Join the Insider! Subscribe today to receive our weekly insights

?

David (00:00)
Welcome, you are listening to the IT/OT Insider Podcast. I’m your host David. Subscribe to get the latest insights shaping the world of industry 4.0 and smart manufacturing. Today I welcome Amir Cahn. Amir is the CEO of the Smart Water Networks Forum. This is a global hub for the smart water industry. They accelerate the awareness and adoption of data -driven technologies in water, wastewater and stormwater networks worldwide. They are a non -profit organization.

SWAN brings together key players in the water sector to collaborate and share knowledge. So today we are going to talk about water and data. Amir, thank you very much for joining me today.

Amir Cahn (00:43)
Yeah, thanks for having me. It’s a pleasure to be here.

David (00:46)
So let me start with the basic introduction question. Can you introduce yourselves quickly and also the SWAN forum?

Amir Cahn (00:55)
Sure. So as you said, my name is Amir Cahn. I’m the CEO of SWAN, the Smart Water Networks Forum. And we really bring together the entire ecosystem to advance use of data solutions, water, wastewater, stormwater networks worldwide. And right now, I think you’re witnessing this data explosion and the number of the types of sensors that are out there. Sometimes it can become very overwhelming. You hear things like AI, machine learning, digital twins.

And that’s what SWAN is really, your guide to make sense of all the noise. And we bring together all the different players, leading water utilities, engineering firms, technology companies, startups, investors, academics to really collaborate, to share best practices, challenges, to really advance the industry forward.

David (01:46)
It’s amazing to see how many companies worldwide are dealing with water and wastewater. It’s unbelievable. The amount is just, I can’t even, I can’t even fathom the number of companies in this sector.

Amir Cahn (02:00)
Yeah, it’s also growing every day.

David (02:04)
So you recently published what you call the Data as a Service Playbook. Could you explain what is Data as a Service in the context of the water and waste water world?

Amir Cahn (02:19)
Sure, so there’s lots of as a service models out there. You’ve probably heard of software as a service and data as a service is a model where instead of a utility producing all that data and then a technology provider coming and using that to do their own algorithms, which is what SaaS is. DaaS is the vendor is generating that data for them. So they’re the ones who are installing the equipment.

they’re the ones who are doing the data transmission, the data collection, and then the utility can really decide what they want to pay for, whether it’s the data itself, summary report or predictive analytics. So it’s a unique business model, which is shifting the risk of technology adoption and all the things that go with it from the utility to the solution provider.

David (03:09)
That’s interesting. It’s a mind shift because I would say from my classical OT background, I wanna install my own sensors, I wanna calibrate them because then I, at least I believe they are telling me the truth or I’m in control. Maybe it’s better to say I have the feeling that I’m in control. So how do you see this from…

it’s my sensor and my data and my server. How do you see that changing towards I’m going to procure a service?

Amir Cahn (03:47)
Yeah. So what you said is really the traditional way of thinking about things. Like I want to own my assets. And if you think about other industries and you think about some of the most innovative companies like Spotify, Netflix, one of the things that made them innovative is that they changed the purchasing model. It used to be that people were very attached to their CDs or DVDs. They said, why would I give up control of these to someone else?

that’s the exact same mindset that utilities need to kind of have is, you know, do I really need to own all the assets in the ground? Because as soon as you own an asset, immediately the value starts to deteriorate. You have to be in charge of the battery replacement, making sure that it’s operating correctly. And the more advanced that sensors become and software analytic packages become, the more difficult it is for utilities to really do it on their own.

David (04:44)
And how, what is the role of the SWAN forum here? Why are you driving this initiative or what do you see in the market, which are the needs, et cetera?

Amir Cahn (04:49)
Yeah, sure.

Yeah, so that’s a great question. And I think that if you think about the big picture, technology is just one small piece of the puzzle. There’s also the people, the process side of things, which can actually have even a bigger impact on the success of technology adoption. And really, there’s no lack of innovative solutions out there. The real challenge is that there’s a lack of complementary.

business models to support the adoption of these technologies. So that’s where SWAN comes in as really a guide in the industry to help utilities really understand what are the pros and cons of these different business models. And that’s where you have a lot of these members sharing their experiences, both DaaS providers, utilities that have used this model. And I think that’s really the value we get this global perspective.

