 The fate of freshwater is the future of life, yet we've taken those waters largely for granted. Nearly a fifth of the world's population doesn't have access to clean freshwater. We need to understand what the impacts are, and then we need to understand how to mitigate those impacts of humans on freshwater. When we do that, we've solved the major global challenge about freshwater security. The Jefferson Project is the most sophisticated technological approach to studying freshwater in the world. Well, we're not doing this in a laboratory. We're doing this in a lake. Lake George is an oligotrophic lake. It's a very special classification and that the water quality is very, very high drinking water quality. It's a huge ecosystem with a lot of moving parts. It's a living laboratory. It is the next generation of science combined with state-of-the-art technology to put eyes on the problems facing Lake George like we've never had before. To understand the lake from physics to fish, top to bottom, there's nothing like it. If you want to really understand the lake, you need to monitor the lake, you need to do experiments about the lake, and you need to do computer modeling of the lake. It's about big data. How do you handle 150 million data points? Jefferson Project is a great example of the Internet of Things technology being applied to environmental problems. So we have intelligence that is built in now at the sensor platforms. There are 42 of them in and around the lake, and that is really the brains of the project in terms of very high quality data. So we model the weather, we model the hydrology, the runoff, how water moves in the terrain around and runs into the lake. So we understand what's happening, what's running into the lake, how it's moving out of the lake, and how that works over time. With that new view, we can develop breakthrough solutions to protect the lake for all time. And that has ramifications not only here from a pure scientific basis, but also if you have an oil spill, or if you have a contamination event in a river or an estuary, these kinds of deployed IoT platforms can react to those things, and there can be remediation efforts. If information is power, the Jefferson Project is providing us with empowered information. Fresh water is under siege, and as we lose fresh water, the quality of our waterways, we lose what makes life livable. I hope the enduring legacy of the Jefferson Project is the long-term protection of this lake, but also the long-term protection of lots of other lakes around the world. Thank you. Thank you for inviting me here today. I'd like to begin by asking everyone in this room a question. It's an important question, one that I'm sure, based on the aspiration shared this week to date, you're asking yourselves, your teams, and your peers. It's a two-part question, the first that's easy to ask, and the second that's incredibly difficult to realize. Here it is. What's your moonshot? And importantly, how will you get there? Which of the world's most enduring problems will you help solve and how? Perhaps it's to ensure a clean water future for generations to come. And even better if that future paves the way to vibrancy, allowing us to leave this world a better place. What's your moonshot? How will you get there? And where do we even begin? Our aging industry is operating in challenging societal, political, and environmental times. And that challenge is being further compounded by additional, fast pace of change from population growth and other challenges that we face today and into the future. Big decisions are being made by you and those seated to your left and right. But our chairman often talks about this, and when she does, she shares that we also live in a profoundly hopeful time because we're entering an era where deep knowledge from the Internet of Things and the ability to process that knowledge is emerging mainstream. We have access to technologies today that didn't exist 10, even five years ago. And together, with reimagined standard operating procedures and the right skill sets, we have the ability to begin to chip away at some of the world's most enduring problems. Today, we have the ability to bridge the physical digital divide with a technological construct, namely the digital twin. Now the digital twin may have achieved buzzword worthy status, but the concept is not new. I'm reminded of a movie from 1995 that dramatized the Apollo 13 mission. It sensationalized the fact that Ken Mattingly, who was supposed to be on the crew but was cut at the last minute due to virus exposure, leapt into action when the oxygen tank exploded onboard the space shuttle. He then led the ground crew and mission control in a series of simulations that led to the safe landing of the spaceship in the Pacific. Now, this shows that NASA as early as 1970 appreciated the value of the digital twin. Today, we define digital twin as the ability to create a virtual representation of the elements and dynamics of a device or system and how it behaves or moves throughout its life cycle from design to build to operate. And we can do this because it's supported by three technological constructs, instrumentation, interconnection, and intelligence. Instrumentation, the sensors, and Internet of Things that are streaming volumes of data from hard to reach and remote locations. Interconnection, our ability to ingest, manage, and visualize that data, and intelligence. The tools and techniques we use to operate on that data, from predictive analytics to