Improve CRE NOI by Cutting Energy Waste with Physical AI, with R-Zero CEO Jennifer Nuckles

Jennifer Nuckles is CEO of R-Zero, a physical AI platform that connects building data to continuously uncover energy savings and improve performance, delivering 20-40% HVAC energy savings with no major retrofit required. She previously served as EVP at SoFi and CMO at Zynga, and spent nearly a decade as a Global Business Lead at Clorox. She is a board member and chairperson of the American Lung Association and a trustee at UC Riverside. Based in San Francisco.

(02:04) From room intelligence to physical AI
(03:51) Buildings have known about waste for decades
(05:00) What changed: hardware costs, software, and regulation
(07:33) Energy as a constraint
(08:12) Local Law 97
(10:08) The end of piloting: choosing and deploying
(11:20) R=Zero model
(14:23) Building efficiency investments
(17:40) Savings Expectations: Qualcomm, Stanford Children’s
(21:03) Energy as an NOI lever: 20-40% HVAC savings
(23:53) The autonomous building continuum
(25:22) What building owners get wrong about energy operations
(28:32) Collaboration superpower: Walt Disney and Yannick Noah

🏙️ Learn more:
-Visit R-Zero
-Jennifer Nuckles on LinkedIn

🏙️ In-person Events:
-Finance Forum: NYC | 11/3
-State of Office Forum: NYC | 11/4
-Breakthrough Awards Breakfast | NYC | 12/2
-All upcoming Commercial Observer events

🏙️ Virtual Events:
-AI & Real Estate: You’ve Hired an Alien Superintelligence. Now What?: 11/10

-AI & Innovation Forum: 11/18

🏙️ Connect with Tangent:
-Edward Cohen on LinkedIn
-Zach Aarons on LinkedIn
-Tangent on LinkedIn

Creators and Guests

Host

Edward Cohen

Host & Executive Producer at Tangent

Host

Zach Aarons

Co-Founder & GP at MetaProp

Guest

Jennifer Nuckles

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Jennifer Audio Episode
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Edward: [00:00:00] [00:00:01] I'm [00:00:02] Edward Cohen, [00:00:03] and this is [00:00:04] Tangent, a Commercial [00:00:05] Observer podcast. [00:00:06] [00:00:07] [00:00:08] [00:00:09] [00:00:10] In [00:00:11] 2024, every building on [00:00:12] Earth generated [00:00:13] 9.9 [00:00:14] gigatons of [00:00:15] carbon into the [00:00:16] air just by [00:00:17] operating them. [00:00:18] Heating, [00:00:19] cooling, lighting. [00:00:20] Not from [00:00:21] being built, [00:00:22] from operating. [00:00:23] That is more than [00:00:24] three times [00:00:25] India's [00:00:26] total emissions [00:00:27] the same year, [00:00:28] and that number went [00:00:29] up last year.[00:00:30]

At the same [00:00:31] time, AI [00:00:32] is straining the [00:00:33] grid. Data [00:00:34] centers alone [00:00:35] consume roughly [00:00:36] 1.5% of [00:00:37] global [00:00:38] electricity, and that [00:00:39] share is growing [00:00:40] fast. [00:00:41] The average office [00:00:42] building, on the other [00:00:43] hand, runs at [00:00:44] about [00:00:45] 53% [00:00:46] utilization, and [00:00:47] HVAC is [00:00:48] about 40% of [00:00:49] its energy spend. [00:00:50] The [00:00:51] math on what it costs to [00:00:52] condition space that [00:00:53] nobody is [00:00:54] in is staggering.[00:00:55]

[00:00:56] Joining us today, [00:00:57] the man [00:00:58] adding [00:00:59] energy [00:01:00] efficiency [00:01:01] to the tennis [00:01:02] court every time he [00:01:03] steps on it, [00:01:04] Zach Aarons, [00:01:05] co-founder and [00:01:06] general partner at [00:01:07] MetaPropp.

Zach: Pleasure to [00:01:08] be here. [00:01:09] I [00:01:10] definitely bring the [00:01:11] E [00:01:12] into [00:01:13] energy and energy [00:01:14] [00:01:15] efficiency

Edward: Excited to say [00:01:16] that we do in [00:01:17] fact have the perfect [00:01:18] guest to talk about [00:01:19] this today. Our [00:01:20] guest today is [00:01:21] Jennifer Nuckols, [00:01:22] chairperson and [00:01:23] CEO of [00:01:24] R-Zero. [00:01:25] Jennifer, where does this [00:01:26] podcast find you?