David (05:49)
Can you share a couple of real life examples where certain water companies who are utilizing this approach?

Amir Cahn (05:57)
Yeah, sure, no problem. So I can give you a water and a wastewater example. So from the water side, there’s a small utility in Louisiana called the City of Gonzales, and they had a big challenge in that they only had two meter readers and they had a lot of angry customers, they were losing revenue. And I talked to an operator there who said that they had a lot of heartburn, meaning they…

maybe had someone who put a decimal in the wrong spot and they wanted to really see how could they adopt smart metering with a low budget for being a small utility. And the way they did that is they actually went to a DaaS approach. They found a company that called UMS that would basically tell them, okay, if you wanna do smart metering over a 10 year timeline, it’s gonna cost you.

$5 per meter per month. If you account for like the cloud storage, the installation, all the analytics. And they said, okay, that sounds great, but we don’t have the money to pay for that. And what they did was pretty ingenious. They passed that cost onto the consumer. So they said, okay, well, with your smart metering package, you’re also gonna get increased communication, like a feedback app, which tells you how much water you’re consuming in real time.

And so the customer said, that sounds great. And so they added $5 per month to their bill. And they were able to actually implement the successful smart metering project where their DaaS provider was the one who was helping them make sense of the data that they were collecting and answer any questions that they have, really kind of acting as the middleman in the job. So that was on the water side. And that’s like a smart metering example.

On the wastewater side, if you go across the globe to Israel, in Jerusalem, so you understand Jerusalem is like one of the most innovative utilities in Israel, but they have a challenge with really how much their treatment plant can grow because they have limited space. And they had a problem with people really polluting on the weekends. So they had a problem with their wastewater treatment plant that there was getting this influx.

of industrial pollution and it was really contaminating the wastewater treatment plants, hurting the environment. And people could just pollute on the weekend. They didn’t really know who was polluting what. So they used a company called Kando. And what they did is this DaaS provider installed the equipment. So they put upstream sensors that could detect in real time the sewage quality. They could even tell the the utility in Jerusalem, who was polluting what.

And I talked to an operator there named Arone and basically he said that for him, he didn’t really care what candy was doing in the field. He just wanted the data and wastewater in particular is hard to get good data quality. It’s really harsh conditions down there. And so the impact of this model was that they really reduced the pollution events by 30 percent in one year.

and as part of their utility, they confine people if they pollute. So once they knew they were using this can -do system, it was actually like a good deterrent where they said, okay, maybe I’m not gonna pollute on the weekend because the utility confined me.

David (09:32)
These are two very interesting but also different business models. So on the one hand, you have the business model of, but it’s actually even an opt -in model. So the customer opts in to get certain additional services, but then the service provider or the water company also benefits from that. And in the other hand, it’s more like the business model is finding the one who pollutes or probably the fact that there is pollution is probably…

Amir Cahn (09:52)
Yeah. Yeah.

David (10:02)
what will cost the company quite a lot of money. Okay, that’s two cool examples.

Amir Cahn (10:09)
Yeah, I think also you kind of nailed it on the button where there’s so many different hybrid approaches. There’s no one size fits all solution. It really depends on the utilities unique challenges, because that’s one thing with DaaS and a lot of other solutions that can kind of be tailor made to fit the utilities challenges.

David (10:28)
Yeah, that’s really interesting. So I would say with that, what are the, in your opinion, what are the key success components for a data as a service implementation? What should we think about?

Amir Cahn (10:48)
Yeah, so you really have to think about both sides. And I think that’s how you have to look at data as a service, where it’s really a partnership model and has to be based on trust. Because if you think about it, the utility is outsourcing their data management, something that’s very personal and sensitive to them. And so they really have to trust the solution provider. In the same sense, the solution provider has to trust the utility is going to maximize their solution.

because they’re putting forth the initial ongoing capital costs. And even if you think about regulators, they have to trust the validity of the data that they receive. So trust is a huge issue, but I think it really gets down to the utility’s maturity level. And in terms of do they understand the value of their data? Do they see it as an asset? Do they really need significant infrastructure updates?

