IoT For All
IoT For All
On this episode of the IoT For All Podcast, Dan Simpkins, CEO of Dwellwell Analytics, joins Ryan Chacon to discuss IoT in residential real estate. Dan dives into experiences homeowners encounter when using Dwellwll’s products and then moves to more high-level by talking about the general landscape of adoption in the real estate industry and the challenges he’s seen in the multifamily sector. Ryan and Dan wrap up the podcast with a conversation about keeping costs down for adopters.
Dan Simpkins is the Co-Founder and CEO of Dwellwell Analytics, Inc. and a longtime technologist, entrepreneur, and business leader. Dan leads the team that created Dwellwell, an IoT proptech product that assists owner-operators of residential property portfolios in protecting and increasing the value of their real estate assets. As a serial entrepreneur with 20+ U.S. patents, Dan frequently teaches, writes, and speaks about entrepreneurship. He founded and led telecommunications pioneer SALIX Technologies, sold in 2000 to Tellabs for $300 million. In 2016, Dan's second start-up, Hillcrest Labs, was acquired and became part of CEVA. Notably, Hillcrest created the first Smart TV operating system and developed the first motion controller for television, used in over 100 million Smart TVs.
Interested in connecting with Dan? Reach out on Linkedin!
Dwellwell is an IoT smart home/proptech product that transforms residential maintenance from reactive to proactive (and even preventative!) using AI, edge computing, and patent-pending sensing technology. They deliver previously unobtainable data and analytics to multifamily real estate owner-operators. Dwellwell detects, identifies, and alerts owner-operators to minor maintenance issues before they escalate into larger, more costly, and disruptive problems. As the first "check engine light" for the home, Dwellwell is poised to fill a significant void in the real estate technology market.
(1:55) Introduction to Dan and Dwellwll
(6:49) Experience for homeowners
(10:26) Target audience
(11:20) Technology adoption in residential real estate
(15:33) Problems in multifamily industry
(19:15) How can you keep costs down?
- [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. If you are watching this on YouTube, we would love it if you'd give this video a thumbs up and subscribe if you have not already done so. If you are listening to this on a podcast directory somewhere else, please feel free to give this a subscribe or subscribe to our channel, to get the latest episodes as soon as they are out, and it also helps other people find the show. Alright, on today's episode we have Dan Simpkins, the CEO and Co-Founder of Dwellwell Analytics, a very interesting, very exciting company. They are a company that is in the IoT, Smart Home and PropTech product space for focus on transforming residential maintenance from reactive to proactive, even preventative in some cases, using AI at computing and patent-pending sensing technologies. Really good conversation, all in all, today. We talk about the residential real estate industry being wary of adopting new technologies and automations and how to kind of think about that, how to overcome it, what can be done. We talk about the multi-family industry, and the data problem that they may or may not have, depending on who you ask and how to approach that. Talk about how maintenance fits into the equation and retaining happy and satisfied residents. And this obviously plays into the different solutions that are available or could be available, that you could build around technologies that we talk about. So a lot of interesting conversations in a space that we haven't covered all that much. So Dan is a fantastic guest. I think we get a lot of value outta this episode. But before we get into it, if 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 Dan to the IoT for All Podcast. Thanks for being here this week.
- [Dan] Thank you for having me. I'm looking forward to it.
- [Ryan] Absolutely. Let's kick this off by having you give a quick introduction about yourself to our audience.
- [Dan] Well, I appreciate your asking. I've been a long-time serial entrepreneur, and I actually came from an entrepreneurial upbringing. My grandfather was an entrepreneur, actually started his first business almost exactly a hundred years ago. My dad took over that business. It's actually where I learned business as a teenager, helping him run his businesses. So that was exciting. I decided to go on a different direction. I wound up going to school and became an electrical engineer. And in the early part of my career, I became an expert in wide area networking just as the internet was taking off. So it was really great to be in the right place at the right time. I leveraged that expertise to start my first company, which was called SALIX. And from there I created two other companies, Hillcrest Labs, and now the one I'm most excited about presently, which is Dwellwell Analytics. A little bit on the the personal side, I am married, I've been married to my wife for 30 years, and I have one daughter, and what's really exciting is my daughter works as a UX designer for Dwellwell.
