Deep vs. shallow integrations and the misaligned incentives in commercial real estate

Happy Thursday!

Welcome to this week’s deep dive exclusively for Nexus Pro members. It’s an honor to have you here. This deep dive is a follow up to my recent conversation with Thru Shivakumar. This conversation was a fun one and want to share my takeaways and the full transcript with you below.

In case you missed it in your inbox, you can find the audio or video here:

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Enjoy!

—James

Disclaimer: James is a researcher at the National Renewable Energy Laboratory (NREL). All opinions expressed via Nexus emails, podcasts, or the website belong solely to James. No resources from NREL are used to support Nexus. NREL does not endorse or support any aspect of Nexus.

Outline

• My reaction
• My highlights:
• The difference between smart and intelligent buildings
• Deep integrations and how they help create intelligence
• Defining digital twins and their use cases
• How the incentives in CRE haven’t been aligned for building intelligence
• Why intelligent buildings are more valuable
• IAQ is a big priority - what KPIs are WELL and RESET looking at and how can software platforms build those in?
• Using a digital twin to weigh the decision between IAQ and energy conservation
• The software capabilities cohesion is focused on
• Thru’s COVID outlook

• Full transcript

My reaction

Cohesion’s perspective in this marketplace is unique: they’re led by someone (Thru) who deeply understands the commercial real estate industry. And yet they were spun out of a mechanical and electrical design firm—the people who understand the building systems the best. The team’s experience bridges siloes.

Last week, with Facilio, we saw a company that is bridging the energy/analytics/O&M siloes as their main focus. Cohesion seems to be headed in that direction too, but they’re also focused on other siloes: property management and increasing revenue for the building owner.

As I said during the last two interviews, talking with Thru and others about deep integrations has opened my mind to how limited and shallow many integrations are. I also know how difficult deep integrations will be to implement in most buildings. One of the reasons existing integrations are so shallow is because shallow is easier. My strategy in the past has been to get data flowing as quickly as possible, prove the value, and then hope to go deeper later on. I love the idea of depth from the start, but I think it could be difficult to implement and scale quickly.

Another thought and theme around here is that deep integrations require more from the data model than, say, Haystack or Brick. This will be a follow-up question for Thru, Prabhu, and others: how can the industry learn from their deep integration experience to facilitate interoperability for all?

What do you think?

Highlights

The difference between smart and intelligent buildings

[00:09:33]

• We think that there's a difference between smart and intelligent. I think that-, I'll give you an example, but just kind of from a definitional standpoint, I think smart is really about having smart devices. And you can have a lot of smart devices, smart systems installed into a building. So you could have a lot of smart thermostats, or air quality sensors, or you know, other kinds of IoT devices throughout the building, and even have like a very new access control system that deems itself as smart because it's connected and there's analytics coming off of it.
• But the way we think about buildings in general is that they should be connected. So things in a building don't happen in a silo. Everything, all the operations happen together. And so we can't look at even the data coming off of it in a silo. So the way we define intelligent buildings is that everything is connected. So all of those smart devices are connected. So the systems and the devices are connected, but you can't leave out the most important piece of a building in a building operation And that's really about how humans use space. So a lot of companies that claim, to be smart or intelligent, lack bringing in the human component to it. So without how people use space, you're missing a big piece of the picture.
• So where I define kind of intelligence and how Cohesion defines intelligence is that every part of the building is cohesive, connected, and we're getting analytics that are holistic, that are combined. So we don't just look at HVAC alone. We look at HVAC along with occupancy, of how people use space. We don't look at, you know, visitor management in a silo, as just a siloed kind of workstream. We look at visitor management in combination with how tenants use space and look at occupancy as a whole. So all of these are really in a very holistic manner together. And so that's what we define as intelligence, is a building that's working cohesively together, both the systems and the people.

Deep integrations and how they help create intelligence

[00:12:23]

• deep for us is that we look at an integration in the context of how are we going to push towards an autonomous building. So we look at it as an integration is only as good as what we can command back to it when that building becomes connected.
• And so for us, let's take access control, for example. We can pull data out of the access control system, but we create a user interface where we give tenants the tools to be able to enter and remove new employees. So they take security out of the mix so that it is in real-time that they're adding and removing employees and giving them clearances. Now that's just a workstream. Right? But what we're doing from that is taking the data out of that and being able to say, alright, well, we've got that integration that if people enter in information into our system or the access control system, it's the same data on either end.
• And so when we look at, then, as we look at occupancy and pulling out data of how people use buildings, so when they come in, when they scan, how many badges they have, we have the same data that's in that base access control system in our system as well, so that it could inform HVAC and now we also know, what floors people are on because it's all tied to access control. So our integrations, when I say deep, it's not that we just bypass that system and we have a one-way integration. We want to be able to command back to any of those systems.
  So this is a better one where from an HVAC standpoint, if we only read the data, so if we read the temperature off of a thermostat. That would be one thing. Great. That's information. But we can't make a building smarter if we can't take that occupancy data and say, Hey, let's actually influence the building and make it responsive to the amount of people that are in the building.
• So right now some of the buildings are manually doing that, understanding, right, that occupancy is less than 5% in buildings, you know, due to this crisis that we're in. And so they're manually influencing the building systems to save money and reduce energy waste. But what if the building could do all this on their own? What if the building system could be set up so that it is responsive and it is autonomous? So that's what we're getting to.

Defining digital twins and their use cases:

1. Situational awareness and setting a baseline with the data

2. Advanced automation

3. Stress testing through modeling and prediction

[00:17:23]

• I think that digital twins are definitely a buzzword across many industries, not just real estate. I think that it's still very new in real estate in understanding what are the benefits of a digital twin? I certainly am a huge believer that that's the way everything is going to evolve to But the definition of digital twin in the most simplistic way, it's really that it's a virtual simulation of something in the physical world, and that something is what defines the variance in digital twins.
• And so a BIM model is a digital twin. So think about the construction side of things. That BIM model is a static digital twin of the physical building. So that was kind of the original digital twin. But what we're doing is we're taking it out, you know, past that construction phase, and we're looking at it during operations. So we're saying how does that building operate?
• And again, this concept of holistic and intelligence is really important because some digital twins will show just the operational aspects of it from a systems standpoint, but not from the people standpoint, the human standpoint. So we kind of, in our company, we talk about left brain, right brain on humans and systems. And what we're doing is a holistic kind of brain together on both people and systems.
• I think a lot of things are done manually in buildings right now. And right now nobody can say they have a full view of every single piece of the operation in real time. Right? So you can't see where people are, what the set points of the temperature is, where their system's failing, and what the temperature outside is. Like nobody can tell you that. If they could, then I'd be very intrigued to meet that person. But that alone, nobody can say. And so everybody has aspects of the building that they see together.
• So bring in the digital twin to give a snapshot of time, so that baseline of the operation. And it shows how is it that the building operates. So take eight weeks ago to now. Eight weeks ago, you will have seen, let's say in a million square foot building that's 80% occupied, you will have seen about 1800 people in the building on a Thursday afternoon. So now fast forward to, you know, eight weeks later we're in COVID and 4% of the building is being utilized.So now you can see where-, what you should be able to see is you're now seeing 4% occupancy. So that 1700 people is down to a hundred people. And where are they at, right? What floors are they at? You're going to see that a lot of those people, when you dig into the data, It's a lot of the janitorial staff and the building management staff. It's not as many tenants themselves. And so as you look floor by floor again dependent on mechanical design, you'll see zone by zone what those thermostats are reading. And if you see something at 73 degrees, you're wasting a ton of money.
• And so you can stress test that. You can look at that. Just like baseline views of the digital twin. You could see the operation. Now when you add in the intelligence, where you take the actions and what you see in a digital twin and you say, I'm going to go do something back in the physical building, because you have those integrations and command ability back to the building via the digital twin you could actually change all of those thermostats to go down all in one swoop.
• And so it's giving the tools to be able to be remote. It's being able to stress test. It's being able to look at different scenarios. And it's being able to say, okay, I'm watching trends over time, if this thermostat reads 68 and we keep setting the set point to something else, we're going to start to see faults and patterns over time. And so a lot of this is about self-learning and eventually getting into self-healing on building faults. So that's what I think is a lot of the opportunity. It is a very, you know, intelligent solution.
• It's like you can't sell a Nest to a person that wants kind of an analog thermostat, right? So just think about that when people say, Oh, you can't get into every single building. I'm like, well, the building that doesn't want to even upgrade a system to be networked is not my customer. So they're not the ones that are thinking about it, but there's a lot of people looking at how holistic data is going to be very useful as we come in and out of cycles of recession, right? Where we need to pull triggers to save money, to where can we maintain asset value? Where can we increase that asset value?
• If you know the baseline of operations and how everything works, let's say there's an influx of people, but they, the building occupancy is going to have a huge event or there's a huge political rally or something. There's going to be 3000 people in the building. How are your systems responding? So you can stress test that inside of your digital twin before it actually happens in real life. And what could you do to temperature? How can you impact air quality? What are the sensors that you have to watch for? How can you actually you know, predetermine what you're going to have to do with air handler unit to actually adjust for the HVAC air quality.

