The Future of Facilities Management: Turning Data into Actionable ROI in Commercial Real Estate

Introduction to Facilities Management and Guest

Drew: Welcome back to the Peak Property Performance Podcast. It's me, Drew Hall, and with us as always, hosting Bill Douglas. Welcome, Bill.

Bill: Drew, good to see you again. Yeah. This week, we have a theme of robotics, automation, the future of operational efficiency in the built environment. And Bill, introduce us to our guest today.

Bill: Today's guest is Ruben Levine. Say, hey, Ruben, and then I'll read your intro.

Ruben Levine: Hey. Hey, hey, everybody. Nice to meet you. Happy holidays.

Bill: Exactly. Happy holidays. Absolutely. Absolutely. Let the energy fill the air. There we go. Ruben's the founder and CEO of StringBeam Technologies, which is a platform that turns facilities management into structured, actionable intelligence for both owners and operators. Ruben's a former Israeli Defense Forces serviceman, a lifelong data practitioner. I know. How many people do you know that you can say that about, Drew?

Drew: Right? That's right. He's someone like us who believes owners should build a moat around their own operational data, not hand it away to vendors without understanding its value. So we're going to explore how facilities data, procurement data, and on-the-ground operational intelligence can unlock new levels of control, predictability, and ROI for owners across every CRE asset class. So again, Ruben, welcome to Peak Property Performance. Glad to have you.

Ruben Levine: Thank you so much, guys. It's nice to officially be brought into your community.

The Role of Data in Commercial Real Estate

Drew: Yeah. Yeah, absolutely. All right, Ruben, we know that there are many owners out there who think they don't have data. They're not thinking about data on a day-to-day basis, for sure. But you, like us, have a core belief that most buildings are producing data all over the place. And that's different with human workflows, more so with human workflows than even with whatever sensors they may have. So speak into that a little bit. What are owners missing?

Ruben Levine: I just think that the owners are... They went from a very generous interest rate environment where there was a lot of acquisitions, as we all know, over the past, I'd say, half-decade, decade, right? And all of a sudden, the brakes have been put on them, and there's just not a lot of fat and gravy going around. Deferred maintenance was something that you didn't have to worry so much about. You probably had the budget, you didn't. But all of a sudden, there's just been this transition, right, in the industry. And before everybody knows it, they all have open positions in this space of managing their business and managing their building.

Ruben Levine: I think the statistics I've seen is that 40% of the industry disappeared in the last six years just out of pure aging out and just COVID displacement. And we still have about 40% of the, I don't know, 22 million Americans that support our blue-collar industries are over the age of 50. I think less than 3% are under the age of 30. So you have like this massive shift going on in the demographics. And I saw this over a decade ago when I ran a fire and environmental services company, the amount of turnover we had. And it's really a food chain issue, right? The more technical, the skill, the more training you need, more certifications. And it's become very sexy again for people to start focusing on because the wages have been pushing up. And that's been this massive ripple effect for everybody.

Ruben Levine: That leads to higher property and casualty rates because now I have more costs of dealing with these liabilities. Everything's getting passed through all the way down the food chain to the ownership. And it just kind of just like woke up to everybody. It's not like you're an idiot. I actually believe that there's always someone within the owner of some real estate portfolio who's an extremely, extremely anal analytic that's looking at numbers and has a tremendous thirst for information. And I think the statistics are 40% of a manager's time is just looking for information, right? So now there's been this incredible renaissance and power of processing speed to be able to kind of just like look through this data very, very quickly and inform people and make decisions on their behalf, right?

Ruben Levine: So this data that is sitting among you, the comings and goings of the people who are in your building, it's not just an occupant issue. That's not my space. I'm really focused on the service entrance here of each one of the buildings, but the contractors that are coming and going, how long they're there, what they're charging you, being able to let analytics tell you how much this electrical company or this elevator company is making per hour. Like sometimes they're making more money than a fairly competent senior analyst, I don't know, PricewaterhouseCoopers or whatever, you know, what is the Pricewaterhouse these days, you know, would charge, you know, for people. There's so much margin in this labor and just understanding that and having it revealed to you is, it's a very powerful moment and it touches a lot of bean counting. And so I hope I answered your question in some sense.

Automation and Robotics in Property Management

Drew: Yeah. Yeah, I think so. I mean, and you've gave an example there of like elevator repair, for instance, right? What are some of those examples that reveal big patterns, you know, project management hours, trade performance, like we're talking about right there, or inspections, are there some common ones that are real needle movers that where data is key?