- [Ryan] That's very cool. Very, very cool. How big is Dwellwell now? How many people do you have?
- [Dan] Right now, on a full-time basis, We have about, a little over a dozen folks. We're small. We actually are using a distributed model, so we have another 20 to 30 odd contractors who work for us in various technical areas.
- [Ryan] Very cool. So why don't you tell our audience a little bit about Dwellwell Analytics, kinda what you all do, the role you play in IoT, that kind of thing.
- [Dan] Yeah, I would certainly love to do that. So let me give a little bit of the origin story. A number of years ago, I have a beach house. The beach house had a couple of frozen pipes that thawed and flooded. Actually, we got a call from our housekeeper that she arrived at the house and that water was coming out the front door. Not a good day. And I, you know, I had been developing technology for a long time. I had actually become, as part of my work at Hillcrest, an expert in sensors. And after I put the house back together, I was walking the floor of the consumer electronic show. And I made an observation that there are over a hundred million cars on the road, certainly in the US, and all of them have a check engine light, effectively a sensor network that provides insights about what's happening in the car before you get stuck on the side of the road. And I realized that of all the homes in the US, none of them have a check engine light. And so I basically created the idea of building the check engine light for residential properties. So you might ask, well what, what is that? How does it relate to IoT? Well, it turns out that, in general, maintenance is an expensive process for residential homes. It's estimated to be over a hundred billion in the US alone. And virtually all maintenance is reactive. We don't fix things in our homes, right? Until they break. And so what we did was we built a sensor, a custom IoT sensor that we place into homes, and we use that sensor to collect data, and we could talk about a little bit later, but we collect data, we run that data into an analysis engine, and we generate insights that help the owners of those homes better maintain them.
- [Ryan] And where does the sensor go? What kind of data is it collecting? I mean, the reason I'm asking is cause I'm sure we've all come across devices that if we can put in our home to detect water leakage, track energy usage, things like that. So how does this kind of compare to those individual solutions that are kind of out in the market to provide value to a homeowner?
- [Dan] Yeah. Well, you bring up probably one of the most important differentiating points of Dwellwell versus some of those products. Many of those products are great products. Some of them I actually own. But many of those products are siloed. So they, they will focus on a single area, like water. Another one you mentioned, maybe electrical energy, potentially HVAC. What we realized is in order to scale a product like this, we wanted to support the whole home across all dimensions, HVAC, structure, indoor environment, appliances, plumbing, and have one comprehensive platform. So that's the big difference between our product-- And others. What we do is we collect multiple sensor streams simultaneously. In order to generate these insights.
- [Ryan] And is this... The sensor stream data, is this from your own devices? Is this plugging into other devices that are already existing in the home? How does installation kind of go? I'm just very curious kind of how this would be, what the experience is like for a homeowner.