How the incentives in CRE haven’t been aligned for building intelligence

[00:24:54]

• So I look at it and the audiences of who we're talking to from an operational perspective. There's the owners that own the building. There's the operations folk that run the building that are paid a fee. Right? And it's a fee most often times based on revenue and their 30 day cancelable contracts. So there's not some longevity to that. And then there's the tenants. And so those are your three big personas inside of a building.
• And the tenants largely up until probably I would say this coworking phenomenon really started picking up in the world where tenants had a voice, they had flexibility, they could demand whatever they wanted to demand, because the flexibility was there. Tenants started to get a voice, and so tenants are parts of the equation, in that they can influence that they want more. So the incentive for a tenant is to have a workspace that is productive, right? First and foremost. It's comfortable. And we did a survey last year that found that tenants really want productivity tools and technology that allowed them to have self service. They don't-, as much as everyone loves to interact with their property management team, it's actually not the case. People just want the tools to do things themselves. So the incentive there is to make sure they focus in on productivity and self service. And those, you know, post-COVID those are changing a little bit, and I'll talk to that in a second.
• But then you look at the operator, and the operator's incentive is not to collect all the data. They'll collect it and disparate sources, right? It's more of a response of what they need to make their day to day jobs easier, and so it's about streamlining workflows. It's about giving answers to questions that, if it's an ownership group that's very involved, they'll get answers to that. So operators tend to be very decision-, and this isn't all operators or property management teams. There are some that are really great. Some of our clients are some of the best and very forward-thinking groups. But really from a property management side, they're not incentivized to really think about making a building holistically smart or holistically intelligent, right? So they're not incentivized to do anything to spend more money on technology, and they're incentivized to keep, you know, keep costs down. And so when you look at how much they're going to spend on technology, they're incentivized to spend the lowest amount of money.
• Then there's the ownership groups, where ownership groups in general are, you know, wanting to keep costs down, but they primarily focus on the revenue side. And what I have heard from a lot of groups where it's institutional investors, where the institutional investor is really largely depending on the property management team to make sure that that property is run the most efficiently and the most, I guess from a P & L standpoint, at the highest margin that it can be. It's pushed down to that team to think that they're doing it the best way they can. And again, these are institutional managers, and then there's ownership groups that are kind of personally managing their own buildings. And those folks really care about looking at every single line item.
• But what we don't see is when you look at a portfolio, how do you make portfolio-wide decisions, right? Because assets trade all the time, you can't have standardization across this system because assets trade in and out. And so the incentive to make everything connected across a portfolio isn't always there. And it depends on kind of their hold strategy from a fund perspective or a real estate perspective, like how long are they going to want to hold the asset? If they trade it and flip it, you know, there's no incentive to invest technology inside of the building that's gonna make it holistically, you know, smarter.
• So that's kinda the part where I think incentives in general to run a smart building, it tends to be about reputation. I want to be better than the building down the street, and I want to differentiate. And so that differentiation tends to put some of those really forward thinking buildings at the forefront of saying, Hey, we're offering you the best product because we're investing in this technology. But again, if it's a developer who does that, they're going to care about the bottom line, not about the longterm operation of it, because likely they're going to flip it over time.
• So I just think that incentives across the capital stack or the operational stack, however you want to define it, it's not aligned to wanting smart tools. And so I think there's going to be a big focus in on the tenants demanding this for it to be industry-wide accepted. If the tenants and the tenants are starting-, so this is now post-COVID world. We're not post yet; we're in COVID world. But they're demanding that they have transparency to air quality measures, which they would have never asked before. So having that transparency, understanding that there's an intelligence side to it, and not just measuring it, but what are you doing to solve it? So again, you could put a bunch of sensors in and you can get data off of it, but if you can't do anything to change the environment based on what the data says, you know, again, you're coming back to a very manual process that now more money, more time, more resources.
• That's not to say that there's not property management groups and, you know, ownership groups that really want their product to be the best. There are definitely groups that are well beyond anybody else that will invest without people telling you why you should invest in technology. Right? So they're way more forward thinking. But I do think that, again, a lot of change gets pushed in real estate from the customer and the tenant and in this instance. So they're going to demand more transparency to systems. So let's start with air quality. I think at some point, from an HVAC standpoint, the industry charges overtime charges for HVAC but the workforce is 24/7, and so that's a misaligned incentive right there where somebody pays 24/7 rent, but they pay for 9 to 5 energy. And so at some point, tenants are gonna push back and say, no, I want all of the kind of energy to match what I'm doing right, when I'm in the space, when my people are in the space. I want it to be responsive to that. And why should I pay any extra because I use my space from 10 to 7 and on weekends where, you know, the tenant next door uses it standard eight to five, old school standard eight to five.
  So I just think that those things are going to be pushed. It's not going to be the landlord that says, Hey, I'm going to innovate this industry. It's going to be the tenant say, this is what I'm going to need from you or else I'm going to go to the next shop over for the next building.

Why intelligent buildings are more valuable

[00:32:09]

• It definitely makes it more valuable. So savings from an intelligent building-, let's take out revenue for a moment and focus in on expense savings. So you'll see savings from utilities, right? And those you could see from energy programs that you know, have been in play for a little bit, but having really that demand responsive HVAC that's responsive to occupancy, it's going to even add more savings even if there's energy efficient systems built in, you'll see more because it's going to be responsive. So you'll see utility savings.

• And if we can, and water is something that's a passion of mine. But I think from a water perspective, it's going to be very different on a municipality by municipality basis. So let's just say utilities are inclusive of water, but how much you can do in water is to be determined. So I think, you know, you've got energy savings, so utility savings.
• Then you've got repairs and maintenance. So from a repairs and maintenance standpoint, if you're actually monitoring, and to say it another way, digital commissioning all of your IoT devices in your system, you're going to see a fault before or when it happens, because you're watching patterns and you're looking at variances. You see something go offline and you see a defunct asset within your building, you're going to know that because it's going to digitally remind you or alert you that something's wrong. So from a repairs and maintenance standpoint, you're going to see a fault before it happens, which is going to save you a lot of money. Because if something trips or if a pipe bursts, a leak is a lot more inexpensive than replacing the pipe before it bursts. So that's where repairs and maintenance are also going to be, you know, a savings.
• And then you look at administrative costs. So an intelligent building, because everything is connected, you're going to actually reduce your software costs, and you could reduce also overhead costs whether that's kind of overtime hours of staff, cutting multiple people in that third shift, whatever that looks like. You can cut the administrative costs, so software, displacement, overhead costs. And then kind of smaller things, like if there's a separate parking management fee that you're paying somebody to manage your executive parking, you could do all of that through an application that's called connected. So administrative costs.
• And then I'd read a stat before that said about, I think it's something like smart buildings are 30% more likely to have tenants stay in them as they looked for lease renewal. So leasing costs would also go down.
• So if you take all of that, and let's say that annually on a very conservative basis, that adds up to 75 cents of savings per square foot, you could roughly say, you know, cap, that you could add value of anywhere between five and $10 million of asset value right off the bat. And that math is not new, right? You heard it from energy when people just sold energy savings. They'd say cap that, and that's an increase in value. You're looking at it from four different buckets. And so that's a pretty large value that you can make up for when you can't influence the revenue as much.
• Then on the revenue side of it, I think there's a lot of platforms out there that talk about tenant engagement, tenant happiness, tenant satisfaction that will increase revenue. I think there's something to that, but I also think that there's hard tools that, you know, a platform can provide such as some optimization opportunities like sharing of amenities across the building portfolio. So let's say an owner or an ownership group has 10 buildings in Chicago, and they have a pool in one building with a massive gym, and then they have a rooftop deck in another, you actually don't have to build that rooftop deck in both buildings, which you know, in Chicago, you get to use it three to six months a year, but you can share those, because what we have done is connected-, the ownership group has the entire portfolio connected , if they want to connect all of their buildings onto a single platform. So you now have access, you can grant access, to all of the different buildings, and you can grant access and restrict permissions of anything else outside of amenities into the different buildings.
• So here you have an example of amenity optimization because you could actually take it a step further, if a building charges for the use of amenities, you can push discounts to nearby buildings. And you can, it gets a little bit tougher to go outside of your portfolio. But, you could look at it if there's property management teams that are the same across different buildings, but, let's just, let's just keep this example to one ownership group. You could share those amenities across the footprint of their portfolio within the city and even like give them access. Like if you were a WeWork member, you get access to all the other WeWorks in the country if you want to go stop anywhere else, or I guess in the world. So why wouldn't ownership groups also who are trying to increase their brand value do the same thing, right? Have a n office available for somebody who's going to New York and doesn't want to sit in a coffee house. Right? Why not just give them the opportunity to you know, be within that and increase their brand value? So that's revenue optimization from an amenities standpoint.
• And then there's the-, we have heard that, you know, from property management teams, they don't always bill the same for amenities across different tenant groups. And so there could be some leakage in terms of, you know, how much they collect based on their favorites because there's not really a process around it that's solidified. So would it equate to a lot of dollars per year? Maybe, you know, depending on the size of the building and depending on how much they charge for the amenity.
• But those are just tactical optimization opportunities that you could have right there. And obviously there's the aspect of, you know, what we originally mentioned was that happier tenants will pay more per square foot for a smart building. And so that is obviously there, but yeah, just kind of honing in on what's practical right now.