Jennifer: [00:01:27] Hello, [00:01:28] Edward. Hello, Zach. [00:01:29] Thanks for having me. [00:01:30] I'm joining [00:01:31] from the Bay [00:01:32] Area and [00:01:33] representing [00:01:34] R0, here to talk [00:01:35] about how we can [00:01:36] make buildings [00:01:37] continuously [00:01:38] perform [00:01:39] better

Edward: [00:01:40] Fascinating. Let's jump right [00:01:41] into it. you've [00:01:42] gone from [00:01:43] room intelligence [00:01:44] to occupancy [00:01:45] intelligence to [00:01:46] what you're now [00:01:47] calling physical [00:01:48] AI. [00:01:49] Walk us through that [00:01:50] progression and, and [00:01:51] how have you [00:01:52] evolved along with [00:01:53] the needs of [00:01:54] building [00:01:55] operators, [00:01:56] worldwide?

Jennifer: So let me first [00:01:57] explain what we do. [00:01:58] We connect to [00:01:59] systems and data [00:02:00] that are already [00:02:01] inside a [00:02:02] building, and we [00:02:03] use AI to [00:02:04] continuously [00:02:05] understand how the [00:02:06] building's performing, [00:02:07] find where it's [00:02:08] wasting energy [00:02:09] or operating [00:02:10] inefficiently, and [00:02:11] identify and [00:02:12] ultimately take the [00:02:13] actions that will [00:02:14] improve it.

[00:02:15] So that's what we call [00:02:16] continuous [00:02:17] building savings. [00:02:18] When you [00:02:19] ask [00:02:20] about the [00:02:21] movement from room [00:02:22] intelligence [00:02:23] to physical [00:02:24] AI, the [00:02:25] progression has been about [00:02:26] moving from seeing the [00:02:27] physical world [00:02:28] to understanding [00:02:29] it and ultimately [00:02:30] acting upon it. [00:02:31] [00:02:32] And we started [00:02:33] by understanding how [00:02:34] individual rooms are [00:02:35] being used.

[00:02:36] That gave us [00:02:37] a very [00:02:38] rich [00:02:39] occupancy data set. [00:02:40] So think [00:02:41] about like [00:02:42] where people are in [00:02:43] buildings, when [00:02:44] people are in [00:02:45] buildings, where they [00:02:46] go, how they [00:02:47] move, how their [00:02:48] usage changed [00:02:49] throughout the day. This [00:02:50] is down to the, [00:02:51] very [00:02:52] granular, myopic [00:02:53] level both by time [00:02:54] and location. [00:02:55] And then we [00:02:56] connected that intelligence [00:02:57] to the building [00:02:58] itself, and we [00:02:59] did that over BACnet [00:03:00] IP into the [00:03:01] building management [00:03:02] system, the [00:03:03] HVAC system, [00:03:04] the controls, [00:03:05] the thousands of [00:03:06] points that are coming [00:03:07] off of the [00:03:08] BMS.

So [00:03:09] physical AI is [00:03:10] the next step. [00:03:11] We can understand what's [00:03:12] happening in the [00:03:13] physical environment. [00:03:14] We can determine [00:03:15] what should be [00:03:16] happening based on how the [00:03:17] building is actually [00:03:18] being used, [00:03:19] as you mentioned, [00:03:20] and [00:03:21] increasingly take action, [00:03:22] and that's a very [00:03:23] different [00:03:24] proposition from just a [00:03:25] pure building [00:03:26] dashboard that reports [00:03:27] out [00:03:28] insights.

Edward: Thank you for [00:03:29] that. m-most office [00:03:30] buildings still [00:03:31] run HVAC [00:03:32] on fixed [00:03:33] schedules sized [00:03:34] for peak [00:03:35] occupancy that rarely [00:03:36] happens, [00:03:37] especially nowadays with [00:03:38] hybrid [00:03:39] workforces working some days [00:03:40] in office and some [00:03:41] not. how long has [00:03:42] the industry [00:03:43] known this, and, and [00:03:44] why haven't we [00:03:45] fixed it [00:03:46] yet?