- [Dan] Yeah. Let me lay this out in a little bit more detail, because your, you know, your question obviously is a question that all of our customers ask. And frankly, the industry asks: How do you do that? I'd say the single, you know, greatest challenge we have as a company is the head scratch, which is, how is that even possible? So what we do is we deploy a sensor that we have designed. We call it a Dwellwell node or D-node. That sensor has multiple sensing capabilities. It can measure the traditional, that sort of table stakes sensing, like temperature and humidity. And it also has other sophisticated sensors in it, that either we've designed ourselves, proprietary sensors like our electrical sensor, as well as indoor air quality or the volatile compound detection, et cetera. So it has this variety of sensors. We place each of these Dwellwell nodes, which has all the sensors integrated, into the home, in a distributed fashion, roughly one every 300 square feet. The sensors look, actually I'll show you one, I think for everybody. This is what one of our sensors looks like. So it just-- Just plugs into an out. It just plugs into an outlet. Generally uses one every 300 square feet. So in a typical, in a medium size home in the US, 2,400 square feet, it would take eight of those sensors. Those sensors then, they are IoT devices, they are integrated devices, but there is actually a significant difference between these sensors and other IoT devices that are out there in the wild. They plug into the wall, so they're not battery operated. So they obviously, they take power off the mains. They communicate information to a hub, to a gateway that we've also developed that goes in the home. That hub collects that data, analyzes it, and then provides insights. The general technology we call ambient inference. It's our form of AI. And so what this sensor is doing is monitoring the ambient environment. So it's monitoring the temperature in a room and across the entire building, the entire home. It may be monitoring the humidity, the light levels, the sound levels. It may monitor the pressure or the volatile compound levels. And by monitoring all of these ambient conditions, we actually can then tell what is happening. Has a toilet flushed without filling or has it filled without flushing? Maybe it has a leaking flapper valve. Has an HVAC system changed its efficiency, so that it's taking longer to heat or cool the home? And by using AI, sophisticated AI that we developed, our own neural network architecture, we can take all of those data streams and then assess where the problems are, where the problems exist, where they lie in the home, and direct maintenance teams to those problems to make the process of home maintenance more efficient.
- [Ryan] Now, is this something that like the everyday average homeowner could and would use, as from like a target audience standpoint? Or is this more aimed at like property owners and people that are managing multiple residences? What is kind of the target?
- [Dan] We have a broad category for our customer base, which is, at least, where we are. Obviously, you asked earlier the size of our company. We're an early stage start-up. We actually started the company four and a half years ago. This is a deeply complex problem, so we've taken our time to work through the details. But we, on a broad basis, we like to say that our customers are people who own homes they don't live in. Because those are people who have the problem at scale. So multifamily owner operators, single family rental owner operators are the two major-- Those are the two primary segments.
- [Ryan] And when we're talking about kinda the residential real estate industry in general, what has technology adoption been like over the last number of years or maybe where it is currently? And I'm just curious as to, is it an industry that you kind of see has been leading the way in technology adoption? Is it something that has been a little bit more hesitant, potentially? And if so, one or the other, what's been kind of big contributors to that trend?
- [Dan] Yeah. In general, the real estate community has come later to technology adoption than other industries. And it's not... It's not unexpected. Many of the professionals, there are two reasons. The real estate is about making money. It's a financial industry. It's about optimizing assets in order to generate return on investment. And so anytime you bring technology to that industry, in many cases you're adding expense, which initially is lowering profitability. So the real estate community really needed to have a proof point. They need to be shown how technology, how technologies like Dwellwell or others will improve the bottom line. But the other piece of it is, secondarily, that they're... They're not technologists. So if you think about my first company, which actually created voiceover IP or internet telephony technology, we were engineers selling to engineers. And so they could assess our technology and understand whether it worked or not. But when you're a technologist selling deep tech like AI to a real estate professional, these are very smart people, but their expertise is not technically centered and that makes it harder for them to assess and frankly trust the technology. So it's more of a show-me type of industry. So when I think about it, I don't necessarily think they're wary of implementing technologies. I think they're skeptical. And ultimately they'll need to see proof points to adopt faster.
- [Ryan] I think that's the common trend across a lot of industries when it comes to IoT specifically. I'm sure it's many different kinds of technology as well. But as we've seen IoT roll out into different industries, some have been a bit slower than expected when it comes to adoption. And it seems like the main trend is that they wanna see proof before they're willing to put the investment of time and money into bringing on a new system that does something. Cause conceptually, it's a very easy sell for a lot of these organizations, but until they see it actually working, due to all the potential moving pieces and roadblocks that people have kind of encountered, there have been a lot of industries who are in that same boat, looking for proof of roll-outs that are successful before they kind of dip their toes in and start implementing these technologies.