IAQ is a big priority - what KPIs are WELL and RESET looking at and how can software platforms build those in?

[00:44:37]

• what we're doing is looking at the different technology that's out there from a sensor standpoint. And we're evaluating it based on what certifications require, so looking at Well Building Certification for IAQ or looking at RESET, which is an international standard as well. Looking at those two and saying, what are the requirements for that certification? But what are all of the different pollutants that you can measure? And so looking at those two, you have different technologies that kind of solve for those two pieces. So that's one piece, it's kind of looking at technology review.
• The second piece is to look at what the building program needs to be. Right now, these indoor air quality programs are pretty expensive. And I think that the big kind of question that, that people have to answer owners have to answer is, is it worth it? To me, I think losing a tenant is pretty hard and it's a big financial hit, and if they want IAQ spend a hundred thousand dollars to deploy the sensors. Of course I'd say that, I'm from the technology side, right? But I do think that when you think about the ROI on this, it's going to be broader to making tenants feel safe and comfortable.
• And so from an IAQ standpoint, we're looking at measurement. So we're doing the tech review, and we're looking at the measurement, and what does it mean to kind of go into dangerous category? And then how do we-, ultimately when we apply that to the digital twin, it's making those active adjustments. So increasing the ventilation rates, you know, influencing kind of the air handler unit and looking at it from an HVAC perspective, but really understanding how many people are in the space too. So you can look at it holistically. And that's what we're designing right now.

Using a digital twin to weigh the decision between IAQ and energy conservation

[00:46:45]

• The way it works right now, it's about the technology and the measurement. When we get into the intelligence side of it, the thing that we need to think about is not only the ability to command back, but it's to learn what's taking the most energy. You know, how can you actually stress test or look at the different scenarios of what you can do to keep those levels down. So looking at people and looking at the pollutants and then looking at the system side, having all of that data, applying machine learning to it, and being able to see the patterns, those are going to help us inform. Do I have an answer of how we're going to actually make sure that energy costs stay down? No, because we need to learn that. There hasn't been as critical of a focus on IAQ until now. Right? And not to say that people haven't been doing it, but it's now at the very forefront of safety and comfort for people to come back.

The software capabilities cohesion is focused on

[00:48:35]

• It's more the latter. So the optimization aspect, we're focusing in on three areas to begin with this year, from a product development standpoint. First is on HVAC. So obviously that one is, you have to go into the set points to be able to command to it, but to optimize it, right, you have to have both. And so from an HVAC perspective, we're looking at scheduling controls and learning, learning the devices, learning the system, and learning human behavior. So that's kind of the, the first step is on ultimately getting to demand responsiveness, pushing energy efficiency. So that's first, in terms of digital twin features.
• The second one is around IAQ that I described already in terms of active adjustments back. And then the third one is about fault detection. So as you look at the different devices-, and it can be on HVAC, it could be on access control, it could be kind of any system that we think about from a fault detection. And also kind of a byproduct of that is asset tracking. So looking at the different devices, assets, asset health, getting a snapshot of that. It's the three areas that we're focusing in on first.
• And from all of that, dashboards and insights are coming out of all of this on a rolling basis. So insights around utilities, insights around occupancy, insights around system performance and how weather affects the people side of it and what patterns can we see on that, affects the systems side of it. And so that's kind of that holistic dataset that we're, you know, we're looking at. Even service requests, how many service requests are coming in and what types of service requests, what tenants, how long is it taking for building management to answer a service request question. For ownership to know that from a property management standpoint, those are all ways to improve the delivery of your product, which for owners,  their product is the space.

Thru’s COVID outlook

[00:55:11]

• You know, COVID-19, every crisis brings about change, right? We heard on a webinar last week or the week before that, I think it was the CEO of Cushman that said, every crisis brings about change, and that will change the world. 9/11 you know, created a TSA. We didn't have TSA pre 9/11, but it's just part of our daily lives.
• And so with COVID, I think what it's bringing light to is, is really focused in on space and how humans use space, right? How can we make it safer? Nobody knows the answer, what we're going to come out like, how we're going to all respond in six months. If we find a vaccine, is everything going to go back to normal or is it going to be that people are a little bit more cautious and more aware of how viruses are transferred.
• And so what I'm excited about is that I actually think that from an industry standpoint of real estate is that this is going to force change for technological innovation in spaces. And I think it's going to shed a light that, you know, where it was very much viewed on a per square foot basis and trying to keep in this technology budget that people, you know, in real estate, that were always smaller than the amenity budget, that you have these great gathering spaces. That might shift over and we might see more money being put into technology solutions versus just the physical spaces.
• And maybe there's a balancing act of both of those. How can you do both? And so I think that, for us being obviously a prop tech company, I think it presents a great opportunity for ourselves to help buildings kind of adapt to this change, be flexible, and continue to, you know, make sure they serve their clients. Cause after all, we're kind of a B to B to C company, right? The people who use our product is both the operations as well as the tenant side of it. So we have a tall order in front of us, I should say. But I'm excited about what this is going to kind of force the industry to rethink some things.

What did you think about these highlights? Let us know in the comments.

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Full transcript

Note: transcript was created using an imperfect machine learning tool and lightly edited by a human (so you can get the gist). Please forgive errors!

James Dice: [00:00:00] Hello friends. Welcome to the Nexus smart buildings technology podcast for smart humans. I'm your host, James Dice. If we haven't met before, I write a weekly newsletter on the same topic. It's also called Nexus. Each week I share what I've learned, my opinions, and what I'm excited about in the quickly evolving world of intelligent buildings. Readers have called Nexus the best way to stay up to date on the future of this industry without all the marketing fluff. You can check it out and subscribe at nexus.substack.com or click the link in the show notes.

Since starting the Nexus newsletter, many of you have reached out to me wanting to talk shop, and we have. After a few weeks of those wonderful conversations, I realized I needed to record and share them with our growing community. So here we are. The Nexus podcast is born. This is our chance to explore and learn what the brightest in our industry together.

One more quick note before we get to this week's episode. I'm a researcher at the National Renewable Energy Laboratory, otherwise known as NREL. All opinions expressed on this podcast belong solely to me or the guest. No resources from NREL are used to support Nexus, and NREL does not endorse or support any aspect of Nexus.

Alright, let's jump in. Episode 7 is a conversation with Thru Shivakumar, CEO and Co-Founder of Cohesion, an intelligent building software platform. We discuss what makes a building intelligent and how deep system integrations help with that. We talk about digital twins, what they're used for, and the operating savings to be had by using them. We cover some of the misalignment of incentives in real estate and much, much more.

This episode of the podcast is directly funded by listeners like you, who have joined the Nexus Pro membership community. You can find info on how to join and support the podcast at nexus.substack.com. You'll also find the show notes, which has links to Cohesion's website and Thru's LinkedIn page.

Without further ado, please enjoy Nexus Podcast Episode 7.

Alright. Hello, Thru. Welcome to the podcast. Please introduce yourself and Cohesion for us.

Thru Shivakumar: [00:02:10] Sounds great. Thanks, James for having me on today. My name is Thru Shivakumar, and I'm the CEO and Co-Founder of Cohesion. We are an intelligent building platform that serves commercial office, large commercial office towers. And I'm happy to kind of be here to talk with you about everything.

James Dice: [00:02:27] Yeah, great to have you. So you and I talked, what, a month ago, something like that, and you told me all about your background before Cohesion. Can you give us a kind of brief rundown of  your background and what you were doing before you started the company?

Thru Shivakumar: [00:02:40] Yeah, absolutely. So I have kind of an atypical career track, but I think that's what you tend to see from people that are running companies that either, you know, they had an idea from the beginning or they kind of fell into it. And I would say that I more fell into this.