And so I think if you look at the globe, I think you can kind of group utilities into kind of four different buckets, I would say. Like one is just inactive utilities that are not thinking about big data, data management, which unfortunately makes up a lot of utilities. Then there’s a reactive utilities who are using maybe traditional paper methods and maybe measuring like one parameter here and there. And then there’s a lot of like SWAN members who are very proactive.

and they’re doing things using different like management platforms like SCADA, GIS to visualize what’s going on in their network. And then there’s really the optimized utilities that are kind of head of the game. And so I think for each different maturity level, utilities will have different needs. And one of the core issues is that they have to really identify the data quality that they’re looking for and what their key challenges are.

because maybe they just need to collect data once a day, maybe they need it multiple times a day, it really depends on their unique challenges. And that really differs by kind of their understanding of their own system.

David (12:56)
It’s good that you mentioned data quality. It’s also a topic we, or I often talk about also on the IT/OT insider, we see somehow that with a data platform approach, and I would say very broadly speaking, across all industries, across all verticals, you need, of course, your connectivity needs to be in order.

You need to do something around data governance as well. And then data quality is also a really important topic here. Do you see data governance, data quality? How is this changing? Who is working around these topics? What are the challenges you see?

Amir Cahn (13:40)
Yeah, so data governance is probably the biggest challenge within a DaaS contract because these are long -term contracts and they depend on the solution not being siloed. So if only one person in the utility is using the solution, they’re not gonna get enough value from it. So there has to be what’s called service level agreements, SLA’s, on the utility and the vendor side.

So in terms of like the vendor side, in terms of like data availability, data uptime, data representation, a good example of like bad data representation is if a vendor, like in the initial launch of the product, puts like a rain gauge under a tree. Like that’s not gonna get you good data. It’s not gonna be representative of the model. But the same sense, there has to be also…

conditions on the utility that they’re not siloing the solution or else it’s really not going to be worth the vendor’s investment. So I think data governance is really key understanding all the different security GDPR requirements there. And every country is different and kind of in their needs. But it also gets back to that kind of maturity level and how they understand and value their data.

David (15:02)
Suppose we have our data governance all set, we have a data platform in place. What are the tangible and intangible benefits for a wastewater company? Is this about money? Is it about cost savings or is it just about other things?

Amir Cahn (15:26)
Yeah, yeah. So you mean in terms of using DaaS? Yeah, so I think that there are several benefits. There are also several challenges and I don’t want to say that DaaS is like a golden solution, you know, that it’s the right fit for everyone because it’s not. Sometimes the utility will have its own internal solution so they won’t need to outsource anything. But I think that there are several benefits. One of them is definitely cost because…

David (15:30)
Yeah.

Amir Cahn (15:54)
you already know the costs of certain things. Like for example, using a cloud services, you know what the costs are gonna be. So you can spread those costs and forecast them across the life cycle of the project. Another huge benefit is the interoperability. So I heard an Australian utility say, why would I wanna install a system where it can be outdated six months later? You know, going from 4G to 5G, for example. And there…

utility doesn’t have to worry about that because that’s the solution provider’s responsibility to update all the, you can call it the in -between process, like to know where to put a certain antenna. But I think the biggest value is that it’s all outcome based and there’s different service level agreements that are part of the contract. And so it’s based on performance versus, you know, just putting up an initial investment in the beginning to just buy a product and you’re kind of stuck with that product.

So here you’re really paying for the outcomes.

David (16:59)
That’s also another way of approaching. It’s also a bit the difference between Capex and OPEX Invest at the Capex mindset where we’re going like, we’re going to buy something, it’s ours, and then we’ll try to implement these things and we’ll see what happens and we write it off over a certain amount of years. So what I hear you saying is that one of the key success factors is that you actually pay for an outcome. Should that be?

Amir Cahn (17:28)
Yeah, like there’s, I really like this university in the UK. So I didn’t mention this in the beginning of the podcast, but I actually did a PhD on data as a service. So that’s why I love talking about it. But one of the universities that I really referred to a lot was called Aston University in the UK. And they have this whole advanced services group, which focuses on servitization. And that’s what really DaaS is. It’s like moving from selling a product to a service.