Ruben Levine: Yeah. And it depends by asset class, right? So, you know, that an elevator is moving in a large, you know, data center tower, you know, where there's heavy security and there's a lot of movement by and between these buildings. There's a sophisticated suppression systems going on. Being a vertical transportation and being able to service these things and get to these things as much as just air ventilation and making sure that it's tempered air and environments like those, it's very, very important to understand that the things are getting done not so much, am I being cheated and being shortcutted, but do I have eyes on all these things? Because the insurance costs of a data center going down or a hospital going down in the middle of an operation is so high.

Ruben Levine: So I really focus on these critical infrastructure environments that really have to be audit ready all the time, always have to be measured to standard and IOT can only do so much. And it certainly can't process all that information, identify the outliers, notify who needs to be notified, auto delegate where it needs to be auto delegated. So, and in there is tremendous amounts of money and it's an asset, right? Having that kind of data about your building when you hand off your building upon sale, with that kind of predictability and that kind of workflow control process, you know, the ebbs and flows of how things are going on your building, how they should and identifying opportunities, identifying outliers, comparing, you know, the bigger your portfolio is, the more powerful that data leak becomes.

Ruben Levine: And you're talking about robotics. The more you know about the unique attributes of what goes on in the accordion of that business, right? And that envelope, the faster you're going to be able to plug in, you know, hardware, you know, to do things for you, tracks that move cameras around, you know, maybe in a mechanical room and just take picture of gauges that haven't been IOTed or will never get IOTed or just looking at puddling on the floor and comparing those photos, right? So there's this massive, massive amount of change that's going to happen over the next 10 years when it comes to what people's definition of a smart building is. And it's very exciting.

Drew: Yeah, that's cool. And that's where we're drawing all our energy from, you know?

Ruben Levine: Yeah, that's nice. I mean, I think that might be the first time I've ever heard of IOT, like being IOTed or becoming IOT, like use like a verb. I get it. I see it as, yes, exactly.

Drew: Well, so I mean, it's obviously... A lot of times I'm talking about with clients, you know, people that own properties, IOT is just the sensor, it doesn't make your building smart just because they can hear and listen and see. You have to make... And they go out of calibration and they go, you know, I have a... What do you do with the data, right? And then we have to correlate it back out and do something with it. So smart is still left out of the equation. We like to use the word autonomous, like put some if-then loops in it, you have data in, you have a formula in between if this, then that. And then the building starts to think, I use an air quotes, because it's really not thinking, you're telling it what its options are, but it's making a decision without a human. So IOT is just the input. It's just the sensors. It doesn't make your building run on its own. It definitely doesn't make it smart. I think that's been oversold by PropTech. So sorry to interject, but those are my...

Ruben Levine: Yeah, no. And you're right. You're right. It has been oversold by PropTech because, as you said, even at the beginning of the show, people, they don't understand this beast called data. They don't understand these oil fields that are here and that they own them and they need to own them. And they need to understand that if the ownership falls in the hands of your third-party provider, they've built a moat around you. Again, I've seen buildings go from CBRE to JLL to Collier's and back to Heinz and all that other stuff. And the property manager and the people that are the same people, this is uniform changes. So these property management organizations have looked at this and said, the way we're going to be able to remain sticky is if we can go ahead and own the data plumbing, right? And that's a big strategy now, right? JLL bought building engines, you got JCI, I think they just bought Muvolo, a lot of acquisition and consolidation going on here because they want to build moats, right?

Ruben Levine: And I think the landlords have to say, hold on a second. I'm okay using your plumbing, but at the end of the day, it's my plumbing. If you take the process plumbing and say, oh yeah, sure, we'll leave you with your data, what are they going to do with it? So it's a big risk today and it's a big opportunity to get your control around it, right? If you really want to be able to save costs and bring a real experience to the inner walls of a property efficiently, right?

Drew: Yeah. So where do you think this is right now? How is the commercial real estate industry, are they at the beginning of this realization of the critical importance of this data? Or do you think, is it fairly mature? Do you think there's a wave that's about to crest or where are we in that lineup? Secondarily, why do you think it's still undervalued where it is undervalued?

Ruben Levine: I think it depends on the kind of leases you have inside your property, right?