Jennifer: [00:03:47] Yeah. The industry's [00:03:48] known for decades that [00:03:49] buildings waste [00:03:50] enormous amounts of [00:03:51] energy. you can [00:03:52] see this when you [00:03:53] drive on a [00:03:54] weekend across a [00:03:55] bridge and look at the [00:03:56] skyscrapers that are [00:03:57] empty, in the [00:03:58] city that you're [00:03:59] passing, and they're all lit up, [00:04:00] right? And you can rest [00:04:01] assured that those [00:04:02] buildings are being [00:04:03] cooled, or heated [00:04:04] between 68 [00:04:05] and 72 degrees [00:04:06] Fahrenheit.

So the [00:04:07] problem really [00:04:08] wasn't [00:04:09] awareness, it was [00:04:10] execution. [00:04:11] Buildings [00:04:12] are, [00:04:13] incredibly unique. [00:04:14] Every BMS is [00:04:15] different. The data's [00:04:16] really [00:04:17] messy. Equipment [00:04:18] is named [00:04:19] differently. [00:04:20] And historically, it's [00:04:21] taken controls [00:04:22] engineers [00:04:23] a [00:04:24] tremendous amount of [00:04:25] work to understand [00:04:26] each and every [00:04:27] building. [00:04:28] So what's changed [00:04:29] is our ability to [00:04:30] use software and [00:04:31] AI to make sense of [00:04:32] that complexity [00:04:33] at scale.

[00:04:34] We don't need to rip [00:04:35] out an entire building, [00:04:36] entire [00:04:37] systems. We can make [00:04:38] the infrastructure [00:04:39] that's already there [00:04:40] much more [00:04:41] [00:04:42] intelligent

Edward: [00:04:43] Zach, building efficiency [00:04:44] has been a [00:04:45] promised [00:04:46] prop tech category [00:04:47] for over a [00:04:48] decade, probably [00:04:49] more. what do you think [00:04:50] has changed in the last [00:04:51] year, last two [00:04:52] years that [00:04:53] makes you think [00:04:54] adoption is, is [00:04:55] actually moving [00:04:56] now?

Zach: Yeah, [00:04:57] ability, [00:04:58] better technology [00:04:59] for accessing the [00:05:00] data. [00:05:01] many years [00:05:02] ago, [00:05:03] speaking from a hardware [00:05:04] perspective, from an [00:05:05] integration [00:05:06] perspective, Jennifer mentioned [00:05:07] BACnet. You had all of [00:05:08] these very [00:05:09] old sort of [00:05:10] systems, [00:05:11] very hard to [00:05:12] connect them together, [00:05:13] very [00:05:14] expensive [00:05:15] to get the hardware in the [00:05:16] building to [00:05:17] acquire the data. [00:05:18] I think [00:05:19] that's definitely much [00:05:20] different just over [00:05:21] the past five years or [00:05:22] so, [00:05:23] and then the [00:05:24] capabilities [00:05:25] of, more on the [00:05:26] software side of [00:05:27] AI able to [00:05:28] analyze, [00:05:29] reams and reams and reams of [00:05:30] data [00:05:31] very [00:05:32] quickly and [00:05:33] [00:05:34] spot [00:05:35] connections and [00:05:36] correlations that [00:05:37] maybe might miss a [00:05:38] human [00:05:39] interpreter of that [00:05:40] data. I think when you [00:05:41] take [00:05:42] those two things, [00:05:43] the [00:05:44] compression of cost and [00:05:45] hardware, [00:05:46] and then [00:05:47] also when you [00:05:48] layer in, [00:05:49] pressures from the [00:05:50] outside [00:05:51] world, [00:05:52] whether [00:05:53] that's a [00:05:54] push for [00:05:55] companies from [00:05:56] their investors [00:05:57] or the broader investment [00:05:58] community to be more [00:05:59] disclosive [00:06:00] about these [00:06:01] data points, [00:06:02] specifically around [00:06:03] energy, but, around [00:06:04] occupancy, other things [00:06:05] too. [00:06:06] And then you [00:06:07] combine that with [00:06:08] the pressure [00:06:09] from [00:06:10] municipal [00:06:11] governments, in the US, [00:06:12] but really around the [00:06:13] world, in certain [00:06:14] pockets of the world, [00:06:15] now [00:06:16] imposing much more [00:06:17] draconian fines, [00:06:18] on buildings [00:06:19] specifically. [00:06:20] I [00:06:21] think it's a perfect [00:06:22] storm of all [00:06:23] these elements [00:06:24] moving into, [00:06:25] uh, a next [00:06:26] generation, of [00:06:27] this sector where... [00:06:28] And [00:06:29] the exciting [00:06:30] thing is that this [00:06:31] type of data [00:06:32] [00:06:33] analysis is now [00:06:34] not just available [00:06:35] to the [00:06:36] most [00:06:37] expensive, fancy, [00:06:38] new class A [00:06:39] office assets. They're [00:06:40] kind of [00:06:41] available to a certain [00:06:42] degree, [00:06:43] across all asset [00:06:44] types, across [00:06:45] all [00:06:46] asset, ages [00:06:47] to a certain degree, [00:06:48] and [00:06:49] within a realm [00:06:50] of more [00:06:51] affordable [00:06:52] budgets.

