the system are causing damage and deterioration, look at the vulnerability of assets in the network to a deterioration or failure, and then also look at the other side of the equation: what will be the consequence if those assets were to fail, and what levers do we have to mitigate the consequences of failure?
To give you a simple example, if you look at a pipe network, one of the biggest causes of pipe ruptures is pressure transient activity in the network, so a strategy that only looks at statistical vulnerability of pipes based on age or pipe material, or even just soil condition, will miss the fact that there are active hazards damaging pipe networks every day. So thinking about hazard and vulnerability together is important. An asset near a hospital will have a higher consequence of failure than one in a recreational area that has a bunch of tennis courts on it. So think about that part coupled with the health of system-control assets to mitigate the consequences of failure. For example, if a pipe fails, how many valves do you have to visit before you’re able to isolate that section of pipe is another important part of the overall asset-management strategy.
We often see that in any given utility network, up to 40 percent of valves are either inoperable, in the wrong position or impossible to locate. If that’s the case, whenever there’s a failure, the consequence is going to be much greater because the inherent controls in the system aren’t fully operational, so a comprehensive view of asset management informed by regular assessment and analytics is an important part of running a more-efficient utility operation.
V1 Media: What are some ways utilities can improve? Is this all in the software they may or may not have, or are there other aspects as far as this digital transformation to decision intelligence?
Cho: We like to think about the decision intelligence approach as having three layers. The first layer is around making sure you have the right data flowing into the system. It’s the sensing layer where you’re pulling in “ones and zeros” that tell you something about the assets. Then the next layer is around understanding and modeling and interpreting the results of that information – an analytics layer. Then the third layer is around developing decision recommendations and actions based on the results of that model. In some cases, utilities don’t have data available on the nature and condition of their assets, where sometimes pipe locations aren’t even well marked, let alone the condition of those pipes or the conditions of those valves.
When it comes to asset management and collecting information in an efficient way, using a range of data-acquisition tools is really important, but the biggest leverage point is actually making sure the data are interoperable and organized around analytic models that support prioritization and activity. That’s one of the areas we have focused on – developing decision-support software modules that ingest information, link them to improved models of system dynamics, and then generate recommendations on the best actions to take to improve the overall reliability and efficiency of the system.
V1 Media: The paper’s announcement included several customer case studies that showed very high delivered measurable gains. Could you describe one of your favorite of these as well as what others can learn from it?
Cho: One of the best examples is in Buffalo, N.Y., where the city was built for a much larger population than it serves today. By leveraging the infrastructure capacity they have in their sewer network, they can better manage sewer overflows. The city has already been able to shave off a couple hundred million dollars off the cost to comply with their long-term control plan and eliminate sewer overflows, and all of that was done by developing a digital twin of the wastewater network that enables real-time optimization to make best use of the existing assets they already had in their system. If you know what assets you have, what condition they’re in at any given time, and you’ve actually developed control and rehabilitation strategies that allow you to do a lot more with what you have, you don’t have to reach for capital dollars to build solutions to problems that may already be within your grasp.
V1 Media: A lot of talk is finally escalating on climate change, and a lot of it centers around water concerns. How do you feel the United States and other countries are doing as far as tackling these problems, and what can be done to increase their urgency and effectiveness?
Cho: The effects of climate change will first be experienced through the lens of water, either through greater water scarcity or increased vulnerability to extreme weather events and flooding. In the United States, one of the things I’m excited about is the potential to use technology to improve the resilience of cities and communities to the impact of climate change, because fundamentally we are going to have to make some changes to urban systems to adapt with climatic conditions well outside of the original environments from which our current urban infrastructure was designed. So when I think about water scarcity, it’s not all about smart water. There are some really great new technologies that are going to help enhance water supplies through recycling of wastewater and making wastewater resources safe for reuse in industrial and municipal and agricultural applications.
I think we’re also going to see a significant improvement in the non-revenue water numbers and drinking-water distribution systems to make our water-delivery systems much more watertight. Today they’re losing, on average, 20 to 40 percent of their water. A lot of that can be saved through inspection data analytics and improved management, so that will make a big difference.
On the flooding side, examples like Buffalo or South Bend or Kansas City demonstrate that cities can actually begin to absorb a lot more of the rainfall they’re likely to see through the optimized use of storage capacity within the existing infrastructure of the system. That’s not going to help if you’re underwater, but between improving a real-time understanding of hydrology and urban drainage, and then by optimizing the resources we have, I think cities are going to be able to assume a more resilient posture without necessarily having to make back-breaking investments in civil infrastructure.
V1 Media: How might engineers contribute toward helping the climate change situation?
Cho: One of the most important things is to reduce the stigma around water recycling and reuse by being out in front in calling for the treatment of water resources around the United States. A drop of water in our stormwater or drinking-water or wastewater systems all have the same potential to meet human needs when properly managed across the cycle, and that’s not a philosophy that has always been prevalent in the engineering community. Embracing the vision of “one water,” not only as an individual but as a professional involved in associations and in public affairs, is a really important part of creating a more-efficient and resilient water-management culture in the United States.
V1 Media: With this “one water” philosophy, is that toward designing systems that flow in and out together or building broader public outreach? What would be the most important aspect of getting that started?
Cho: One of the most important parts of the “one water” approach is educating the public on the importance and value of water in all of its stages. In talking about our wastewater collection and wastewater treatment systems, we must begin to frame those less as a waste problem and almost as a manufacturing challenge for making clean drinking water. We need to help people understand that when water is properly treated and cleaned, it becomes a resource the community can use in new ways, because the more we can transition urban infrastructure to a self-contained system, the more we can lessen the impact on the environment and increase the resilience in the system’s natural variability.
V1 Media: Your company name evokes nature as the best model for water transport, so do Xylem solutions lean on more natural and green techniques as opposed to more human engineering?
Cho: The vision of Xylem is to emulate and support the vision of water as something that cycles throughout the ecosystem, whether that’s helping monitor and ensure the health of lakes, rivers and streams–where we have a lot of technologies that can help ensure the health and quality of natural systems–all the way to identifying ways to manage water in the most energy- and chemical-efficient means possible. We’re trying to take energy and chemicals out of the system to make the water cycle a lot more environmentally responsible.
The most important thing to think about when it comes to engineering is the social dimension of the choices we make. Decision intelligence is so important not because we think it’s important for all water infrastructure to have sensors or smart devices attached, but because water systems equipped with decision intelligence offer services in a way that’s more affordable for communities in the longer term. Affordability is one of these issues that gets a lot of airtime, but where the rubber hits the road is when we make large capital investments in infrastructure that may not be necessary, just because we haven’t fully exhausted the properties and potential of the infrastructure systems we already have by optimizing their operations with the data and analytics now available. Everybody deserves access to high-quality, affordable water services, so we look at decision intelligence as part of the core public-service mission of the utility to help drive more-affordable solutions for customers.