On this episode of the IoT For All Podcast, Ryan Chacon is joined by Vutility’s CEO, Matt Barber, who discusses the importance of capturing timely, relevant, & accurate data. The podcast starts with an introduction to Matt and Vutility before going into use cases of the company and the current issues with data collection. Matt then talks about how to capture data and the process of building the HotDrop product. Ryan and Matt wrap up the podcast with a high-level overview of challenges in the industry and where Vutility’s customers come from.
About Matt Barber
Matt has been an entrepreneur, business owner, and investor for the past 20 years. After completing his MBA at BYU, he spent several years as an executive consultant leading global organizations and innovative startups, providing financial and operational guidance. After initially joining Vutility in 2017 as COO, Matt has served as CEO since 2020, overseeing the global commercial expansion of the company, including technology development, market strategy, business growth, capital financing, and operations.
Interested in connecting with Matt? Reach out on Linkedin!
About Vutility
Vutility powers insights that change how businesses work through cost-effective, scalable access to real-time energy data down to the circuit level. We deliver the data that sparks change. As the leading provider of high-resolution energy monitoring, Vutility enables businesses across all industries to optimize their energy consumption and improve operational efficiencies. Vutility has created innovative and cost-effective IoT-based monitoring sensors paired with our leading-edge graph databse cloud technologies, so companies across a range of commercial and industrial settings can gain relevant and timely insight into their energy usage and monitor critical infrastructure and equipment. The HotDrop family of devices provides minute-by-minute data behind the meter down to the circuit level, transmitting over half a million data points per year.
Key Questions and Topics from this Episode:
(01:50) Introduction to Matt and Vutility
(03:22) Use cases of Vutility
(05:08) Issues with data collection
(09:20) How to capture timely and relevant data
(12:45) Process of building the product
(15:36) Challenges in the industry
(18:39) Where customers are coming from
Transcript:
– [Voice Over] You are listening to the IoT For All Media Network.
– [Ryan] Hello everyone and welcome to another episode of the IoT For All podcast, the number one publication and resource for the internet of things. I’m your host, Ryan Chacon. If you are watching this video on YouTube, we’d really appreciate it if you’d give this video a like and subscribe to channel, if you haven’t already done so. Also, if you are listening to this on a podcast directory, please feel free to subscribe so you get the latest episodes as soon as they are out. All right, on today’s episode, we have Matt Barber, the CEO of Vutility. They are a leading provider of high resolution energy monitoring. They enable businesses across industries to optimize their energy consumption and improve operational efficiencies. Matt is a fantastic guest. We talk a lot about the data side of IoT. We talk about causes of stale data. What stale data means, issue with data collection in use cases associated with the environment and energy. We talk about how to better capture timely, relevant, and accurate data, how to make or the making of unique product hardware that has lots of different patents associated with it, different technical implementations, different things that are, or I guess the challenges that are associated with that and kind of how to approach it, how to approach the buy versus build conversation. We talk about scalability, things along those lines, but it’s a fantastic conversation that I think you’ll get a lot of value out of. But before we get into the episode, many of you out there are looking to enter the fast growing and profitable IoT market, but don’t know where to start, check out our sponsor, Leverege. Leverege’s IoT solutions development platform, provides everything you need to create turnkey IoT products that you can white label and resell under your own brand. To learn more, go to iotchangeseverything.com. That’s iotchangeseverything.com. And without further ado, please enjoy this episode of the IoT For All Podcast. Welcome Matt to the IoT For All Podcast. Thanks for being here this week.
– [Matt] Hey, it’s my pleasure, Ryan. Appreciate the invite.
– [Ryan] Absolutely, looking forward to this conversation. Let’s start off with a quick introduction about yourself, background experience, anything you think can be relevant for our audience.
– [Matt] Yeah. So my name is Matt Barber, I’m the CEO of Vutility. I’ve been here for about five years now. I have a varied background in consulting, finance and then strategy, really. And I joined Vutility as the Chief Operating Officer five years ago, I’ve been the CEO for about two years. So I’ve been intimately involved in creating the product and driving it to scale and then creating the market around it.
– [Ryan] Fantastic. Let’s talk a little bit more about the company itself, kinda the overall focus, goal, role you all play in IoT, that sort of thing.
– [Matt] Yeah. So right now Vutility, we are a B2B company, so we don’t do any residential products, it’s all commercial. What we’ve re what we realized from our early days is that granular data specifically right now, energy behind the meter. So if you think about a building that has a meter, there’s no data what’s happening behind that meter. And that’s where we focus with our proprietary hardware software solutions to deliver and capture that relevant data behind the meter and get it out timely, relevant, accurate, and at low cost. And so that gives us a scalable advantage.