machine learning and scenario planning, all helping to enhance the decisions that we're making. We've already seen the digital twin in its supporting technologies at work in my opening video about the Jefferson project. But the digital twin, in fact, is at work at hundreds of water and sewage sector participants across the globe who are in varying stages of implementing the technologies that support the digital twin in their journey to digitization. So let's take a closer look at each of the three supporting technological constructs. Instrumentation, interconnection, and intelligence, and how they're at work today, leveraging bits and bytes to positively impact drips and drops. We begin with instrumentation. Technology is infusing every aspect of our lives, from sensors to meters, actuators and microprocessors, all monitoring and measuring life on this planet as we know it, providing unique perspectives and visualizations from hard to reach in remote locations. This instrumentation, by the way, we refer to as the Internet of Things, and it's expected to grow in our industry by 12.5% annually. By 2020, Gartner projects that the Internet of Things will outnumber humans by four to one. Incredible. An early example, though, comes to us from the Southeast United States, one of the largest, most diverse parks systems who is running 360 million gallons through a complete water and wastewater system at a cost of five million dollars annually. Now, the teams knew that their costs were high and that there were efficiencies to be gained, yet the problems were difficult to find and fix due to the labor-intensive nature of the work. So the teams instrumented. They put in 40 smart meters across 13 parks, streaming hourly data to a centralized command center that then visualized and published this information to the park managers who were then able to put that information to use, saving months in finding and fixing problems. To quantify this feat, the teams saved one million dollars annually that would then be funneled back into learn-to-swim programs and after-school programs for needy children. A good news story for instrumentation indeed. Now let me show you how harvesting the data provided by instrumentation and combining it, interconnecting it with other relevant data sources, supports the digital twin and is driving results in our industry. But first a word about the data. We talked about instrumentation, but utility leaders will cite as many as 150 different sources of data that are at work today providing information about their operations, yet most of them will say that there is no real practical way in which they're using this information, which leads me to share with you one of my favorite quotes. This one from the former CEO of Netscape, Jeff Barksdale, who said, if we have the data, let's use the data. If all we have are opinions, then let's go with mine. In this next example, let's have a look at how one utility used the information that they had at their fingertips. This example comes from the largest water and wastewater utility in Europe and the problem was at the time the CEO's second biggest problem, trunk main bursts. The utility had experienced eight bursts in the second half of the year, leading to significant damage to homes and businesses, traffic disruptions, and temporary system water loss. Yet the problems were very difficult to analyze and come to a final solution in terms of the root cause analysis. The teams thought that the burst just happened. Yet there were some believers out there that thought perhaps the answer lies in the big corpus of data that they're collecting about their business. So the teams went across silos within the organization. They collected reservoir level data. They collected pump data. They collected valve and flow data. They brought it together on a centralized platform, used a data model to normalize the data, and began to analyze it. And the results were astronomical. The teams realized that weeks before the bursts, there were patterns occurring. And as the timeline progressed, the stress on the system increased leading up to the bursts. They were able to quantify those characteristics. They started to notice that reservoir filling levels were unusual, with reservoirs running dry just before the bursts. They realized that some pipes had 50% increases in flow leading up to the bursts, indicating stress on the system. And the pumps, they were operating irregularly. Pumps that typically operated every 24 hours were operating more frequently, almost displaying characteristics of a cardiac arrest victim. So the teams concluded, taken alone, none of these indicators were enough to predict the bursts. But together, they were able to begin to predict and ultimately prevent the bursts, the power of interconnection. Now that we've explored instrumentation and interconnection, let's turn to intelligence. Our research shows that 30 to 60% of the time an investment spent on any analytics project worldwide is in organizing to get started. However, if you have the data you need, because you know you've instrumented, and you have it agreed upon platform, for ingesting that data, a data model to manage the data, and a process for analyzing the data, you can come to a solution 75% faster. This is where the intelligence comes in. It's at work today in our industry. We see use cases in the water and sewage sector where applying predictive analytics, machine learning, and scenario planning to tackle problems from non-revenue water loss to