Edward: And I think that's [00:06:53] an inflection point. I [00:06:54] mean, I, I read a [00:06:55] statistic, can't remember [00:06:56] exactly what it was, [00:06:57] most of the [00:06:58] buildings that we will [00:06:59] have in [00:07:00] 2050, [00:07:01] 2060, or whatever [00:07:02] decade into the future, [00:07:03] we already have them [00:07:04] right now. there will [00:07:05] not be new [00:07:06] buildings. , So [00:07:07] retrofitting [00:07:08] existing buildings is [00:07:09] where we can really [00:07:10] make a [00:07:11] difference in the [00:07:12] operational [00:07:13] cost and the impact to the [00:07:14] environment [00:07:15] ultimately.

and talking about [00:07:16] those external [00:07:17] pressures that [00:07:18] Zach just mentioned, [00:07:19] AI is [00:07:20] straining the grid and, and [00:07:21] driving energy [00:07:22] costs higher. [00:07:23] so Jennifer, how [00:07:24] does that change the [00:07:25] conversation with a [00:07:26] building owner who [00:07:27] has heard the [00:07:28] efficiency pitch [00:07:29] before?

Jennifer: [00:07:30] Yeah, I completely [00:07:31] agree with Zach. What's [00:07:32] super interesting right [00:07:33] now is that [00:07:34] energy [00:07:35] is becoming a [00:07:36] constraint, not [00:07:37] just an expense [00:07:38] item. And [00:07:39] so, with the [00:07:40] build of data [00:07:41] centers, electrifying [00:07:42] [00:07:43] transportation, adding [00:07:44] enormous amounts [00:07:45] of AI [00:07:46] compute loads at [00:07:47] the same [00:07:48] time, [00:07:49] it's becoming a real [00:07:50] problem for building [00:07:51] owners.

And [00:07:52] I think what we should [00:07:53] be asking [00:07:54] is, to [00:07:55] your point, [00:07:56] Edward, where can we [00:07:57] find capacity in the [00:07:58] infrastructure we already [00:07:59] have? [00:08:00] And commercial [00:08:01] buildings are a huge part [00:08:02] of that equation. The [00:08:03] cheapest megawatt is the [00:08:04] one that we [00:08:05] don't need to [00:08:06] generate because we've [00:08:07] eliminated [00:08:08] waste

Edward: [00:08:09] let's move on. [00:08:10] So talking about [00:08:11] regulation, I mean, let's talk about the [00:08:12] sticks. a lot of [00:08:13] them were with [00:08:14] good intentions, [00:08:15] whether they [00:08:16] have been [00:08:17] applied, [00:08:18] implemented, or they have [00:08:19] real teeth [00:08:20] to [00:08:21] incentivize building [00:08:22] owners and operators [00:08:23] to [00:08:24] operate their buildings more [00:08:25] efficiently.

Now that's [00:08:26] still TBD, but [00:08:27] for example, in New York [00:08:28] City, we've had Local [00:08:29] Law 97, [00:08:30] that is fining [00:08:31] buildings for carbon [00:08:32] emissions. Other [00:08:33] cities are [00:08:34] following. has that [00:08:35] shifted the [00:08:36] conversation with an asset [00:08:37] manager who has always [00:08:38] treated energy as [00:08:39] just a line [00:08:40] item?

Jennifer: Yeah, it's, [00:08:41] it's moved [00:08:42] from being [00:08:43] ESG [00:08:44] focused to more [00:08:45] financial, so [00:08:46] really changes the CFO [00:08:47] conversation. [00:08:48] Energy [00:08:49] efficiency isn't just showing [00:08:50] up on a utility bill [00:08:51] anymore. It's [00:08:52] creating compliance [00:08:53] costs, like you mentioned, [00:08:54] Local Law 97 [00:08:55] penalties, which are, [00:08:56] now being [00:08:57] implemented. They were kind [00:08:58] of a slap on [00:08:59] the hand warning [00:09:00] through 2025.