– [Ryan] Fantastic. Yeah, we’ll dive into that here in a second, but I wanted to ask if you could maybe dive in a little bit more to kinda the use cases and applications that you all are involved with, it usually helps kind of bring everything full circle from what it is that you all do to the general applications and problems you solve in the industry you focus on.
– [Matt] Yeah, so the cool thing about our product is, everybody needs this granular data and they use it for different purposes. So I can show you… If you want me to, I can show you a piece of our product right now. So look at this device, this is called HotDrop. So what this device does is you can put it on any wire in the panel and similar to the physics of how you charge your phone inductively, this inductively charges off the magnetic flux of the wire. So it harvests the energy. There’s no batteries and there’s no plugs to it. So in essence, any critical asset in a building, you can go snap this on, scan it, and it begins to measure and monitor in real time and back haul the data out to understand with granularity, any machines that are behind the meter. So if you think about an industrial environment where there’s pumps, there’s air conditioners, there’s all these critical assets, you can put one of these meters on every one of those and understand real time, is it on or off. How much energy is it consuming? Is it going to fail? So predictive failure and maintenance. So it’s a level of granularity of critical assets that no one’s been able to do because it’s so cost prohibitive and so time consuming to back all that data out.
– [Ryan] Yeah, that’s kind of a great overview. It’s kinda like a fitness tracker for…
– [Matt] Exactly, yeah.
– [Ryan] For the space, so cool. So I wanted to ask you though, when it comes to the collection of data in environmental and energy use cases, what are the general issues with data collection and potentially the causes, and maybe they kind of connect together the causes of more like stale data in general. So kinda higher level picturing it, just to kinda set the tone a little bit more for our audience who may not be as familiar with the space as others would be.
– [Matt] Yeah, so that’s a really broad question. So I’ll try to talk a little bit about the collection of the data and the value of collecting it and how difficult it actually is to collect. So typically, first of all, one of the hard things about installing data and collecting data at a panel is a panel it’s a steel box, which creates a faraday cage. So typically it’s hard to wirelessly pull that data out and broadcast it out with any kind of distance. We’ve chosen a protocol called LoRaWAN and you’re probably familiar with it. LoRaWAN can go miles outside… Inside a building we can get thousands of feet. So what that allows us to do first of all is have hundreds of these devices in a building with very high certainty that the data is going to be able to back haul to the gateway. The next issue with data that we see cropping up with IoT is security of data, right. And so one of the things that, because our partners are energy companies, there’s a certain standard to back hauling that data that was important for us to have. So we have our own layer of encryption on the data, so that if there’s a man in the middle where someone’s trying to intercept that data, it’s basically garbled junk that comes to them and it’s decrypted in our cloud. One of the things… The device is basically an edge computer. So one of the things that we also focused on is, I spoke at an edge computing and IoT conference and I don’t know that… So stale data is a problem, but one of the bigger problems that I think industrials are seeing is the massive amounts of data that are coming from the edge to the cloud, right. I read that by next year, it’s like 1.3 gigs a second are being created from edge devices in the Fortune 100 companies. And so having too much data that’s not relevant and having pooled unstructured is actually a really big problem. So one of the things that we focus on our devices is actually limiting the data points that we’re bringing back and sending back only the most salient or relevant data points to the customer. So…
– [Ryan] Is that a decision that you all kind of have expertise and focus in and or is that something that you’re discussing with the customer and helping them kind of evaluate what is truly relevant and what maybe not maybe more
– [Matt] Yeah, that’s a good question. Typically, the use cases for the energy data, it’s pretty static. Like they all want amperage, amp hours, but we can back haul other data. We can back haul temperature, we can back haul different data about the device. But at least for these use cases, we know we can target in and rather than try to pull all the data back, use the energy on the device and eat up cloud storage, we’ve targeted in and we know the data that we wanna bring back off of our own proprietary devices, right. But it’s a moving target. As customers ask for different use cases and we start to understand more of what they’re doing with the data, we may adjust the strategy. But as of right now it’s kinda like why everybody loves the Apple products. It’s so simple to use, right? Our relation process is simple, the data comes back simple, our APIs are simple and we think creating simplicity for the customer, even around the kinda data that’s coming back is our job at Vutility.
– [Ryan] Yeah, that sounds very kind of, so like a great focus for kind of your overall mission and what you’re trying to achieve, not just with the technology but in the conversations that you have with customers who are trying to understand the value you provide, which I guess kinda leads me sort of to my next question, which is, how to truly capture timely, relevant, accurate data from the source pertaining to these use cases we’re talking about? How does that conversation usually go with customers when you are talking to them about the value this provides, because the simplicity aspect of it that you’ve mentioned a number of times here is very, very important for any element or any use case in IoT. But have you noticed in the industries that you focus on any type of disconnect between the value you are all providing and just their general understanding or perception of the value, that kinda educational component?