I started my career in corporate finance, and I was with pretty traditional large corporations, but I had a very atypical career track. Every kind of role that I had was around with a bit of a change management and turnaround situation, so I had pretty fun experience from that standpoint. Started my career in healthcare, and then quickly pivoted over to Hyatt hotels, which we had bought a brand of hotels. It was called Amerisuites back in the day. And we bought that portfolio, and we recapitalized, rebranded, and started a whole new brand called Hyatt House and Hyatt Place. And that whole concept, it was like being part of a startup at that point, because while I was in finance and asset management, I also got to choose carpet styles for the hotel rooms and the hotel hallways.

So we were a small startup-y team, and so we ended up two years later, proved that the concept was obviously successful, as everyone can see Hyatt Places all around, and they've now launched a new brand called Hyatt centric. So I think that brand continues to grow, which is. Home away from home, the concept of 24/7 F&B.

It was a great experience from that standpoint. That was pre- any sort of kind of software tools from a finance perspective, so I learned Excel really well there, and how to, you know, essentially build macros. as I joke around to my team. That was the start of my software development career and that was the extent of my software development career with Excel macros so.

James Dice: [00:04:30] Yeah. I had a similar Excel macro history before the world of analytics software came around. I was using Excel for that kind of stuff, so I get it.

Thru Shivakumar: [00:04:39] I still think they use it though. I think that pretty much the world continues to use, you know, Excel for, especially the real estate world for any sort of valuation work or, you know, even budgets and things of that nature. So I don't think the days have changed that much. James.

James Dice: [00:04:54] Right, right.

Thru Shivakumar: [00:04:56] So after that, after Hyatt, I went to GE Real Estate where it was another large company, large group of assets. It was parking this time, and parking and hospitality had very similar kind of traits in terms of the revenue side of the equation. Everything was transient revenue, understanding a very small portion of the revenue was repeat customers and trend-based customers so monthly customers. So a lot of it was really understanding the demographics and the trends of how people utilize those assets. But more so you know, in those asset classes, what I saw and what I started to see was that there was a pretty big focus in on expense management and focus on the margin side. And so in a business where you can't rely on longterm leases, like commercial office or multifamily, it becomes a bit harder. You know, you have to focus in on the gross margin. And so I started, and this is, you know, back in ' 07 I started to really dig into: what can we make better through analytics and data, and how can we get more of it?

So I was in finance, but all we had were finance KPIs. And so there was a lack of exposure to the operating KPIs. And I knew there was just a lot more there. And so that's kind of where I started to get very intrigued about the lack of data in the space of real estate overall, when it's the, you know, it's the biggest asset class in the world, really, of these large buildings that are largely managed on the ground level. So it was the start.

And I went and did acquisitions and business development work at a couple of funds, and made my way to the city of Chicago's Economic Development Council. And did some public private work on real estate and infrastructure.

And then I fell into this because I had met the chairman of a company, a large MEP engineering company where he and I, you know, we were having breakfast and we just started talking about a software that the firm had developed with the partner company, a developer. And he said, I think there's something here. I don't know what that is, but you've been involved with startups, and can you help me think about this? So I helped him think about it, saw that there was a massive market potential for connected buildings and intelligent buildings coming soon, I should say. And I think it's finally here and arrived, which is why it's exciting. But I was excited to look into this, and we decided to spin the technology out of that company and start Cohesion. So that's how it all began the humble beginning.

James Dice: [00:07:18] Cool. And that company is ESD, so how are you guys related to them today?

Thru Shivakumar: [00:07:24] Yeah, so it's definitely ESD Global. They are a mechanical, electrical, and plumbing firm, a design engineering firm. So they do a lot of the work on designing how the building works, all the controls, and the mechanical. So they'll do new construction buildings. They'll do retrofits. They do both work, office towers. They'll do critical facilities, like data centers and also workspace tenant design. So they kind of, they're in the design space. So if they're designing, you know, designing the space for their client, they have the opportunity to bring us in. But in terms of the relationship we're really just great channel partners, and they're an investor in our business. And we talk all the time, and we do joint projects, so it's, it's a fun relationship.

James Dice: [00:08:09] Cool. Yeah, I think that's fascinating. I haven't seen a lot of-, I've worked for a design firm in the past, haven't seen a lot of startups spun out of engineering design firms before. So it's definitely a unique, unique point.

Well, that whole history of your career leading up to Cohesion is fascinating. Definitely a lot of stops there. And just to point out to everyone, you guys are out of Chicago, Cohesion, right? So your company is based in Chicago.

Thru Shivakumar: [00:08:35] Correct

James Dice: [00:08:36] Cool. Yeah. So before we kinda dive into the platform you're developing, I wanted to dig into some of the perspectives you could share with our listeners around the smart building space.

And I think it's good to talk to you about it because I get the sense that you're not like-, like I'm an insider, right? I grew up, you know, grew up, but my career was engineering contracting, energy efficiency consulting. I'm very much a product of this industry, whereas I feel like you've been hitting it from a bunch of different angles, slightly outside of operating and maintaining buildings.

So I wanted to kick it off by discussing with you some definitions. So what is a smart building? And I noticed that you guys on your website make the delineation between smart and intelligent. So can you talk about the difference between that, given that both of those are very fuzzy buzzwords at this point in our industry.

Thru Shivakumar: [00:09:33] They are definitely used very interchangeably, for sure. We think that there's a difference between smart and intelligent. I think that-, I'll give you an example, but just kind of from a definitional standpoint, I think smart is really about having smart devices. And you can have a lot of smart devices, smart systems installed into a building. So you could have a lot of smart thermostats, or air quality sensors, or you know, other kinds of IoT devices throughout the building, and even have like a very new access control system that deems itself as smart because it's connected and there's analytics coming off of it.

But the way we think about buildings in general is that they should be connected. So things in a building don't happen in a silo. Everything, all the operations happen together. And so we can't look at even the data coming off of it in a silo. So the way we define intelligent buildings is that everything is connected. So all of those smart devices are connected. So the systems and the devices are connected, but you can't leave out the most important piece of a building in a building operation And that's really about how humans use space. So a lot of companies that claim, to be smart or intelligent, lack bringing in the human component to it. So without how people use space, you're missing a big piece of the picture. So where I define kind of intelligence and how Cohesion defines intelligence is that every part of the building is cohesive, connected, and we're getting analytics that are holistic, that are combined. So we don't just look at HVAC alone. We look at HVAC along with occupancy, of how people use space. We don't look at, you know, visitor management in a silo, as just a siloed kind of work stream. We look at visitor management in combination with how tenants use space and look at occupancy as a whole. So all of these are really in a very holistic manner together. And so that's what we define as intelligence, is a building that's working cohesively together, both the systems and the people.

James Dice: [00:11:42] Yeah. I think that's definitely a differentiator. If I could just restate that back to you, you might have occupancy data that's maybe used for HVAC or occupancy data that's used for space management, but when you have a cohesive platform, you're able to use that same data across all of these different channels. And obviously it's a rising tide, right? The more data is shared between the different channels, the better each channel does at the job it was doing before.

Thru Shivakumar: [00:12:08] Right.

James Dice: [00:12:08] Cool. So you guys also talk about this term deep system integrations. Is that kinda what you mean by deep system integration where you're connecting all of them together, or am I missing the definition on that one? Can  you kind of give us the background there?

Thru Shivakumar: [00:12:23] Sure. So I guess deep for us is that we look at an integration in the context of how are we going to push towards an autonomous building. So we look at it as an integration is only as good as what we can command back to it when that building becomes connected.

And so for us, let's take access control, for example. We can pull data out of the access control system, but we create a user interface where we give tenants the tools to be able to enter and remove new employees. So they take security out of the mix so that it is in real time that they're adding and removing employees and giving them clearances. Now that's just a work stream. Right? But what we're doing from that is taking the data out of that and being able to say, alright, well, we've got that integration that if people enter in information into our system or the access control system, it's the same data on either end.

And so when we look at, then, as we look at occupancy and pulling out data of how people use buildings, so when they come in, when they scan, how many badges they have, we have the same data that's in that base access control system in our system as well, so that it could inform HVAC and now we also know, what floors people are on because it's all tied to access control. So our integrations, when I say deep, it's not that we just bypass that system and we have a one-way integration. We want to be able to command back to any of those systems.

So this is a better one where from an HVAC standpoint, if we only read the data, so if we read the temperature off of a thermostat.

That would be one thing. Great. That's information. But we can't make a building smarter if we can't take that occupancy data and say, Hey, let's actually influence the building and make it responsive to the amount of people that are in the building. So right now some of the buildings are manually doing that, understanding, right ,that occupancy is less than 5% in buildings, you know, due to this crisis that we're in. And so they're manually influencing the building systems to save money and reduce energy waste. But what if the building could do all this on their own? What if the building system could be set up so that it is responsive and it is autonomous? So that's what we're getting to.