[00:09:01] Now we're in the first [00:09:02] period through [00:09:03] 2030, and by [00:09:04] 2035 these are [00:09:05] significant for [00:09:06] owners and [00:09:07] operators, in New [00:09:08] York City. New York [00:09:09] City led the [00:09:10] way and other [00:09:11] cities are rapidly [00:09:12] following, Philadelphia, [00:09:13] Boston. so when [00:09:14] you increase your [00:09:15] compliance cost, you increase your [00:09:16] energy cost. This [00:09:17] affects your net [00:09:18] operating income.

It [00:09:19] ultimately affects the [00:09:20] asset value. [00:09:21] And [00:09:22] once that happens, [00:09:23] then energy [00:09:24] performance is [00:09:25] not a sustainability [00:09:26] project just [00:09:27] kind of sitting off to the [00:09:28] side. It [00:09:29] becomes [00:09:30] part of how you operate and [00:09:31] protect the [00:09:32] economics of the [00:09:33] asset

Edward: Zach, [00:09:34] curious, I mean, [00:09:35] now that, depending [00:09:36] the asset class, [00:09:37] but within commercial [00:09:38] real estate, [00:09:39] when we've had [00:09:40] near [00:09:41] zero interest rates for [00:09:42] the past 10, [00:09:43] 15 [00:09:44] years owners will always [00:09:45] underwrite rent [00:09:46] increases. [00:09:47] It'll keep [00:09:48] increasing, in most [00:09:49] cases. but now [00:09:50] interest rates are [00:09:51] higher.

they're not high [00:09:52] by historical [00:09:53] standards, let's make that [00:09:54] clear, but they're, [00:09:55] they're higher. [00:09:56] so people are looking at [00:09:57] operations. so [00:09:58] now companies like [00:09:59] R0 [00:10:00] are at the forefront [00:10:01] of improving [00:10:02] operational [00:10:03] efficiency. Has [00:10:04] this also changed how [00:10:05] you look at tech [00:10:06] companies that are [00:10:07] helping [00:10:08] operations be [00:10:09] more efficient in [00:10:10] this new [00:10:11] [00:10:12] non-zero interest rate [00:10:13] environment?

Zach: [00:10:14] Yeah, it's [00:10:15] a necessity. [00:10:16] If, uh, [00:10:17] technology can [00:10:18] help get your [00:10:19] expenses [00:10:20] lower and [00:10:21] you're spending [00:10:22] [00:10:23] less on the [00:10:24] technology and the data [00:10:25] to [00:10:26] do so, [00:10:27] everybody's gonna lean into [00:10:28] that. I [00:10:29] think [00:10:30] experimenting with a bunch [00:10:31] of different AI [00:10:32] solutions, [00:10:33] just for the sake of [00:10:34] it and spending a bunch [00:10:35] of money on [00:10:36] compute [00:10:37] where there's no [00:10:38] [00:10:39] justification in [00:10:40] terms of actual expense [00:10:41] savings, that's [00:10:42] a, hard sell right [00:10:43] now. I [00:10:44] think the era [00:10:45] of [00:10:46] experimentation with [00:10:47] that stuff is, [00:10:48] nearing its end, [00:10:49] and [00:10:50] customers in the [00:10:51] sector [00:10:52] zeroing in on [00:10:53] what [00:10:54] actually is gonna, gonna [00:10:55] move the needle for [00:10:56] them. think the fun [00:10:57] of testing and [00:10:58] piloting is kind of [00:10:59] over. [00:11:00] Now it's [00:11:01] about choosing [00:11:02] and deploying [00:11:03] and rolling [00:11:04] out [00:11:05] cross-portfolio

Edward: [00:11:06] Great time to be [00:11:07] alive. [00:11:08] Jennifer, walk us [00:11:09] through what [00:11:10] R0 does from the [00:11:11] moment sensors [00:11:12] go into the [00:11:13] building to the moment [00:11:14] savings show up [00:11:15] on the utility [00:11:16] bill

Jennifer: [00:11:17] Yeah. So there's, [00:11:18] really two sources of [00:11:19] intelligence. We [00:11:20] can understand [00:11:21] actual [00:11:22] occupancy where [00:11:23] that's relevant, and we [00:11:24] connect [00:11:25] directly to the [00:11:26] existing building [00:11:27] management system [00:11:28] to understand [00:11:29] how the building [00:11:30] itself is [00:11:31] operating. [00:11:32] So from there, we're [00:11:33] continuously [00:11:34] analyzing the building. [00:11:35] Where is energy being [00:11:36] wasted?