Ruben Levine: A triple net leases and you're just providing an envelope to somebody and everything's on their inside and that's a corporate occupier or whatever you want to call it, they need to be thinking about that data if that's their model. If you've got high white gloves or a lot of common area maintenance that you're responsible for, malls and other things have a pretty big responsibility outside those triple net leases. I think they've all realized how much power, the ones that I'm speaking are already there. I had a senior guy over at a hospital call me up, just like you just said, Bill, you know, he said to me, he says, wait, and all this stuff about this AI management's asking me to come forward with AI solutions to run our plant, you know, an operation. Isn't AI just one big add-if statement? He said just like that to me and you're right, you know, it's building that logic and the tribal knowledge into this now is, you know, I think we're still in the early innings of it and the reason why it's only taken until now, it's not because it's not smart people. It just hasn't been a priority. People are focusing on, you know, since COVID, they've been focusing on redesigning their buildings, you know, to deal with this, you know, transient worker and transient company, you know, kind of model and creating hotels out of the corporate, you know, the corporate buildings, you know, so someone could go ahead and quickly expand and take over a floor, you know, in New York City and pretend like it worked there for a month, you know, maybe do impress the client or prospect, I don't know. Every, you know, there's so much, they're just becoming so agile with, you know, the delivery of what they're going to be able to put inside, inside these buildings, that's where all the investment's been, right, of time and money has been in amenities, getting people back into work, creating environments and we can go ahead and pay our debt service, right? So, you know, I think, but now everyone's looking now, how do we go ahead and run these operating costs and create a very efficient or create or gather this data so we can do better jobs of charging people back, you know, and giving them chargebacks for the things in the, in the utility and the resources that, you know, there's a bay here where people can load and unload, there's 16 tenants. I want to charge that bay back to them. I need to give them a way to go ahead and reserve it and let other people know it's not there. I need to let the truck drivers know who have signed into whatever that app is. It allows the ecosystem to alert when they're arriving. You know, there's tons of opportunity and efficiency, you know, of time. If you can bring that, a nervous system around that, I don't know. We see a common area. Cost accounting is a very prevalent problem. Like you have, you know, maybe it's triple net or maybe it's a higher end building. You have a customer support 24 by seven operation. The same time you have a coffee shop on the first floor, a lawyer firm on the top floor and a dentist in the middle. And they're not all working the same hours, but you're just going to apply cam charges based upon square feet. It's, we're finally seeing in the past couple of years, seeing owners take that apart and make it more applicable, not to punish their 24 by seven tenant, but to attract more other tenants that don't fit the same model, we can't expect that the dentist pay the same cam charges as somebody who works two and a half, three and a half times as much hours wise.

Building a Data Moat for CRE Owners

Bill: So Ruben, what is, I've heard you say this on the show and we've said before to elaborate on what you like, what is building a moat around your data actually look like in practice for a CRE owner or operator?

Ruben Levine: First of all, most people think when they, when they say that, that it's the water that's at the moat, right? That you've built a bridge of that. Okay. Building the moat itself, that's going to hold that water for a sustainable period of time and, and be able to collect that water and hold onto it. And if it overflows, it drains the right way and all that stuff, right? That's data plumbing, right? So you have to just make a decision now, whether it's a strategic imperative to build a moat around your own data and allow your business partners to draw from it and use it and extract from it or collect some stuff on their own and keep it for themselves, but there's a bare minimum of information we're going to need to know about what you do in our property. And when you define those things, you could go ahead and quickly figure out the ways to collect. And some of it's external data, you know, was it snowing outside? Oh, the snow removal company came. That's why, you know, and being able to bring and, and give that, that meta-tagging formula around it so that you can quickly retrieve it, quickly identify it and so on and so forth. And we're telling people that that's not such a heavy lift. If you start collecting your data in one setting or make sure that it all comes together in a unified way. Cherry, I'm sure you're familiar with in the industry is doing a wonderful job of going to all these disparate systems that cut across, you know, two dozen different kinds of technologies in the tech stack and try bringing all together and unify it. That's talking about what happened yesterday. Very important to predict what's going to happen tomorrow, right? But while all that's going on, you should start collecting your data from today forward. And we tell our clients, we believe that after six months of you playing around in our sandbox, we can identify your building for your unique tenants. Like you just, you just said, because two buildings that look exactly the same are going to have different behavior patterns, different energy. It draws just because of the people who occupy it, right? And then you've got the codes of the buildings and then you've got the different buildings within a portfolio. That's why I think there's so, I don't think that there's a facility management company out there that owns more than 5% of the market. I'll send you the, a visual, some analysts out of India put it out there. And I thought it was quite interesting that Compass has less than 5% of the industry, JLL has less than 4% of the industry, Aramark, right? You thought every corporate cafeteria, you know, and hospital systems, not even a half percent and 83% is others. So, you know, this is because of the variability that's out there. So you asked the question about building a moat. Every single building has its own, you know, collection pools, create those collection pools, own that information and give it to your partners to be successful for you. We talk in the book about own the damn data. We just go ahead and say it. The publisher didn't want to publish it, but we said it anyway, own your damn data, but it means control it. And then you can coordinate with it and actually use it, like talk to your vendors about where you're going with it. Instead of just you talking to me, Mr. Vendor, like why don't I collect information, draw some insights from it and talk back to your system and make it even better. Your AI can't do that because I, my AI can see all of my systems. You're only seeing the one that you sell me. So the moat is.