David (17:52)
Mm -hmm.

Amir Cahn (17:58)
And they do a great job of simplifying what are kind of the, they call it like the staircase, like from just selling a product to then you’re guaranteeing the performance of that product in terms of like maintenance services. And then the highest level, you’re guaranteeing like a capability or an outcome. And a really good way to simplify this, I was actually thinking about: How could I simplify DaaS to someone?

who doesn’t understand all that jargon and it’s still like a new term. And this idea of servitization is used in so many other sectors. And I was thinking about the first service job I had. So this is a true story. My first service job, I was working for a company called FedEx Kinkos. I don’t know if you’ve heard of Kinkos before, but it’s like a copy center. Yeah, So it’s a copy center. I was what you’re called a copy boy.

David (18:50)
but I know FedEx.

Okay.

Amir Cahn (18:56)
So basically I had like a purple, black polo, like an apron, and people would come in the store and they’d not know how to use the copy machine. So I’d be the one to tell them like face up, face down, this is where you insert the paper. And one of the things that FedEx offered was instead of them using their own credit card to really…

buy the paper and sometimes they’d make mistakes so they’d have to pay for the mistakes. I had a special blue card that looked like a credit card and I could give this to them and they could basically make as many mistakes as they want with this card and in the end they would just pay for the paper that they wanted. So the copy that they wanted whether it’s like front and back, laminated, whatever. And I didn’t realize at the time but I was providing what’s called an advanced service.

because in the end, FedEx was losing a little bit of money and people making mistakes, but they were gaining so much customer loyalty In the sense that we were helping them achieve what they really wanted to do in the first place. Using a copy machine is not their core competency and if you think about it, managing a copy machine or getting all the insights from it would probably be even lower competency level for them. And so that’s an analogy for DaaS.

David (20:17)
Yeah.

Amir Cahn (20:17)
You are paying for the outcome. The DaaS provider is providing you that blue card to say, hey, I’m going to help you do this. You don’t have to do it on your own.

David (20:25)
That’s a really cool story. And absolutely, I fully understand the link between the copy machine and the data product. Let’s talk about technology versus culture versus mindsets. Well, I have my opinion. I often voice that also on my blog and in the other podcasts. But how do you see…

the technology evolutions, how do you see culture and how do they align or maybe collide?

Amir Cahn (21:02)
Yeah, so very, very powerful question. And I think that people are the determining factors of technology. Even the technology can have all these like great, you know, gadgets and like things that can help the utility. But the culture factor is going to determine if it’s a success or not. And I think that that’s one of the biggest challenges utilities have. Like I’ve been in the industry now for about 11 years and

Every year, the SWAN Conference is less about the technology and more about like change management. And I think that one of the core issues is this scary term about failing. Because if you think about the public sector, like we’re dealing with the most precious commodity, of course, we can’t fail like there are levels of failure, you know, like a treatment plant can’t shut down. But at the same time, you can’t innovate unless you’re willing to fail.

And one of SWAN’s partners is called the Institute of Brilliant Failures. So we once had a keynote from their chief failure officer, Paul Iske. And he defined fail as first attempt in learning. And really, you need to be comfortable with allowing people to try new things and just having that mindset that, yes, it’s going to be new, it’s going to be scary. But if we reach, you know, a

point where we’re not sure, let’s think about how we can pivot versus giving up the project entirely. And I think that people is incredibly important to build that buy -in from the beginning. And same for a DaaS provider. Like they can have a great solution, but if they don’t do enough training and showing the different people the value, because people might think, you’re going to replace my job. Or a labor union might say, you’re going to threaten.

people’s jobs in the utility where in the same sense, you’re really trying to enhance what they’re doing and seeing how you can work together. So people is probably the most important thing and then data quality is up there too, but people are a core part of the smart water journey.