James Dice: [00:14:36] No, that's very helpful. Yeah, I didn't put that together just by the term. So it really helps. So I understand it definitely from an analytics perspective. So I've definitely set up a lot of analytics implementations that are one way, and you couldn't easily go back and modify the technology stack to make it two way. You basically have to start over. Right? So, I know there are a lot of people that are listening that are coming at it from that perspective, but like a lot of them are still doing this, where like we talked about Excel macros, maybe like the next, the next step up from Excel macros is like, everyone's pulling data from a SQL database that the building automation system is pushing trends into right now. So if you have that infrastructure set up, you can't then start commanding back to the BAS with what you have set up. So that's definitely fascinating. And I think a lot of people can look at their integration processes and go, are we really set up for this next phase, which is more advanced supervisory control capabilities.

Very cool.

Thru Shivakumar: [00:15:38] Now you've just told me that I needed to change the word deep though on our, on our website, since it's not clear.

That's great feedback.

James Dice: [00:15:46] Yeah. I mean like I do this all day, if I don't know what it means, that's, that's maybe a good filter. I understand what it means now, though so that's good. Cool. So, yeah, and I write about this topic all the time, and I'm always trying to figure out like the right terminology because that's a big thing about our industry is that we don't have standardized terminology.

Thru Shivakumar: [00:16:07] Well, it's new and that's what happens to an emerging industry, right? Buildings have been around forever, but intelligence is new and it's just starting. While people have had ideas, I think my director of marketing, Laura had sent me an article from 2011 about intelligence. And she's like, wait, this started so long ago. And I said, yeah, that's the industry and the industry's you know, ability to change over time. So.

James Dice: [00:16:33] Yeah. I've been talking a lot lately about, I just got the iPhone 11 and I've been-, just from the setup process, so for those of you who don't know you, you set your iPhone next to your old iPhone and you turn on Bluetooth on both devices and it's now set up like literally five minutes later, all your apps are downloaded. They're all logged into. All your settings are exactly the same. So I've been using that analogy for the last couple of weeks because like compare your iPhone to your building, it's just absolutely crazy. Anyway, that's my soap box.

So continuing on our definitions, so in my head, I had Cohesion as a digital twin company. So we can get into the Cohesion platform in a minute. But what do you, how do you define digital twin? That's another buzzword, another difficult term to define right now.

Thru Shivakumar: [00:17:23] Yeah. I think that digital twins are definitely a buzzword across many industries, not just real estate. I think that it's still very new in real estate in understanding what are the benefits of a digital twin? I certainly am a huge believer that that's the way everything is going to evolve to But the definition of digital twin in the most simplistic way, it's really that it's a virtual simulation of something in the physical world, and that something is what defines the variance in digital twins.

And so a BIM model is a digital twin. So think about the construction side of things. That BIM model is a static digital twin of the physical building. So that was kind of the original digital twin. But what we're doing is we're taking it out, you know, past that construction phase, and we're looking at it during operations. So we're saying how does that building operate? And again, this concept of holistic and intelligence is really important because some digital twins will show just the operational aspects of it from a systems standpoint, but not from the people standpoint, the human standpoint. So we kind of, in our company, we talk about left brain, right brain on humans and systems. And what we're doing is a holistic kind of brain together on both people and systems.

So again, one of the key things is integration on our platform. We're pulling out the data from the integrations. We're pulling in the data from our app standpoint and figuring out how people use space, what actions they take, what's important to people, how often they use the space, and pull that together and start to see real time trends, real time operational viewpoints of how the systems and people work together.

James Dice: [00:19:01] Okay. And when you talk to your customers, what do you talk about as far as use cases for digital twins? Because one of the things that I have a hard time with is describing what it is on top of what they're already doing. So like what jobs does it do that they're currently not getting done or they're doing manually, or that type of thing?

Thru Shivakumar: [00:19:22] Yeah. I think a lot of things are done manually in buildings right now. And right now nobody can say they have a full view of every single piece of the operation in real time. Right? So you can't see where people are, what the set points of the temperature is, where their system's failing, and what the temperature outside is. Like nobody can tell you that. If they could, then I'd be very intrigued to meet that person. But that alone, nobody can say. And so everybody has aspects of the building that they see together.

So bring in the digital twin to give a snapshot of time, so that baseline of the operation. And it shows how is it that the building operates. So take eight weeks ago to now. Eight weeks ago, you will have seen, let's say in a million square foot building that's 80% occupied, you will have seen about 1800 people in the building on a Thursday afternoon. You will have seen that the, you know, thermostats widely varied -, let's put this in context of Chicago, not California, but you'll have seen the varying thermostats between 68 and 74 degrees, and you'll see that by zone. And so looking at mechanical zones, now you'll start to understand why we spun out of a mechanical engineering design firm. You know, we start to understand how the building was designed mechanically.

So people often think that an old building can't be smart or intelligent, but there's a lot that you could do, and I'm sure we'll get into this in a bit, but what we can do is give that baseline of the operation itself. Then what you could do is you can actually stress test it. So now fast forward to, you know, eight weeks later we're in COVID and 4% of the building is being utilized.

So now you can see where-, what you should be able to see is you're now seeing 4% occupancy. So that 1700 people is down to a hundred people. And where are they at, right? What floors are they at? You're going to see that a lot of those people, when you dig into the data, It's a lot of the janitorial staff and the building management staff. It's not as many tenants themselves. And so as you look floor by floor again dependent on mechanical design, you'll see zone by zone what those thermostats are reading. And if you see something at 73 degrees, you're wasting a ton of money.

And so you can stress test that. You can look at that. Just like baseline views of the digital twin. You could see the operation. Now when you add in the intelligence, where you take the actions and what you see in a digital twin and you say, I'm going to go do something back in the physical building, because you have those integrations and command ability back to the building via the digital twin you could actually change all of those thermostats to go down all in one swoop.

And so it's giving the tools to be able to be remote. It's being able to stress test. It's being able to look at different scenarios. And it's being able to say, okay, I'm watching trends over time, if this thermostat reads 68 and we keep setting the set point to something else, we're going to start to see faults and patterns over time. And so a lot of this is about self-learning and eventually getting into self-healing on building faults. So that's what I think is a lot of the opportunity. It is a very, you know, intelligent solution.

It's like you can't sell a Nest to a person that wants kind of an analog thermostat, right? So just think about that when people say, Oh, you can't get into every single building. I'm like, well, the building that doesn't want to even upgrade a system to be networked is not my customer. So they're not the ones that are thinking about it, but there's a lot of people looking at how holistic data is going to be very useful as we come in and out of cycles of recession, right? Where we need to pull triggers to save money, to where can we maintain asset value? Where can we increase that asset value?

James Dice: [00:23:03] Fascinating. Cool. I like that. That model there, digital twin value, what do you, what do you mean by stress test? I'm not sure I quite get that term.

Thru Shivakumar: [00:23:12] That's the finance side of me. So what I mean by that is-, let's keep it on the system side and not finance. If you know the baseline of operations and how everything works, let's say there's an influx of people, but they, the building occupancy is going to have a huge event or there's a huge political rally or something. There's going to be 3000 people in the building. How are your systems responding? So you can stress test that inside of your digital twin before it actually happens in real life. And what could you do to temperature? How can you impact air quality? What are the sensors that you have to watch for? How can you actually you know, predetermine what you're going to have to do with air handler unit to actually adjust for the HVAC air quality.

James Dice: [00:23:52] Yeah. You're taking that model and saying, what if this happens?  Alright.  That's all the, the defining we'll do today. It's not all the defining I'll do, cause I feel like this is something that I just do all day, every day. But anyway .

Okay, so I want to talk about incentives. So last time we talked, you shared some interesting insights from your kind of-, I don't know if you feel like an outsider, but I'm just labeling you as an outsider. You know, you're coming at this from a different perspective than me, but you talked about all these ways that the incentives in real estate are not aligned for smart buildings. Like we're just not set up that way. Right? And you named all these different layers, but maybe just introduce that concept for everyone. I'm sure everyone's aware because they're living in it, but I felt the way that you described it was like, Oh yeah, duh. That's actually genius but obvious at the same time. So just introduce that concept for us.

Thru Shivakumar: [00:24:50] Just making it controversial all of a sudden.

James Dice: [00:24:53] Yeah.

Thru Shivakumar: [00:24:54] So I look at it and the audiences of who we're talking to from an operational perspective. There's the owners that own the building. There's the operations folk that run the building that are paid a fee. Right? And it's a fee most often times based on revenue and their 30 day cancelable contracts. So there's not some longevity to that. And then there's the tenants. And so those are your three big personas inside of a building.

