Large, public water systems serve 82% of the U.S. population, yet they account for only 8% of all water systems. The remaining 92% of systems serve smaller populations and have smaller budgets—and, as such, have more difficulty finding and affording water treatment solutions. WQP Associate Editor Sara Samovalov spoke with Jeff Lipton, director of marketing for WaterSmart, about data systems and how they can benefit small systems.
Sara Samovalov: What is the WaterSmart Essential platform?
Jeff Lipton: We have a data analytics and customer engagement technology platform that we provide to water utilities throughout the country. There’s a utility analytics dashboard that all of the utility staff have access to. Then, on the end-use customer side, there’s a web portal and there’s a mobile application. That’s the core of the solution. We also provide other auxiliary services; we have a client services team that provides onsite training, personalized content creation, customization, recommendations ... The primary difference between the core platform and WaterSmart Essential is that [Essential is] just limited to the technology components. We really tried to strip out all of the components that have marginal costs associated with them, so we can make it affordable to the tens of thousands of smaller utilities that operate in this country.
Samovalov: What led WaterSmart to focus on providing data to smaller water utilities?
Lipton: We looked at the data, frankly. There are 154,000 water systems in the United States, which is just astonishing. Of that, 100,000 are called “transient” systems, which are things like campsites and mobile home parks—things that aren’t really water utilities. That leaves [more than] 50,000 community water systems. Of those, 8%—about 450 or so—serve about 82% of the population. Because they tend to have bigger budgets and more technological sophistication, most of the vendors to the industry have focused on those larger utilities. What that means is the vast majority of smaller utilities that service small communities and rural communities are left out of access to these modern communication technologies and analytics technologies. We saw a huge opportunity there.
Samovalov: Why do smaller water utilities need data?
Lipton: Everybody needs access to data. It’s very hard to manage something that you can’t measure. Regardless of the size of the utility, if they don’t understand who’s using what, where and when, they have a harder time forecasting their revenue, planning for infrastructure investments, making the political case that they need to [make] for those investments to various stakeholders. If they’re armed with quality data, they can make better-informed decisions. Then they can better manage their operations and keep costs down.
Samovalov: Are there issues small utilities face that large utilities do not? How can software help with these issues?
Lipton: The challenges smaller suppliers face are very similar to the challenges larger utilities face: issues of decaying infrastructure, disengaged customers, rising operational costs across the board, water quality challenges. The key difference is that the relative cost of the capital investment needed for smaller utilities is much higher than it is for a larger utility. If you have a customer base of 300,000 accounts, then you have a large recurring revenue stream that can help to pay for those infrastructure investments. But for small systems that service communities of 3,000 or 4,000 people, they still have the need for water treatment plants and storage facilities and distribution infrastructure—but they have a much, much smaller revenue base, so it’s harder for them to make those critical investments. It increases their need to make better decisions, engage their customers, improve satisfaction and gain political support for these ongoing investments.
Samovalov: What kinds of data do smaller utilities need, and how can this software provide them?
Lipton: [The utility] provides us with some basic information. We supplement [those] data with external sources of data, including property records, weather information and census data. We use all that to create models of how consumption is working with a given user. And then from that, they’re able to make better investment decisions about where they deploy resources, what those would be, programs to educate people. Because we can help virtually audit their systems, we can identify water loss in the system to some degree, so they can do a better job at working with a limited budget to address some of the critical challenges.
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