David (23:14)
When I talk about data platforms and I link them to IT/OT convergence, I often compare, or not compare, but I often say that IT/OT convergence is actually data convergence. And because one of the main reasons why we try to…

converge somehow the IT and the OT silo in our companies is because we need data, not only from OT to IT, but also from IT to OT to the cloud. In every direction, we need to start integrating data. What I see when I look to the platform ecosystem today, I see something happening in the market. So where a couple of years ago, when you needed to have sensor data, it was well,

The only way you could do that is by installing a local historian in your plans or maybe on corporate level, maybe in your private cloud. But in any case, you were using a historian because that thing was made to store time series data. If you had a problem with sensor data, if you wanted to get something, you would go to OT . full stop, no questions asked. What I see today is that today the data…

problem when people start talking about data, it’s typically that IT or the data teams start to own that problem. So that means that they were very used to working with, I would say, traditional corporate data. And now they also need to start pulling in data, sensor data from the shop floor, from the treatment plants, from distribution networks, from the cloud, they need to combine that. And what I see happening from a technology point of view is that,

A lot of startups start working on these platforms. You have some conflicting protocols, conflicting visions. You have the hyperscalers versus the small companies. You have the IT companies versus the typical OT companies. I could say that we are somehow in this storming phase where everybody’s trying to do stuff and we’re not really sure yet what the default way of working in the coming years will be.

That’s at least how I perceive it. I would say the world as it is today. I wanted to check how are you perceiving the world of suppliers? And what do you see changing in the coming years, in the coming five years? Do you have some kind of a crystal ball maybe?

Amir Cahn (25:49)
Yeah. Yeah. So you didn’t even mention AI. Like AI is like changing at a like crazy factor we can’t even predict. And I think AI is one of the biggest kind of catalysts for using new technologies because a water utility is seen as a service provider, just like someone’s cell phone company, energy bill and

David (25:53)
Yeah.

Amir Cahn (26:18)
you don’t want to be in a situation where, you know, people like a customer is calling you, you can’t tell them like what the problem is. Like they expect like the water company to be like their credit card company to know exactly what happened and when. And so I think as you see the kind of the sector really evolving and other sectors really embracing AI and innovative service models that the water sector is kind of going to have to catch up. And I think that.

You can look at the technology side, but one of the biggest factors is also the aging workforce. So there’s this term like silver tsunami, like people, you know, retiring at a record rate. And it’s hard for these utilities to attract this next generation to get them excited about working in a water utility when they’re using really old methods. So I think that one of the answers could be like a data as a service platform where,

Instead of relying on utility to have this existing in -house knowledge, they can really work together with a technology provider to kind of supplement their knowledge and to kind of assist them produce that good data quality they need to do those kind of AI algorithms. But if you ask me where I see the sector evolving, I don’t think you can put the onus on water utilities because there’s not enough DaaS suppliers now.

And that’s one of the reasons we produced this DaaS playbook. It has 14 case studies to also give advice to solution providers, maybe want to migrate, not just offering SAS, but offering DaaS for utilities that really need help generating this data. And also in terms of engineering firms working together with the utilities and the DaaS providers to really benefit everyone involved. And I think that…

One of the interesting things I did in my PhD is I did a global utility service. So I asked people if they’re using DaaS, how they’re using it. And one of the interesting findings was that if a utility uses DaaS, let’s say for one application, like smart metering, they’re 50 % more likely to use it for another application, like water quality monitoring, and 30 % more likely to use it for more than two applications. So like once they understand the value of this kind of outsourced approach,

they wanna do it for different applications, which would help them even more if these vendors were working together. Because then they could ensure more interoperability, the vendors could use the same data standards. And I think that’s where the industry is heading to having more collaboration between the key players that work in a utility, the engineering firm, the consulting firm, the vendor, the utility really working.

and sharing the risks and the rewards. And right now it’s more like, okay, I’m going to sell you my product, give me your money and basically like, you know, I’ll see you when you need help. But there has to be what’s called these touch points. And that the vendor and the utility can kind of work hand in hand, because that’s what the industry needs. We’re at this pivot point where, you know, we have

water that’s dwindling, climate change that’s really impacting all aspects. And like people say, climate change is really water change, you know, the drought or flooding. And I think that it’s needed now more than ever. And like, that’s kind of my aspirational goal that we can kind of simplify the value for people to understand, okay, this is how I can apply it. This is how I can benefit from it. And this is how we can kind of work together to kind of…

you know, advance the water sector to be in a better situation.