And the tenants largely up until probably I would say this coworking phenomenon really started picking up in the world where tenants had a voice, they had flexibility, they could demand whatever they wanted to demand, because the flexibility was there. Tenants started to get a voice, and so tenants are parts of the equation, in that they can influence that they want more. So the incentive for a tenant is to have a workspace that is productive, right? First and foremost. It's comfortable. And we did a survey last year that found that tenants really want productivity tools and technology that allowed them to have self service. They don't-, as much as everyone loves to interact with their property management team, it's actually not the case. People just want the tools to do things themselves. So the incentive there is to make sure they focus in on productivity and self service. And those, you know, post-COVID those are changing a little bit, and I'll talk to that in a second.

But then you look at the operator, and the operator's incentive is not to collect all the data. They'll collect it and disparate sources, right? It's more of a response of what they need to make their day to day jobs easier, and so it's about streamlining workflows. It's about giving answers to questions that, if it's an ownership group that's very involved, they'll get answers to that. So operators tend to be very decision-, and this isn't all operators or property management teams. There are some that are really great. Some of our clients are some of the best and very forward-thinking groups. But really from a property management side, they're not incentivized to really think about making a building holistically smart or holistically intelligent, right? So they're not incentivized to do anything to spend more money on technology, and they're incentivized to keep, you know, keep costs down. And so when you look at how much they're going to spend on technology, they're incentivized to spend the lowest amount of money.

Then there's the ownership groups, where ownership groups in general are, you know, wanting to keep costs down, but they primarily focus on the revenue side. And what I have heard from a lot of groups where it's  institutional investors, where the institutional investor is really largely depending on the property management team to make sure that that property is run the most efficiently and the most, I guess from a P & L standpoint, at the highest margin that it can be. It's pushed down to that team to think that they're doing it the best way they can. And again, these are institutional managers, and then there's ownership groups that are kind of personally managing their own buildings. And those folks really care about looking at every single line item.

But what we don't see is when you look at a portfolio, how do you make portfolio-wide decisions, right? Because assets trade all the time, you can't have standardization across this system because assets trade in and out. And so the incentive to make everything connected across a portfolio isn't always there. And it depends on kind of their hold strategy from a fund perspective or a real estate perspective, like how long are they going to want to hold the asset? If they trade it and flip it, you know, there's no incentive to invest technology inside of the building that's gonna make it holistically, you know, smarter.

So that's kinda the part where I think incentives in general to run a smart building, it tends to be about reputation. I want to be better than the building down the street, and I want to differentiate. And so that differentiation tends to put some of those really forward thinking buildings at the forefront of saying, Hey, we're offering you the best product because we're investing in this technology. But again, if it's a developer who does that, they're going to care about the bottom line, not about the longterm operation of it, because likely they're going to flip it over time.

So I just think that incentives across the capital stack or the operational stack, however you want to define it, it's not aligned to wanting smart tools. And so I think there's going to be a big focus in on the tenants demanding this for it to be industry-wide accepted. If the tenants and the tenants are starting-, so this is now post-COVID world. We're not post yet; we're in COVID world. But they're demanding that they have transparency to air quality measures, which they would have never asked before. So having that transparency, understanding that there's an intelligence side to it, and not just measuring it, but what are you doing to solve it? So again, you could put a bunch of sensors in and you can get data off of it, but if you can't do anything to change the environment based on what the data says, you know, again, you're coming back to a very manual process that now more money, more time, more resources.

James Dice: [00:29:52] Got it. That's fascinating. So if I'm repeating it back to you, what I just heard was like, maybe the old model is you're going to try to talk to the property managers and say, I'm going to give you a really quick payback with energy savings and you can reduce your operating costs. And that used to be all we had. Right?  But I think what you're describing now is like this tenant-focused pressure that's basically like, you will do this. I don't really care about your short-term mindset, your 30 day cancelables. It's like you'll make this building intelligent, or else? Is that kind of the new-?

Thru Shivakumar: [00:30:25] I mean, it's a theory, right? That that's the way it's going to be. That's not to say that there's not property management groups and, you know, ownership groups that really want their product to be the best. There are definitely groups that are well beyond anybody else that will invest without people telling you why you should invest in technology. Right? So they're way more forward thinking. But I do think that, again, a lot of change gets pushed in real estate from the customer and the tenant and in this instance. So they're going to demand more transparency to systems. So let's start with air quality. I think at some point, from an HVAC standpoint, the industry charges overtime charges for HVAC but the workforce is 24/7, and so that's a misaligned incentive right there where somebody pays 24/7 rent, but they pay for 9 to 5 energy. And so at some point, tenants are gonna push back and say, no, I want all of the kind of energy to match what I'm doing right, when I'm in the space, when my people are in the space. I want it to be responsive to that. And why should I pay any extra because I use my space from 10 to 7 and on weekends where, you know, the tenant next door uses it standard eight to five, old school standard eight to five.

So I just think that those things are going to be pushed. It's not going to be the landlord that says, Hey, I'm going to innovate this industry. It's going to be the tenant say, this is what I'm going to need from you or else I'm going to go to the next shop over for the next building.

James Dice: [00:31:54] Got it. Okay. And how about from the owner's standpoint? How does an intelligent building platform make their flipping more, more fruitful for them as they look to, you know, flip buildings in their portfolio

Thru Shivakumar: [00:32:09] It definitely makes it more valuable. So savings from an intelligent building-, let's take out revenue for a moment and focus in on expense savings. So you'll see savings from utilities, right? And those you could see from energy programs that you know, have been in play for a little bit, but having really that demand responsive HVAC that's responsive to occupancy, it's going to even add more savings even if there's energy efficient systems built in, you'll see more because it's going to be responsive. So you'll see utility savings.

And if we can, and water is something that's a passion of mine. But I think from a water perspective, it's going to be very different on a municipality by municipality basis. So let's just say utilities are inclusive of water, but how much you can do in water is to be determined. So I think, you know, you've got energy savings, so utility savings.

Then you've got repairs and maintenance. So from a repairs and maintenance standpoint, if you're actually monitoring, and to say it another way, digital commissioning all of your IoT devices in your system, you're going to see a fault before or when it happens, because you're watching patterns and you're looking at variances. You see something go offline and you see a defunct asset within your building, you're going to know that because it's going to digitally remind you or alert you that something's wrong. So from a repairs and maintenance standpoint, you're going to see a fault before it happens, which is going to save you a lot of money. Because if something trips or if a pipe bursts, a leak is a lot more inexpensive than replacing the pipe before it bursts. So that's where repairs and maintenance are also going to be, you know, a savings.

And then you look at administrative costs. So an intelligent building, because everything is connected, you're going to actually reduce your software costs, and you could reduce also overhead costs whether that's kind of overtime hours of staff, cutting multiple people in that third shift, whatever that looks like. You can cut the administrative costs, so software, displacement, overhead costs. And then kind of smaller things, like if there's a separate parking management fee that you're paying somebody to manage your executive parking, you could do all of that through an application that's called connected. So administrative costs.

And then I'd read a stat before that said about, I think it's something like smart buildings are 30% more likely to have tenants stay in them as they looked for lease renewal. So leasing costs would also go down.

So if you take all of that, and let's say that annually on a very conservative basis, that adds up to 75 cents of savings per square foot, you could roughly say, you know, cap, that you could add value of anywhere between five and $10 million of asset value right off the bat. And that math is not new, right? You heard it from energy when people just sold energy savings. They'd say cap that, and that's an increase in value. You're looking at it from four different buckets. And so that's a pretty large value that you can make up for when you can't influence the revenue as much.

Then on the revenue side of it, if we add in the-

James Dice: [00:35:09] Wait a second. So when you say cap that, I think I know what that means because one of our readers, shout out to Joe. So Joe is one of my readers and he has been giving me a finance lesson, and I'm going to be having him on the podcast soon. But I know what cap that means. I don't think there's a lot of people that know what cap that means. So will you explain that?

Thru Shivakumar: [00:35:28] Yeah. So very simple real estate valuation lesson is that you look at the net operating income of a building. So let's just say for simple, Oh, I'm not going to test my math skills. I'm not going to do the math, but let's just say that net operating income is about a hundred dollars. If you take that, you've heard of revenue multiples, right? When it comes to non real estate companies. You'll put a revenue multiple of some X, you'll say like 10x multiple on the revenue. But in real estate, we like to do things differently. So you flip it and you call it a cap rate. So that 10x is now one over 10, and so you're looking at it, you're dividing out the percent, essentially.

So in Chicago, I think cap rates are now changing because of the environment. But let's say cap rate in Chicago is about 5%. So it's market driven. So you take that a hundred dollars of net operating income divided by that 5% to get the asset value. And obviously I'm not doing real numbers, but so every dollar that you save, if you cap it, that's how you increase value.