Drew: I have to say one of my favorite hobbies lately is just going out on chat GPT or co-pilot and just asking like a crazy question. You know, it's just like fun. It's like a game for me, right? Just to go out there and ask away. How many times do three consecutive numbers show up in the Powerball lottery? You know, over the, since the Powerball lottery, and then it comes back like, you know, 10 seconds. Oh, this has happened 49 times in the past 18 years. And there's this many drawings. I just, you know, this processing capability is not that far away from every property owner out there. It really, this is not light years ahead. It's not. If, if, if they have their data. Do they have to go out and create the moat to collect that data? If you rely on someone else, he's going to be as inefficient as he, as the prior management and management company was, it's gonna be the same bodies, just different uniform, same behavior patterns, all that other stuff, same limited capture of information, less transparency, less accountability. If I have to get a ticket driving through a school, a school zone, because I went because a cat, a camera captured me. I think this is where smart city is going to have to end up in order to effectively run cities is to be able to say, can the camera mounted to the side of the building, tell me if these people put out their recyclables the right way. So that when, when a public transportation comes around, they know what to grab. Are these people putting their cooking oil out in the right way? God knows what, you know, what, whatever the tripping hazards, I think camera vision, you know, if I had to predict what's really going to be the big aha next is when, you know, I guess security cameras and begin to converge with the data collection and digitizing that information, that's, I think that's when everybody's gonna, you know, and I don't think it shouldn't be that expensive. You know, at the end of the day, we're talking about storage and downloads. Right. Anyways, I'm excited about it.

Ruben Levine: Well, it's a process change. It's not a forklift upgrade. This is not CapEx intensive. It's really not. You have to manage your vendors and work with them, but the data's right there. And then you have to find a way to make them want to participate. So, you know, that's really where, you know, we, you know, at least where my, what I, what I love most in my job is just the whole UI UX experience and creating, allowing people to do this on mobile, because I think that there's been a lot of, there's a lot of great data out there, but it's still very desktop, very tablet oriented, lots of visual real estate to play with, but, you know, I think I saw a statistic that from 2014 to 2022, people were actually using their mobile phone three times as much when I think it was four and a half hours a day. They're really just on their mobile. And then there's one additional hour when they're on that mobile doing things that have nothing to do with work. That's five seventh of people day is now pounding away on swiping and doing this and trying to, and that's where I'm having the most fun just as an, as an innovator and, you know, almost an artist. When I, you know, when we play around with this stuff, you know, I was just working with the users and just trying to find ways, you know, how do we get them engaged? How do we get them to want to play with it and engage with it? And I think most of the landlords, at least the ones I've worked with are capable of turning around to their ecosystem and saying.

Ruben Levine: We love the work you do for us. This is not about us wanting to call blow us on you. This is about risk management, right? This is like, we saved a million dollars on these 50 buildings using this technology. We need to save a million dollars on the other half of the portfolio now. Just talk to it, put your information into it, get other, again, there's a lot of other companies doing this in many other realms. So again, it's just, this is what, you know, how you are, how we think you build a moat around it. And if you guys want to cut that out, if that was too string beanish, knock yourselves out, it's kind of, you know, totally cool, you know, for the editors among us, but I, I, I'm curious, you know, just to hear from you guys, like, you know, are there asset classes that you feel are more attuned to it than others? Or do you think it's more of a regional thing? Like, you know, you're, you're out there talking to a lot of people. I'm just curious.

Bill: By it, do you mean moat or do you mean collecting data? Understanding the opportunity of having the data, you know, or are there still? Yeah. I don't find that it's asset class driven. I think the owners are intimidated by technology to start with. And that's just the industry as a whole, but AI has been so fast and so strong coming on and, and almost oversold. Probably every vendor you see is now telling you, if not selling you what their AI features are. And that's just a way for them to be more efficient and better at providing the service you're already paying for. So the inference by the ownerships, the owners that I see are that they're covered by AI and we try to say what you're not actually using it across your property, let alone your portfolio. Because, you know, this vendor says they're using it. Okay. So AI could be NLP, right? It could be robotics and it could be machine learning. Those are the three big tools as we try to bucketize AI. Sometimes somebody will put in a natural language processing OCR or voice recognition and say, now we're AI. And really they've just been scanning your bills for years. Now they're really good at OCR in a way you can search it. So yes, it makes it easier for you, but the data is still not in your hand. The data is in their hands. So we're trying to transfer the mindset to be, we get the data in the property's hands and then look across these 15 to 20 to 25 silos of data and see what machine learning could find then about operations improvements. I don't, we don't see it across asset class. Some asset classes, we can't impact the revenues as much like an office. You can, you can sell more services to tenants, but in apartments, it's very limited, you know, senior living is going to be even more limited. But when we talk about operation expenses, it's across all asset classes. I'm going to let Drew answer it, but that was my long answer. The editors might want to cut that too, Ruben, but there was a long.