– [Matt] Yeah, it’s a great question. And what it always leads me back to in like my five years at Vutility, five years ago… So if you think about the energy industry and utilities and how non-progressive they typically are, they’re slow, they use old technology, there’s not a big incentive to change. In the beginning, we would bring our tech and basically we weren’t selling against many competitors, but we were selling against doing nothing, right. And that’s sometimes a really hard sell. As we’ve started to show, the way I like to look at it is the cost per data point. What it used to be is extremely high and it wasn’t back hauled to the cloud, it wasn’t accessible, it didn’t flow, right. As we’re bending the cost curve down as a cost per data point, people are starting to understand, these are the use cases of stuff I can do with this data that in the past, it was just way too expensive on a cost per data point or cost per measured point, right. And so, I don’t know if I answered your question, but we’re in the middle of I feel like a revolution and people understanding if I measure and monitor this, I can get this insight which leads me to this action, right. And so that’s our role is to give you those salient data points to then make the action. We haven’t jumped ahead into, hey, you should do this, we partner with companies to do that. The way I like to describe what we do, because one of our investors is Chevron, one of our main investors is, we’re like we’re kinda like the oil pump, the oil rig, that’s pumping the oil out of the ground and we’re the pipeline, but we’re not the refinery at the end.
– [Ryan] Gotcha. So we are harvesting that data and we’re piping it out at scale to all different people that are then analyzing and using it for whatever their use case might be, machine monitoring, ESG reporting, benchmarking, billing, right. So there’s just so many things you can do with the data.
– [Ryan] Right. Yeah, I think that’s like, obviously the first and most important step of when it comes to you’re thinking about IoT is just being able to get access to data that was not available before. And then the next step is being able to take it, interpret it or presented in a way that can be interpreted and analyzed and then utilized by the end user to make decisions or whatever they’re trying to do with the data in order to be successful with any type of deployment when it comes to IoT. Lemme ask you, when you were… The product you showed earlier, when you were building that product, kind of, what was the process like to build it? I’m sure there were many different pieces that went into the development of it. If there was patents involved, that’s a whole another kinda thing. But just like… And I guess what I’m trying to lead into is to talk about not just the process you went through, but from a customer’s perspective that whole buy versus build side of things, or I guess question that they a lot of times are asking themselves, like, is it better to just buy something that already exists versus build maybe something custom? How did that kinda conversation happen internally and then how have you kinda see that perceived out in the market?
– [Matt] Yeah. So, anybody who does an IoT startup and tells you they had it all planned out, they’re lying to you, right. There’s a lot of little twist and turns and bumps and things you learn along the way. One of the things that I think is super unique about Vutility when we’re talking about our process of innovation is, when I look at the IoT landscape for startups, you see a lot of people they’ll build a visualization or analytics solution, they’ll build their cloud and then they have their sensor that they wanna integrate, whether they buy it or build it and understanding of how to scale a sensor to the scale that we wanna play at, that’s a completely different animal than building a software solution. And so we started a little bit reverse. We knew that first of all, we looked for a solution in the market that we could buy, right. They gave us the speed to install, the granularity and the low cost, right. There was nothing out there. So that gave us an opportunity to first of all, innovate, file patents and then build at scale. So we focused on finding a scaled manufacturer and that’s one of the first things that we perfected is, can we build this at scale? So right now our throughput is a 100,000 units a month that we can build. Our partner is one of the largest contract manufacturers in the world. I’m not gonna say who they are, but we have scale. So we figured out hardware– I was the Chief Operating Officer while we were doing this. And our CTO comes from that world and it’s a different animal to have quality at scale, dealing with supply chains. It almost makes building a software solution seem like child play relative to all moving parts and yields and tolerances and unique materials that you need for the product. So I always tell people an IoT business is almost like running two businesses, right. You have your procurement and manufacturing side, and then you have your product delivery and software side of the business.
– [Ryan] So I wanted to kinda pivot real quick as we’re getting closer to wrapping up and ask you about other challenges that you’ve seen in the space in general. You mentioned scalability here a second ago. So I’m curious if you’ve noticed any unique challenges as it relates to companies being able to scale. And then just generally speaking outside of that, anything that kinda comes to mind.