James Dice: [00:36:30] Yeah. So it might be 10 to 20 times what the annual energy savings are, or the annual O&M savings is what you were just describing. That might be the actual value when they go to sell.

Thru Shivakumar: [00:36:40] Correct.

James Dice: [00:36:41] Sell the building. So cool. So, yeah, you were going to talk about revenue, for the, from the owner's standpoint.

Thru Shivakumar: [00:36:47] Yeah. I think there's a lot of platforms out there that talk about tenant engagement, tenant happiness, tenant satisfaction that will increase revenue. I think there's something to that, but I also think that there's hard tools that, you know, a platform can provide such as some optimization opportunities like sharing of amenities across the building portfolio. So let's say an owner or an ownership group has 10 buildings in Chicago, and they have a pool in one building with a massive gym, and then they have a rooftop deck in another, you actually don't have to build that rooftop deck in both buildings, which you know, in Chicago, you get to use it three to six months a year, but you can share those, because what we have done is connected-, the ownership group has the entire portfolio connected , if they want to connect all of their buildings onto a single platform. So you now have access, you can grant access, to all of the different buildings, and you can grant access and restrict permissions of anything else outside of amenities into the different buildings.

So here you have an example of amenity optimization because you could actually take it a step further, if a building charges for the use of amenities, you can push discounts to nearby buildings. And you can, it gets a little bit tougher to go outside of your portfolio. But, you could look at it if there's property management teams that are the same across different buildings, but, let's just, let's just keep this example to one ownership group. You could share those amenities across the footprint of their portfolio within the city and even like give them access. Like if you were a WeWork member, you get access to all the other WeWorks in the country if you want to go stop anywhere else, or I guess in the world. So why wouldn't ownership groups also who are trying to increase their brand value do the same thing, right? Have a n office available for somebody who's going to New York and doesn't want to sit in a coffee house. Right? Why not just give them the opportunity to you know, be within that and increase their brand value? So that's revenue optimization from an amenities standpoint.

And then there's the-, we have heard that, you know, from property management teams, they don't always bill the same for amenities across different tenant groups. And so there could be some leakage in terms of, you know, how much they collect based on their favorites because there's not really a process around it that's solidified. So would it equate to a lot of dollars per year? Maybe, you know, depending on the size of the building and depending on how much they charge for the amenity.

But those are just tactical optimization opportunities that you could have right there. And obviously there's the aspect of, you know, what we originally mentioned was that happier tenants will pay more per square foot for a smart building. And so that is obviously there, but yeah, just kind of honing in on what's practical right now.

James Dice: [00:39:32] Totally. Okay so the only other incentive question I have is sort of looking at this from the O & M standpoint. So the way I understand that incentive mess is that a lot of them just want to basically give away their products that they can then make money off of the service contracts.

And so talk a little bit about how that's kind of holding us back as well.

Thru Shivakumar: [00:39:53] Very, very controversial now. You know, it's a hypothesis that we kind of have from a service level agreement standpoint from OEMs that, let's just say you have a big company that has the HVAC equipment. There, the incentives to make it smart so that the system is self healing or identifies faults is not the main incentive of one of those large companies.

Because as you said, right, and just kind of prodded here was that the service level agreements are a lot of where they make the margin on that sale. So like you said, they will give away their, the equipment for very, very low costs to get the contract so that they can hold that service level agreement, which is where they make a lot of their money.

And so I think it doesn't encourage for a smart relationship, right? With the building or intelligent relationship with the building, and so there's not those incentives. It's cutting out that ability to have lock in agreements and have cut that whole piece out from the industry, which has been an issue to innovate because there's so many of those contractors that will work in the building that have that domain knowledge expertise that the building side who's managing the building don't always have, and so you feel this vendor lock in, that an intelligent solution can actually take you out of and give you the opportunity to not have to pay that because you have the tools yourself.

James Dice: [00:41:16] Right. Right. Yeah. Sorry for putting you on the spot.

Thru Shivakumar: [00:41:19] That's okay.

James Dice: [00:41:21] Air everyone's dirty laundry, but, I'll do it myself whenever I fully understand.

Thru Shivakumar: [00:41:26] I'm just going to blame you for it.

James Dice: [00:41:27] No, that's fine. That's fine. Alright, so let's, let's kind of shift over to Cohesion as a company and product real quick.  So it sounds like you guys are in the middle of developing version 1.0? If I'm understanding that properly let me know, but it sounds like you're in the middle of a launch or, where are you at in the products development process?

Thru Shivakumar: [00:41:48] Yeah. So I would call it 2.0. 1.0 was our first product inside of our first building that we had launched with ESD, right. So when we were under ESD as a company, we launched a version one. And version one was really , it was built for that single building, but it was built with bones to be able to build a SaaS platform and take from it and learn from it. But it wasn't a fully scalable platform in and of itself. It fully scaled within the building, but it didn't- , it wasn't a SaaS platform, a commercial SaaS platform. So I call that version one.

And version two now is really about being able to take that product, take our product, and scale it quickly across multiple buildings and portfolios. And so we wanted to make sure that we captured the uniqueness of a building, but in a commercial scalable platform. So that took a lot of work. So we spent a good, good portion of 2019 building and designing the product so that we looked at every use case that could happen within a feature, and thought about it from the depths of what would the tenant want? Again, bringing it back to the human side of it, what would the tenant want and how would they interact with it? What workstreams could we make easier and automate from an operation standpoint, property management standpoint? And then looking at what does the owner want from an insight standpoint. So every feature that we designed was looking at all the different use cases of that and trying to go deep into each feature. So there's my word again, deep. But we tried to make sure that every feature that we had was looking at it from the personas, but then also how does it integrate into the different systems?

So it took us a long time, but I think one thing that we had, which was the, you know, my team that came from ESD and the team at ESD has been very helpful, is to think through some of those from the systems standpoint. My experience is on the operations and asset management standpoint. So we were able to kind of combine that and making sure along the way we do the appropriate product research, working with our existing customers, and also looking at a broader perspective of-, again, kind of looking at the concept that a lot of people work in office buildings and so you could, from a user standpoint, a tenant user standpoint, you can actually ask your friends, and that's product research that works in the office building. So, you know, there's a lot of opportunities to be able to get that feedback.

James Dice: [00:44:16] Okay. Yeah. So you guys have been doing a lot of interviews and getting feedback from a bunch of people, with different users of the building.

So in terms of the platform's capabilities-, and we're kind of running low on time, so I kind of want to do a little rapid fire here. So you mentioned indoor air quality, so talk about the capabilities you're, you're developing for that.

Thru Shivakumar: [00:44:37] Yep. We have that on our product roadmap for at the end of this year. We have now brought it really-,  fast forwared that to starting to look at that right now. So what we're doing is looking at the different technology that's out there from a sensor standpoint. And we're evaluating it based on what certifications require, so looking at Well Building Certification for IAQ or looking at RESET, which is an international standard as well. Looking at those two and saying, what are the requirements for that certification? But what are all of the different pollutants that you can measure? And so looking at those two, you have different technologies that kind of solve for those two pieces. So that's one piece, it's kind of looking at technology review.

The second piece is to look at what the building program needs to be. Right now, these indoor air quality programs are pretty expensive. And I think that the big kind of question that, that people have to answer owners have to answer is, is it worth it? To me, I think losing a tenant is pretty hard and it's a big financial hit, and if they want IAQ spend a hundred thousand dollars to deploy the sensors. Of course I'd say that, I'm from the technology side, right? But I do think that when you think about the ROI on this, it's going to be broader to making tenants feel safe and comfortable.

And so from an IAQ standpoint, we're looking at measurement. So we're doing the tech review, and we're looking at the measurement, and what does it mean to kind of go into dangerous category? And then how do we-, ultimately when we apply that to the digital twin, it's making those active adjustments. So increasing the ventilation rates, you know, influencing kind of the air handler unit and looking at it from an HVAC perspective, but really understanding how many people are in the space too. So you can look at it holistically. And that's what we're designing right now.

James Dice: [00:46:27] Okay. And does that include the energy impact? Because that's something that I haven't really seen a lot of people talk about yet is like, Hey, let's ventilate the hell out of the building. So then we can-

Thru Shivakumar: [00:46:37] Increase our energy costs.

James Dice: [00:46:39] Yeah. But then, I mean that's the number one way to increase energy usage. So how are you guys thinking about that?

Thru Shivakumar: [00:46:45] The way it works right now, it's about the technology and the measurement. When we get into the intelligence side of it, the thing that we need to think about is not only the ability to command back, but it's to learn what's taking the most energy. You know, how can you actually stress test or look at the different scenarios of what you can do to keep those levels down. So looking at people and looking at the pollutants and then looking at the system side, having all of that data, applying machine learning to it, and being able to see the patterns, those are going to help us inform. Do I have an answer of how we're going to actually make sure that energy costs stay down? No, because we need to learn that. There hasn't been as critical of a focus on IAQ until now. Right? And not to say that people haven't been doing it, but it's now at the very forefront of safety and comfort for people to come back.