Drew: I'm interested. I'm interested. I'm interested in your perspective. You know, I will take that away from this phone call, whether the editors publish it or not. No, I would say the exact same thing. It's definitely not, it's definitely not tied to a particular asset class. Technology, I would agree is the scary point. You know, it's so often I feel like we still are seeing that from ownership where technology is sort of the necessary evil, like they don't really know what all it is doing, what all it could do, whether it's working or not, what systems could possibly be generating data. I don't know. Do we have that type of system? I'm not sure. Even if you do know that you have that type of system, do you know if that type of system is participating in Dataflow? And if it is participating in Dataflow, what is that Dataflow? And do you, do you have capture of that? Do you have the ability to actually own it? Do you own it? So, I mean, you know, there's just a lot there, but I mean, kind of tying back to what you were saying. It comes down to a trust factor, right? You know, people, because it's such a foreign territory and the whole language and the whole space of AI to many of these property owners is really, really something that they don't understand. You know, you really have to, you know, analogies are great. I look at this as like where banking was in the seventies, you know, this is just a lot of mom and pops, smaller banks. And then through acquisition, they had to create standardization across the board. And the more they collected that data, the more they were able to more effectively operate and they had to understand about their customers and they went through this evolution by necessity a long time. And there was so much money to make. If you just had information, two and a half seconds from the trading floor before the other houses about some sort of news or some sort of other trade that just took place and the way they brought that all about, it made the banking industry to be, you know, just this efficient. So, and still until property owners decide to go ahead and capture this data, you know, I think it's going to continue to be fragmented industry. There's going to be a lot of costs, at least on the operating side, which is where I live, that you're not going to be able to get rid of until you start exercising, you know, the muscles around that data to go ahead and, and understand it and be willing to be educated by it and informed from it. And I, I think a lot of people are, are there, but you have to be, you have to be aware, you know, also because the data can also sometimes, you know, intimidate, you know, the mere fact that, you know, my little world is going to become so much more transparent to everybody else, that I'm not so sure I want to invite that in my life, you know.

Ruben Levine: Yeah, that's fair. I think too, there's a component here of seeing is believing, you know, so, so often KPIs aren't specific enough. And so one owner may not necessarily know how another owner out there is winning because KPIs are not specific enough to a particular system or set of systems. And so it's, it feels a little bit cloudy, like, eh, okay, they've achieved some efficiencies. No, it's you've got the monopoly that you got, you've got that, you know? Now that might not be a problem for Saturday. We imagine that the best, you know, nealy impossible thing to do would be to ask again and again. What's best to you, best for me, best for somebody I could very easily improve that for it? Like I didn't think it was supposed to be appreciated in that way. Don't be confused. That's already great. Now let's let's move on to the big thing, do you have experience or confidence? Cause I saw a article somewhere, was it from someone saying that, go ahead.

Drew: No, I think you might've like phrases like sensitivities or like a privacy concerns. Am I revealing too much? I think you did mention that.