- [Dan] Yeah. I think there's a another point. That is absolutely a really key point. You brought up a point earlier I'd like to go back and touch on, which is that you mentioned, well there are water leak detectors, for example, in their residential area or their electrical. Many IoT solutions are siloed, and in some cases they're overengineered for a very specific function. But what you don't see are products that are as holistic. So it requires, so integration is often required by the adopter in order to create a total solution. And we see that in the smart home extensively, right? There are a variety of different products. They don't integrate well. We're now starting to see new standards emerge, like matter, that's coming on the scene, that will hopefully change the ease of integration or increase the ease of integration. But that is one of the challenges. And it's one of the reasons why at Dwellwell, what we decided to do was to deliver a product that would serve these multiple domains simultaneously, effectively create a whole home solution, to give our customers the ability to implement without having to do that integration themselves.
- [Ryan] Totally. One thing I wanted to ask you, as you mentioned a second ago, you were talking about kind of more of the single-family residence, then the multifamily industry. When it comes to the multifamily industry itself, what is like the biggest problem there? And I'm wondering how big of a role data, because that's obviously a big part about IoT, is being able to collect data from things you weren't collecting data from before. How that has kind of played a role or maybe lack thereof until recently, and what that's really doing to kind of propel that industry forward?
- [Dan] This is a really important question. The general question of the value of data, right? In general, customers don't want data as much as they want somebody to interpret the data. So there's a little bit of, there's a yin and a yang going on. The fact is that the biggest challenge that they face is that they don't really have a lot of visibility into how their buildings, especially in the multifamily, how they're working. They may know the general, the core infrastructure because the maintenance teams get to see it and touch it every day, but they don't really know what's going on behind the doors of the residential, you know, units. So you could have a 100 or 200 apartment apartment building and a vast majority, 80% of that building, is completely out of view of the maintenance teams. And so there really isn't, there isn't the data available for them, or the insights to help them triage the maintenance process and optimize it. So we see, one of the biggest problems we're hearing from our customers is that maintenance costs are going up at an astounding rate. And actually, these, some of the data, the numbers that I'll share, generally five to eight or as much as 10% a year was actually before this current round of inflation hit us. And so their maintenance costs are going up, but there's a second problem. It's really hard to find people to do the work. There are a fewer people trained in these skills. And, you know, employment, we're almost at full employment, and there are very few people that they can hire. So we actually have a serious issue. There's a substantial shortage of housing in the country. It's estimated as much as five to ten million units between now and 2030 in terms of shortage in housing. And yet, and yet we're not adding that percentage of new workers. So where we're helping our customers is providing them not only the data on how the entire building is working, but we're giving them the power to convert that data into actionable insights that enable them to... It's a term of art in the field. So I'll introduce it to your audience. But there's the idea of wrench time. So that's the percentage of time that a maintenance person's actually repairing something, versus windshield time, which is the percentage of time that they're either figuring it out or driving to a building or going to get parts. And so by taking the data, processing it, giving actionable insights, we hope to increase wrench time and decrease windshield time and bring down costs.
- [Ryan] Yeah. That was gonna be my next question is how can these owner operators really keep costs down if you're saying that they're going up by, you know, the likes of 10%?
- [Dan] Yeah. Well, this is important. If we think about, so for us, ROI comes from a number of different sources. So how does ROI play in? Well, what we're doing is we are giving them the ability to convert unscheduled maintenance to scheduled maintenance. So it happens that there are studies that show that the cost of unscheduled maintenance can be two to five times as high as the cost of scheduled maintenance. So perfect example. You have, you know, we work. We work a 40-hour week, but the week is 160 odd hours in a week, right? So there are a lot of hours during the week where people are not working. So you have your first heat wave, it occurs on a Saturday afternoon, and a number of air conditioners needed refrigerant, and they failed. So now you have to go out and not only do you have to find people on the weekend to service it, so you might get into a queue. People... You've heard that time, well, like, oh my God, I called the repair person and, you know, I had to wait a week. So you've gotta get in a queue. Today, with supply chain issues, you might not even have the parts you need. And so, converting, so by taking data, analyzing it, and converting maintenance from a reactive process to a proactive one, we enable them to make that maintenance process planned and reduce cost. So that's one big way we do it.