James Dice: [00:47:34] Yeah. Yeah. Totally. That's a great answer. You don't have to act like you know exactly how this is all going to play out.

Thru Shivakumar: [00:47:39] No, no.

James Dice: [00:47:40] So, but I do think the whole advanced supervisory control - I'm actually writing a deep dive on this right now - the whole advanced supervisory control field of technologies has the potential to weigh those types of factors on its own. We just need to tell it basically what the limits of the optimization are. So if we're not willing to spend over X amount on utilities in order to produce better ventilation, then we can set that limit and the algorithm can kinda respond accordingly. So that's really cool.

So speaking of supervisory control, what are you guys thinking besides-, you talked about basically you connect all the systems together and then now you can use the digital twin to control. So what types of algorithms are you thinking about including as part of that? Is it like, I'm going to manage all my set points or is it getting into more like I just described, like optimizing systems using machine learning for instance?

Thru Shivakumar: [00:48:35] It's more the latter. So the optimization aspect, we're focusing in on three areas to begin with this year, from a product development standpoint. First is on HVAC. So obviously that one is, you have to go into the set points to be able to command to it, but to optimize it, right, you have to have both. And so from an HVAC perspective, we're looking at scheduling controls and learning, learning the devices, learning the system, and learning human behavior. So that's kind of the, the first step is on ultimately getting to demand responsiveness, pushing energy efficiency. So that's first, in terms of digital twin features.

The second one is around IAQ that I described already in terms of active adjustments back. And then the third one is about fault detection. So as you look at the different devices-, and it can be on HVAC, it could be on access control, it could be kind of any system that we think about from a fault detection. And also kind of a byproduct of that is asset tracking. So looking at the different devices, assets, asset health, getting a snapshot of that. It's the three areas that we're focusing in on first.

And from all of that, dashboards and insights are coming out of all of this on a rolling basis. So insights around utilities, insights around occupancy, insights around system performance and how weather affects the people side of it and what patterns can we see on that, affects the systems side of it. And so that's kind of that holistic dataset that we're, you know, we're looking at. Even service requests, how many service requests are coming in and what types of service requests, what tenants, how long is it taking for building management to answer a service request question. For ownership to know that from a property management standpoint, those are all ways to improve the delivery of your product, which for owners,  their product is the space.

James Dice: [00:50:27] Totally. Okay. So let's talk about go to market really quick. So where are you guys at in terms of your launch and then how are you going to go to market once you do launch? Is it direct to owner, or are you going through partners? How's that gonna work?

Thru Shivakumar: [00:50:41] Yep. We are live. So we have already launched.  We have over 7 million square feet of contracts, and we're actually gonna grow into Asia soon. We just landed a really large Asian client that is very forward thinking on intelligence and creating intelligent-

James Dice: [00:50:58] Congrats.

Thru Shivakumar: [00:50:58] Thank you. Intelligent experiences for their tenants. And we're working with a property services company to launch their white label app as well. Can't say it yet, but there will be some exciting news coming out on that.

And so we look at a go to market strategy as kind of twofold. Maybe there's a third that I might add in, but the first one is looking at portfolios.  A single building's investment into an intelligent platform is worth something, but it's incrementally more on a portfolio when you can standardize the data across the different buildings and see the insights across your massive investment. It has a lot of value. So it's valuable to a single building, but it's 10 times more valuable to a portfolio. And so we think that if we target portfolios, right, we can grow within the portfolio, build the relationship, and start to make sure that we're helping our clients optimize all of their portfolio and drive a lot more insights to how they can make the value of their assets in whole better. That's kind of first.

The second is that we look at channel partnerships. In this industry of integrations, we, from a product perspective, we have channel partnerships. So on the product side, we'll partner with them. On the sales side, right, there's integration partners that we are working on getting, so people that will help us implement our products. We also have it from a sales channel partnership, right? So property services teams are the best example, right? How do you pitch new businesses? A lot of new businesses will want technology to come with their services. So how can we jointly go in and pitch both services together?

So the go to market strategy is really focusing in on a very strong channel partnership strategy as well as focusing in on portfolios.

James Dice: [00:52:41] Cool. Well, I didn't realize you were live. That's amazing.

Thru Shivakumar: [00:52:43] Oh, we're live. Yeah.

James Dice: [00:52:46] I'll put Thru's info in the show notes and-

Thru Shivakumar: [00:52:48] There you go. We launched it. Yeah, we launched in February and we've been live-, our commercial platform had launched in February. Our V1 was live for about a year and a half in two of the buildings. And now we're rocking and rolling.

James Dice: [00:53:02] Cool. So how about, how are you guys approaching the pricing model side of this? So is it like a straight SaaS fee or is it, there's an upfront cost as well. How does that work?

Thru Shivakumar: [00:53:12] There is an upfront cost and a Saas fee,  they both are on a per square foot basis. The upfront cost really covers a broad swath of things. So we make it as turnkey for the customer as we can. So we'll come in, we'll do the integration. We don't charge a custom development fee for any integrations of the large systems. So the access control system integration, we're going to do that. Our thought is that we do it, we build it. We're going to continue to see other customers that use it. So we don't want that single building to have to pay for that custom development fee. So we do, you know, we charge this upfront implementation costs that's inclusive of the implementation, the integration, and then the testing. We also, you know, set up the digital twin of the building, the building itself, that virtual building, and then set up the users with all the permissions. So the whole platform is built on permission, so you can make sure that every building is unique on there, how each person works with the platform is unique. And answers all of the kind of security and permissions questions that a building would have or tenants would have.

And then we also, when we launch, after we get the go ahead, we do tenant trainings and we do a lobby launch. So all of that's included in the implementation fee. We also do materials for the tenants so that they have guides. And it's a very, you know, it's a very involved process. We think about it as a partnership. It's a longterm partnership with the building. And so we'll continue on a customer success standpoint, making sure that they get what they want.

You know, when you bring in a SaaS platform, everyone has ideas as to how to improve it. So we will constantly take back that feedback.

James Dice: [00:54:49] Okay. Very cool. So, okay, so as we kind of wrap up here, what are anything you want to talk about that you're excited about in the next couple of months of your development? Obviously COVID-19 is-, it's April 30th for everyone listening to this afterwards. But, we're very much still in the thick of things. And, how are you guys thinking about the next few months to a year at Cohesion?

Thru Shivakumar: [00:55:11] You know, COVID-19, every crisis brings about change, right? We heard on a webinar last week or the week before that, I think it was the CEO of Cushman that said, every crisis brings about change, and that will change the world. 9/11 you know, created a TSA. We didn't have TSA pre 9/11, but it's just part of our daily lives.

And so with COVID, I think what it's bringing light to is, is really focused in on space and how humans use space, right? How can we make it safer? Nobody knows the answer, what we're going to come out like, how we're going to all respond in six months. If we find a vaccine, is everything going to go back to normal or is it going to be that people are a little bit more cautious and more aware of how viruses are transferred. And so what I'm excited about is that I actually think that from an industry standpoint of real estate is that this is going to force change for technological innovation in spaces. And I think it's going to shed a light that, you know, where it was very much viewed on a per square foot basis and trying to keep in this technology budget that people, you know, in real estate, that were always smaller than the amenity budget, that you have these great gathering spaces. That might shift over and we might see more money being put into technology solutions versus just the physical spaces. And maybe there's a balancing act of both of those. How can you do both? And so I think that, for us being obviously a prop tech company, I think it presents a great opportunity for ourselves to help buildings kind of adapt to this change, be flexible, and continue to, you know, make sure they serve their clients. Cause after all, we're kind of a B to B to C company, right? The people who use our product is both the operations as well as the tenant side of it. So we have a tall order in front of us, I should say. But I'm excited about what this is going to kind of force the industry to rethink some things.

James Dice: [00:57:03] Cool. Well, yeah, thanks so much for coming on the show. I enjoyed it. . And I'll put Thru's contact info in the show notes or LinkedIn so everyone can reach out to her. And anything else you want to say before we, before we take off Thru?

Thru Shivakumar: [00:57:17] No, I think, I love what you're doing on these podcasts and I think that, you know, I, I'm excited about and be intelligent building space and so, keep doing what you're doing. I think we all need to hear it.

James Dice: [00:57:28] All right, friends. Thanks for listening to this episode of the Nexus podcast. For more episodes like this and to get the weekly Nexus newsletter, please subscribe at nexus.substack.com. You can find the show notes of this conversation there as well. As always, please reach out on LinkedIn with any thoughts on this episode.

I'd love to hear from you. Have a great day.