Ruben Levine: Yeah. Yeah. Look, you know, we all, I guess if we all tape recorded our life from the moment we wake up in the morning until the moment went to sleep and what we looked like when we woke up in the morning, when that all of a sudden it became revealed to all the people you see at work while you know, you're, you're sitting in your makeup and your hair, your hair looks great. And you just, you're just, you're making a totally different presentation about yourself. And I think everybody has that, you know, I don't care who you are, you know, even Donald Trump, Elon Musk, all these guys, you know, I'm sure they look pretty, pretty, you know, uninteresting, uh, when we would, they don't allow us to see them. So let's just make sure that everybody on your stats, that's human behavior. Right. And as you get higher up in these organizations in a world of capitalism, right. I earned the right to become even more private, you know, but we all know that the really good guys have this different kind of culture and that is how do I become super, super time efficient? Like you talk to the VCs and what they're looking for, they're looking for founders who just like have this lights out, you know, efficiency about them and smooth operator, yet nonetheless way about them. And that's so much part of selecting, you know, the type of people that they're going to invest in. Right. And I think the same thing is in, in any business or any property, there are those people and if you can use data to create that kind of culture. So I don't even want to say which property, cause it's in Manhattan. There was a very, very big issue that happened there recently that was front page news, but I could tell you that. You know, we got thrown out of there because someone was doing something in under four minutes that everybody was taking between 40 and 60 minutes to do. And when that became revealed, um, this individual went to their union rep and said, you know, I know they gave me my own phone and it was not on my phone, which they're not allowed to do, but forget about it. And I got thrown out on my behind. Now what happened at this building, I would never wish on my worst enemy, but let me just say that, you know, this was my experience, you know, very early on. And I had to like open my eyes up to that. And I, I ended up calling this particular individual later to apologize, you know, just even though after it was over, I felt like I didn't want this person to, I don't want them to associate my brand, right. With this mishap. I just apologize. I said, listen, this was not our intent here, you know, to, to do anything like that, and he says, well, you should know, he says, I just wasn't comfortable with your user interface. It just was hard for me. So I would go around and I would take the piece of paper, right. That we used to use to look at these 60 gauges in this three square block property, right. That everybody else would take 40 minutes. I did it in 25 minutes on my piece of paper. And then I came back and I spent four minutes going into your thing online and just entering it. It was such an eyeopening opportunity for me because you know what? Union or not, right. He's right. I'm the problem, right. And, and that's where it was most revealing for us. And I went back to my design team and I said, we need to create a way to collect data and engage people who want to play along with this. And if there's not a feedback loop and if we're not pounding down the doors to understand, we're never going to get past go here. So, you know, on one hand, you know, this is about their kind of look, you know, wolf in sheep's clothes, right. It looked like, you know, we were whistleblowing and in the end it really became, you know, back at us. And that was my lesson to me is that I want to convince people that, you know, you have a culture, I want to adapt to your culture, but the really efficient guys at the top and the real leers that are setting the cultural tone there should be able to, you know, invite people, you know, into that. And I'm hoping that's where people, at least I'm seeing that's where that's what they.

Drew: All you want to work with good customers as opposed to objectionable ones out of the gate. So, sorry to digress.

Bill: I totally understand that. I think everybody listening understands that too. Choose your customers. Yeah. What about that?

Leveraging Data for Insurance and Cost Reduction

Drew: So Ruben, like if you think about major wins that you've seen once facilities and procurement data is leveraged, you think about the major wins that people experience, you alluded a little bit to some, can you walk us through one recent or not, just where leveraging that data has resulted in a major win?

Ruben Levine: I was talking to a customer of ours about wanting to increase what we were doing with them and have them take on a couple more features and he came back to me and said, listen, our insurance rates were just the quotes. We just got back on these properties, like 50 properties. It's going to be like 35% across the board. It's like, everyone's like, what the hell are capital? We're revisiting our CapEx budgets and everything like that. And I said to him, hmm, so I'm thinking I'm not going to get any more business here, my contract canceled and I said to him, I said, you know, do me a favor, send me over your claims information over the past five years, as you know, we all know what, I think most people in risk management don't know what a mod is. I hope if not, otherwise you're in the wrong role. But I went back to him and I said, listen, I'm showing you, you've gave me a hundred buildings. I only took these 50 that, you know, we're tracking data on and I've been able to correlate between people who are using our system and tracking who's coming and going to your lower, you know, what I'll call the lower quartile, you know, kind of risk, you know, classification and claims history. Why don't you go back to them and tell them we're going to roll out to the other, you know, rest of the portfolio with this thing, how much of a break would you, you know, give us? And they called, he called me up afterwards. He says, dude, it just dropped our quote. They capitated everybody at five to 7% saved us a million dollars. You know, I was like, you know, cool. So, and that's just tracking people coming and going from, from their place and indicating what they're doing and how long they were there using a sign and a, and a mobile phone.

Drew: You know, we talked about it all the time here, like reduce utilities expense, but insurance expense is the second one right behind that. Cause it's been going up so much in the past three to five years. And by being proactive and sitting down with the underwriter, we're seeing massive reductions. Energy, saying your insurance is going to go down, but instead of double digit increases, you can keep it to one or two points with the right information and the SOPs to pack it up. And you just gave us a great example, a million dollars.