– [Matt] Yeah. It’s funny ’cause we love working with very large corporates. One of the things I’ve realized working with these companies is, it might sound a little sacrilegious, but you look at, let’s just say a company that has 5,000 locations and you start to talk about their OT strategy or their team that manages their critical assets and they have no idea what’s going on behind the meter in those buildings, and it’s shocking to me. So one of the things that I realize is there is a massive opportunity. Most of these organizations are flying blind when it comes to understanding their critical infrastructure, which is a massive opportunity for us, right. But one of the things that you’ll always run into is the internal teams and where the data goes. So having the data go to your cloud rather than stay on-prem, that’s the thing that you’re always gonna run into, right. Is custody of the data. And any device that if you think about it is, has any complexity, the data has to go somewhere to be analyzed, parsed, decrypted, right. And so that’s been one of the hiccups, not hiccups but challenges is dealing with internal data management policies with large companies and really trying to get them to understand like, almost every system you use internally, the data’s not staying on prem, right. It’s being back hauled to someone’s cloud somewhere, this is no different. So that’s been something that was unanticipated that we dealt with. And then the other part is, I just think when you have a product that has data that can be used in so many different applications, trying to understand and visualize that data for everybody how they want it is very difficult, right. Which is why our strategy to be an analytics company, we are not that. It’s funny, we talked about this, but we have a customer that said, after we presented to ’em, they said, “Wow, you’re not a YAAC.” And we’re like, “What’s a YAAC?” And they said, “Yet another analytics company.” The hardest part is to get the data at the source, at scale and then broadcast it up through to the cloud and then deliver it to an analytics partner. So we’ve stayed away from the analytics piece and we’ve chosen to partner with those guys and it’s been a good partnership thus far is to be the pipeline of the data for those kinda companies.
– [Ryan] Then lemme ask when it comes to just the business model standpoint, are more customers in the pipeline coming from your side or from your partners that are then coming to you and saying, “Hey, we need the data ingestion and collection piece.” That’s why they come to you or is it you are finding the customers, then you’re saying, okay, now once we can pull the data and now we go work with our partners and bring the partners in for the analytics piece of it all.
– [Matt] That’s a great question. So we used to go direct… About a year ago, we pivoted to go to partners and it’s been more partners with projects that they’ve won, that they need the data for. And they’ve used, I love the term simulated data. And that means like old, stale, estimated, right. And when they see our solution, a light goes off and they realize that their solution becomes more valuable when it’s plugged into the Vutility data pipe. And so although we do get leads from people, we usually send those leads directly to a partner to actually use the end data solution. So, yeah, it’s varied, but more often than not, it’s partners with existing scaled projects and they know they need the data they just have, until they found us, they haven’t had a great way to find that data and deliver it–
– [Ryan] Yes, just definitely a multi kind of… There’s multiple pieces to this all and finding a company who can do both, whether it’s through partnerships or on their own is a challenge for sure. And it sounds like you all have some very exciting things going on in the space that you play in, which is just great to hear.
– [Matt] Yep. We’re super bullish on the growth of the industry. I mean, just from our perspective… Obviously we’re just gonna grab a tiny piece of that, but the industrial IoT market by 2030 is gonna be a trillion dollar market, right. And it’s just rapidly growing and the mandates on energy data are accelerating as well. So we see executives five year plans that executive teams have for energy reporting and ESG reporting are being down to one year plans and they’re all looking for solutions, ’cause they realize there’s no fidelity to their data unless they can get it from the source. They need to be believable. The data needs to be believable.
– [Ryan] Absolutely. Totally agree with you. I think it’s a common, not necessary problem, but it’s a similar need across many industries the access to the data, how believable is the data, that kinda thing. So it really resonates well I think just with what OT is and what the goal of the industry in general with all the different technologies and components of it. So last thing I wanna ask you is for our audience out there who wants to learn more, get a better sense of kinda what you all are doing, stay in touch, maybe follow up with questions, what’s the best way to do that?
– [Matt] Yeah, go check us out at vutility.com. So it’s utility with a V in front of it and we have a blog and obviously, we have a social media presence and…
– [Ryan] Fantastic.
– [Matt] Yeah. Look for us on your podcast, right. Hopefully I get to come back again and talk about our new product that comes out in a couple months, right.
– [Ryan] Definitely, there’s lots of new stuff that we’re doing, we’d love to find a way to work together so we can chat more about that offline for sure. But I really appreciate your time, Matt, it’s been a great conversation. Thanks for kinda shedding light on an industry in a space that we haven’t had too many experts come in here and talk about. So it was a great conversation and I really appreciate it.
– [Matt] Cool. My pleasure, man. I appreciate your time.
– [Ryan] Thank you.
– [Matt] Okay, thank you.
– [Ryan] All right, everyone. Thanks again for watching that episode of the IoT For All Podcast. If you enjoyed the episode, please click the thumbs up button, subscribe to our channel and be sure to hit the bell notifications so you get the latest episodes as soon as it become available. Other than that, thanks again for watching and we’ll see you next time.
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