- [Ryan] Yeah.
- [Dan] Another way... Yeah, go ahead.
- [Ryan] No, go ahead. No, go ahead and finish. I have a follow-up question but I want to hear the next way you do this.
- [Dan] All right. So a another way is to eliminate catastrophic failures. So insurance is a high expense, especially in the multifamily space, and many of them don't even use their insurance unless it's a complete loss. They don't hit their deductibles. So what we're also doing by giving data early, by presenting information about challenges that are happening as soon as they happen, we can minimize the effect of catastrophes. We also, you know, we have a purpose statement, and I'll end with this and let you ask your question. We've defined a purpose statement, which is, you know, better home... It goes like this: better home, better life, better earth. Right? And so for us, we believe if we take better care of our homes, it obviously, we take better care of ourselves, and ultimately we make the earth more sustainable. We make our homes, which are a substantial percentage of energy use, more efficient. And so by making homes more efficient and by giving our customers the ability to make their homes work better, they increase tenant satisfaction, reduce churn, and produce a more sustainable building.
- [Ryan] Yeah. That's fantastic. You actually answered my next question, which was, I imagine, more of a statement per se, but I imagine all of this, especially on the maintenance side, not just the bringing down of the cost, but also the way that they're able to be more proactive about it, be more predictive about it. It seems like this just generally across the board works to make everyone that plays, that has a stake in this, happier. And it just seems, it's a very fascinating kind of story and not just from the development of the company, but at the same time the product you have out on the market and the mission that you all have to kind of help this industry advance through technology. It's super interesting.
- [Dan] Yeah, well, I appreciate that. We're really excited about it. We are now in pilots. We have pilots with multifamily operators, we have pilots with single-family rental operators. We are not yet, you asked a point earlier, a question earlier, are we selling to individual consumers? We're not selling to individuals yet. But ultimately, once the product is refined and goes through a few passes of enhancement, we do plan to open it up to the consumer market, but through channels like the home automation and the home security markets.
- [Ryan] Fantastic. Well, Dan, I really appreciate your time today. This has been an awesome conversation. You know, when you talk about the real estate space in general, there's always lots of questions about it. I think the most conversations that I've had so far have been really around smart home as opposed to more of the property side, management side of things. Whether it's single-family residences, multifamily residences, you name it. And the approach you all are taking, I think, is a very interesting one. To kind of just think about what really matters to an industry as large as this, and being able to supply them with a solution that really starts to address their problem and need and make everyone happier kind of across the board through the ability to collect data in a new way, easier way, it even seems like, which all ties into the overall goal and value of IoT. So I very much appreciate you taking the time here. For our audience out there who wants to learn more, follow up, maybe ask questions, just connect in any way with you and the company, what's the best way they can do that?
- [Dan] Yeah, the best way is through our website. We have a "Contact us" at www.dwellwell.ai. So we are Dwellwell Analytics. There is a dwellwell.com that isn't us. So dwellwell.ai. And certainly I'm on LinkedIn as Dan Simpkins at Dwellwell. So don't hesitate to reach out to me through that way or directly through our website.
- [Ryan] Fantastic. Well, Dan, thanks so much again, really appreciate it. Excited to get this episode out to our audience, and think we're gonna get a ton of value out of it. I would love to find another opportunity to have you back to maybe talk about some other topics in the future.
- [Dan] Right. That's absolutely great. I really appreciate you taking the time to talk to me today. Thanks, Ryan.
- [Ryan] Thank you. 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 notification so you get the latest episodes as soon as they become available. Other than that, thanks again for watching, and we'll see you next time.