Ruben Levine: And I've talked to the insurance. I haven't talked to the insurance industry about this for several years. And I'm thankfully, you know, through people very connected to a lot of the, you know, the senior underwriting folks, you know, at the new degrees. And, you know, there's subsidiaries that kind of, you know, touch this market. And I can tell you, they do not want to mandate anybody using any particular software because that passes the liability. You told me to use this software. You told me to work with these guys. You told me I would get a rate reduction. If I did, then all of a sudden we forgot to do something. They just want to, they want so much fine print, just, you know, the sign-up phase, you know, to the software. And they just do not want to take this on, but it would happen fast if there is some sort of carrier that turns around and says, let's create a safety group in the space. If you're out there and you're listening in and you think you can make that happen. I used to be part of a safety group when I had my fire and environmental services company. And that was like the difference of $800,000 a year, you know, in insurance expenses, just being part of that safety group. So, you know, strategically we're, we're, we're looking, you know, into that. Because I think that that's important.

Bill: I'm glad you liked the example. You know, we have plenty of examples and we're constantly looking at this data. Well, at least I have such a thirst for it to try and understand which clients are growing, which buildings are growing, which ones are, you know, which are moving up, who's got better completion rates, you know? So I have as much a thirst for this information to make my little property operate with their anchor tenants that we have here and their ecosystem and foot traffic they bring into my mall, you know, you know, that's the way we look at it. You know, you're, you know, in our business, we're just a bunch of servers trying to space or sublet it. Redundant.

Practical Steps for Data-Driven Workflows

Drew: Like for what's the simplest way for the owners listening today, CRE owners. What's the simplest way to start turning operational workflows into structured intelligence? That's the last question. And then we'll move into the fun part.

Ruben Levine: Yeah. You got to work with some sort of if this, then that based, you know, a data gathering backbone. You know, once you go ahead and start sucking that information and you understand the type of process you would do, if you did it yourself, you're the SME right in the building, if you would do this yourself, how would you do it and create that little kind of guide that anyone who picks it up at any stage is going to be able to follow that. And now you're beginning to collect your data in a smart manner. And as soon as you can collect a little bit of that data, then I think you're, you're ready to really starting to understand how you can automate and kind of auto delegate and take that information. So you got to start collecting now. You've got to start collecting now, collecting it in a manner that you can analyze or you can allow or teach analysis, you know, to it, right. Or how you would analyze it.

Bill: I love it though. You said, start collecting now. I love it because the common theme on your show is start collecting yesterday. Got to start somewhere. Got to start. Everybody says that by the way. And I think that it's not a tagline. It's just, you start collecting data. Then you'll know what you can do with it.

Drew: This was really great. I really appreciate your time. Did we get everything you wanted to talk about?

Personal Insights and Career Advice from Ruben

Ruben Levine: At the end of each of our episodes, we always like to ask our guests a few little gut level questions, right? Just, we call it, we call it the extra floor, right? In the spirit of commercial real estate. There was an Amanda, what was her name that you recently, what was her name? Amanda. Yeah. One of the clips she answered, you can see that she was answering one of these.

Bill: Okay. Yeah, absolutely. Yeah. So here we go. Number one, what's a book or a podcast that has shaped how you think?

Ruben Levine: Look, I read a lot of books. You know, some of them are business books. Some of them are like just in my personal inspiration books. You know, I'd have to believe that spin selling is kind of like one of the, you know, really shaped once I really kind of understood how to sit down and have a consultative dialogue with people and not come across like I'm trying to sell you something and like I'm trying to help. I want to get you to believe that I can help and I want to only be evaluated based on the help I provide and learning how to do that well and come across sincere and make the guys turning the wrenches feel like you know how to turn a wrench and you've turned many wrenches in your day, you know, and all that stuff. Um, you know, I'd probably say that's inspired me most, at least, you know, on the business side. How's that?

Drew: Yeah, good. Absolutely. What's the best piece of career or life advice that you've ever received?

Ruben Levine: Ruben, I suggest you go back to college, move to New York. If you can succeed in New York, you can succeed anywhere. Bob Affronti, my first boss, after I got out of the army, I was out a little late. So I missed the fall semester at UCLA. So I went back to LA and a buddy of mine got me a job at this insurance company and Bob Affronti, he should rest in peace. My first boss really, really tapped into my essence and became like a real mentor. You know, like I don't want to start crying, but you know, he was a real special guy to me and, uh, yeah, that's what he said to me, like when the tax year, 1986 tax year, I'm showing my age, got shut down and the money we were making, we were making good money. Kind of got shut down. He says, I want you to stop. I want you to go get your college degree now. Don't get caught up in work. Don't make the same mistake and go to New York. You're a nice Jewish boy. If you can make it in New York, you can make it anywhere.

Bill: Oh, that's cool. You know, he, uh, what then?

Ruben Levine: Oh, he was a Brooklyn, Irish Catholic, you know, grew up in Borough Park, knew more Yiddish than my, my grandmother. And, uh, he was a great guy. Uh, I've had good mentors over the years. Uh, but he really set the bar high, you know, how's that for an answer?