field crew optimization and even capital budget planning. And the results speak for themselves. We're seeing 10% decreases in water loss, 25% increases in work crew utilization, 15% decreases in transportation or energy costs, 24% increases in gas yields on sewage sites, and 10% decreases in capital budget needs. So if we know that the digital twin supported by instrumentation, interconnection, and intelligence can lead to these stellar results, then why is it that not every water and sewage sector participant in the community has achieved a fully deployed state with the digital twin alive and working across their enterprise? Well, it turns out that the move from innovation to practice is hardly ever cosmic. And there's a troubling statistic out there. Across all industries, 84% of digital transformations fail. And they fail because technology is only one part of the equation. Sure, it takes the right technology, but it also takes the right technology supported by the right processes with buy-in from the right stakeholders who have the right skills in order to see the results that we need now and into the future. So let's talk about the future for a moment, because that's an area of great interest in speculation. We've come a long way since 1970, but what's next for our sector? When we attend IWA's World Water Congress in 2028, just 10 years from now, what technology and innovations will be helping us to use bits and bytes in order to positively impact and transform drips and drops? Well, I realize that predicting the future is risky business, and I'm further reminded by Nostradamus, who once said that predictions are difficult, especially when they're about the future. But let's boldly go there and call out three potential technologies that have the possibility to really transform our future. The first would be breakthroughs in faster, more complex and accurate computation. 5G, an artificial intelligence driven video analytics would be too. The speed and precision that they will provide will transform our industry. What we once measured in months will become weeks, weeks will become days, days will become hours, and hours will become continuous. Big data effectively will become small data as we achieve more granular temporal and spatial precision, and that speed and precision will lead to better understanding of the logistics and cost of water as it flows through our supply and consumer systems. We'll have faster automatic remediation from remote monitoring devices, which will ultimately lower our energy costs, increase our safety rates, and decrease the environmental risk that we face. New business models will emerge. I'm already aware of a company that has the ability to use video analytics to understand what's growing in every field across the globe, from opium poppies to rice. Imagine what that could do for the water energy food triad. The second technology that I'll call out is more human like AI, and it will manifest in the form of common sense, one shot learning, and creativity, common sense. Machines will have the ability to know that when I continue to blow air into a balloon, eventually it will pop, or if I knock this table over, the water on top might spill. Well, one shot, or sparse learning. Machines will have the ability to know after they see something just one time what the cause and effect was, and be able to incorporate that into their body of knowledge. Relatable examples here are physical ones. I only need to bang my head against the wall three times, or maybe just once before I know that it hurts, and I don't want to do it again. The physics-based nature of our industry is very promising for this capability, and creativity. We're seeing it at work in the Jefferson Project. You see when it comes to 12 billion data points, there becomes this art to data exploration, and the 3D and graphing capabilities are early examples of this, but it could also help us with new water connection designs, or gray water reuse systems, pump schedules, or even the ability to better design transportation systems that take into consideration future flood paths. The third technological innovation that I will call out is one that gets me very excited, and this is that every one of us will have our very own personal robot or virtual assistant helping us to make better decisions in the boardroom, to better safety in the field, and even the optimal agenda for our return trip to Tokyo when we attend the 2020 Olympics, taking into consideration those things we've already seen, those we have yet to discover, and the interests and preferences of our lucky companions. So I'll leave you with this. The dynamic pace of change is leaving people feeling uncomfortable and rightly so. We're going to need to change the way that we work in order to meet and beat the challenges of today and into the future. We have a formula, the technology, plus the processes and the people, and the technology is supported by the digital twin, and it's three underlying components, instrumentation, interconnection, and intelligence. So I invite you to try new things, create a space for testing and experimentation, and to collaborate. Across the divisions within your utility and broader ecosystem, your vendors and partners, universities, researchers, innovators, incubators, and the broader community, a Japanese proverb, a single arrow will easily break, but not ten in a bundle. Let's help our neighbors achieve their moonshots and in doing so drive real change in this world. Thank you for your time.