David (30:06)
Well, we do have quite some service providers who are also listening to the podcast. So hopefully they hear your message loud and clear. How can either service suppliers or end users get involved with the SWAN network? The SWAN forum, sorry.

Amir Cahn (30:12)
Yeah, listen up, listen up.

is, yeah, so now I’m going to pitch SWAN. Basically, we’re a membership based organization and we have over 350 members from around the world. And we’re actually going to do a special until July 30th, where we’re going to have 10 % discount on our membership. So it’s a great time to get involved. We have a lot of different communities in the Americas, Europe, Asia Pacific. We’re very global. And then a lot of

technical committees based on AI, data as a service, smart metering, energy efficiency, interoperability. So a great way to get involved, share your insights. We produce different reports, do different workshops. I’m going to Singapore Saturday night. We’re doing an event at Singapore International Water Week. But really it’s a platform for people to share best practices, challenges, and really help accelerate the industry forward.

And kind of it’s also a way for them to amplify what they’re doing and work together with these leading utilities from around the world.

David (31:33)
We’re definitely going to put a link in the show notes and the article to your website, to the playbook. As a final question, Amir, I just want to ask your advice to somebody who’s listening to this podcast. It’s an end user. It’s somebody who is working in a water, wastewater or stormwater facility. So what advice would you give them today?

to start their journey towards becoming data -driven.

Amir Cahn (32:08)
Yeah, so I think you have to understand what your core challenges are and understand that there are a lot of options out there. It’s not just doing it in -house or SaaS. There’s a lot of different these partnership models and they have a lot of terms like data as a service, metering as a service, but really the idea is that you’re shifting some of the risks that you’d be responsible for to a technology company. And…

The two biggest barriers to using data as a service are concerns about data ownership and data security, which I 100 % understand. Like why would someone, you know, feel insecure, they don’t want to feel insecure about their data. But what’s interesting is that those are not really blockers because when you talk to utilities that are actually using DaaS, those are not made big concerns from a data ownership perspective because utilities really trust the contract.

If it says that the data is theirs, that’s usually enough for them. And on the wastewater side, a lot of this information is publicly available. So they can just keep a duplicate of information on their servers. And from a data security standpoint, if you think about it, all the data is being stored in the vendor standalone system. So if there’s a security problem, it’s going to be on the vendor side to resolve, and this data can be encrypted.

like smart metering data, if someone gets their hands on it, they’ll just see a bunch of numbers. They won’t know what it really means. So I think that what’s really important is to understand that it’s a journey. You don’t just become optimized utility or proactive utility overnight. You have to understand what your key business drivers are. You have to understand that a smart water network has different layers in its architecture. So you don’t just jump to a…

you know, an amazing AI platform. You have to have the solid foundation for your sensors, your communication, how you transmit all this information, how do you visualize it, are using like GIS, SCADA. So we have a great resource on our website called the SWAN Circular Model, which helps people understand the value of this journey. And the most important thing is that you’re not on your own. You know, people have similar challenges. So a utility from,

Canada can learn from a utility in Spain, can learn from a utility in India. And the most important thing is that they talk to each other and that we really work together to kind of solve this really pressing water challenge. And also learn from other sectors. You know, we’re a service industry. How can we learn from the manufacturing sector? How can we learn from the entertainment industry? Like we’re using cloud services. So there’s so many business models, so many unique approaches we’re doing.

and really encouraging more startups. I see really innovative startups and sometimes they just need to be given that chance because they’re doing a lot of great things. So, you know, kind of being open -minded with pilots and also not looking as a pilot as just like a sub -project, but really trying to see how you can integrate it into your utility. So also check out SWAN for great startups.

David (35:27)
I remember we’re not on our own. We can learn from each other. With that, Amir, thank you very, very, very much to join this podcast and obviously to our listeners. Make sure to subscribe and we’ll be back soon with another exciting story. Thank you very much.

Amir Cahn (35:48)
Thanks.