Drew: That's great. Yeah. What's a small daily habit or ritual that makes big difference for you?

Ruben Levine: To make sure I touch base with every one of my immediate family. Always call my wife. How was your day? Always look at the family chat. Make sure I love one of the photos or videos and posts of my grandchildren that they put up there for everyone to look at and comment. It's a daily ritual. I want to do it. I want them to know that it's important to me. I take these breaks because I'm, I'm pretty intense, you know, throughout my work day. And if I get interrupted by them, I could be pretty short or even ignore the call, God forbid, three times in a row, even for my wife. So, you know, just making sure I just connect and let everybody know and, and just, you know, draw, you know, pleasure from what it's, what all this really has to all be about. Like, you know, if I get too selfish and this is all about me and my, you know, wanting to change the world of technology, you know, that's secondary to, so it's a daily ritual I go through. And, you know, sometimes more than once, sometimes several times depends on the action going on. Just making sure I'm drawn into it and connected to it.

Bill: Work-life balance, right? Love it. Well, what's one thing your younger self, like when your mentor was talking to you would be shocked that you care about today?

Ruben Levine: Oh God. If it was Bob Affronti, I don't think anything. I think he really saw what I was capable of and what my strengths and weaknesses of. So I don't think he would be shocked. You know, this is Ruben's younger self, not Bob. Yeah. Just being so, you know, in a wholesome, you know, family life, like I am, you know, I grew up, my parents split up when I was in college, I was kind of very much on my own.

Ruben Levine: Talking about the Israel Defense Forces. I went to the IDF because I was in Israel and we lived there as a kid. I was drafted. I could have left and said, no thanks, but I need someone to kind of parent me and grow up. So that's my younger self, pre-military, didn't have much of a work ethic and so on and so forth. And I think the Israeli army gave me great work ethic, but also kind of tightened some screws that needed to be tightened. But, you know, I've got this kind of family. I got children and grandchildren. I'm part of my community and I'm humbled by the kind of people that I rub elbows with. My cap table is really a very, very special group of people that do a lot in this world. And I have a responsibility for that. So if someone would have showed me this movie back then, I would have turned around and said, must be somebody else. And again, I couldn't have planned it that way. I'm just really, really delighted that I get exposed to people who make me want, inspire me to want to be more like them and charge my path, I guess. I don't know any other way to express it. Does that answer your question?

Drew: That's awesome. Like, perfect. I like how you said that, like imagining it like it was a movie. That's very cool. So Ruben, last one. When you're not working, what do you love to do that recharges you?

Ruben Levine: I love to go play a round of golf. There's always in the summer times, this Friday afternoon moment where myself and my buddies go out to a golf course. We walk the golf course to get some exercise. We have little games and just smell the grass out there and enjoy the sunshine and just really, really kind of put a gap between the intense work week and the weekend and then really go home and then just crash. You're tired, but that is a really, really special time in the winter time. I find other ways too, but I usually try to create a couple hours of buffer between Friday night and my work week and just really get into a different mindset. And then it's like a bat out of hell come sometimes Sunday. But it's a sprint while you marathon, I guess. But then you got to chill.

Closing Thoughts and Contact Information

Bill: I love it. The buffer between you and the Friday and the weekend. We'll put these in the show notes, but how should our listeners contact you should they choose and want to?

Ruben Levine: I think ideally through my LinkedIn page and reaching out to me would be great. If this stuff gets published and people get to know me through this medium for sure, tag me. I'd be interested to learn more about you. I'll provide you guys with my email address, again, hopefully my filtering knows how to do a good job at, sometimes when someone who you really might want to hear from or talk to, they also get caught up in your filters. So I actually find that email, although people think that's more personal access sometimes because of our filtering becomes a lot less than you think. So I do see tags when come to me or people try and chat out with me on LinkedIn more so than I would see in my own inbox per se. So how's that for advice to get in touch and again, love to talk, love to refer people, someone in my network is going to help somebody else go ahead and get a job or get a business opportunity or gather some research, the more we just take those extra couple of seconds just to say, yeah, sure. No problem. Get more stars in your star chart, more beans in your string bean.

Drew: Okay. It's really nice meeting you and maybe following this, let's maybe we should huddle up with more of a business agenda because, again, if you want to tap into my market and the people that I'm doing business with, with something intelligent, I could help you get that call, please don't hesitate and anything I can educate you guys about what we do. And if you come across somebody, let me know. We talk again.

Bill: Thank you so much for joining us and to all our listeners out there, thanks as always, and be sure to follow, like, subscribe, and we'll see you all on the next episode.