[00:11:37] What's operating [00:11:38] incorrectly? [00:11:39] What can be [00:11:40] changed? [00:11:41] And [00:11:42] how do we close that [00:11:43] loop from [00:11:44] identifying an [00:11:45] opportunity to taking [00:11:46] the action [00:11:47] and [00:11:48] measuring the [00:11:49] result? the really [00:11:50] important thing, to [00:11:51] Dak's point, [00:11:52] is we're not asking the [00:11:53] owner [00:11:54] to, trial [00:11:55] or to [00:11:56] test a bunch of different [00:11:57] solutions, or to [00:11:58] replace their current [00:11:59] systems.

[00:12:00] We're making the system [00:12:01] they've already [00:12:02] paid for [00:12:03] perform [00:12:04] better. [00:12:05] And I think this [00:12:06] is, really important [00:12:07] because buildings [00:12:08] don't have a data [00:12:09] problem. [00:12:10] They have an [00:12:11] understanding and [00:12:12] action problem. A, [00:12:13] a large building [00:12:14] has [00:12:15] tens of thousands, [00:12:16] hundreds of [00:12:17] thousands of BMS [00:12:18] points that's [00:12:19] producing data [00:12:20] simultaneously, [00:12:21] continuously.

But this [00:12:22] data's really [00:12:23] messy, and it [00:12:24] doesn't tell them [00:12:25] by itself what's [00:12:26] wrong or what to [00:12:27] do. [00:12:28] So the real value [00:12:29] is [00:12:30] understanding what the points [00:12:31] represent, [00:12:32] how the equipment [00:12:33] relates to how the [00:12:34] building is actually [00:12:35] being used, [00:12:36] what [00:12:37] normal should look like, what's [00:12:38] actually happening, [00:12:39] and what's wasting [00:12:40] energy, and [00:12:41] then determining the [00:12:42] actions to take and taking [00:12:43] them.

And that's [00:12:44] really where AI is [00:12:45] [00:12:46] transformative

Edward: walk us [00:12:47] through what, a [00:12:48] deployment [00:12:49] looks like. I've read [00:12:50] that [00:12:51] R0, in a building [00:12:52] of over one million [00:12:53] square feet, was [00:12:54] installed in about [00:12:55] eight hours [00:12:56] overnight. I mean, that [00:12:57] sounds [00:12:58] insane, [00:12:59] insanely good. but yeah, [00:13:00] walk us through, that [00:13:01] kind of speed [00:13:02] change, and [00:13:03] adoption, for what a [00:13:04] building owner can [00:13:05] expect.

Jennifer: Yeah. [00:13:06] So that's [00:13:07] exactly what makes the [00:13:08] model [00:13:09] interesting, to Zach's point, [00:13:10] what we can do so [00:13:11] quickly now. So [00:13:12] a million square foot [00:13:13] building, for [00:13:14] example, sounds [00:13:15] like it should [00:13:16] require a massive [00:13:17] retrofit, and it [00:13:18] doesn't. We're [00:13:19] sitting on top of [00:13:20] infrastructure that's already [00:13:21] there. [00:13:22] Dramatically changes [00:13:23] the adoption [00:13:24] equation because now we can [00:13:25] talk about software [00:13:26] deployment [00:13:27] timelines rather than [00:13:28] construction [00:13:29] timelines [00:13:30] and, [00:13:31] operating expense [00:13:32] rather than a [00:13:33] multimillion-dollar [00:13:34] capital project.[00:13:35]

So for [00:13:36] sensors to be in de- [00:13:37] deployed, these [00:13:38] are [00:13:39] readily [00:13:40] available, easy to [00:13:41] deploy sensors. [00:13:42] They're attached [00:13:43] overnight. our system [00:13:44] then integrates within the [00:13:45] BMS. We start [00:13:46] trending [00:13:47] historical [00:13:48] data, that the client [00:13:49] gives us in advance, [00:13:50] and then we start [00:13:51] managing the [00:13:52] building over the [00:13:53] first two weeks to [00:13:54] kind of get a [00:13:55] baseline, and then we [00:13:56] start [00:13:57] prioritizing changes [00:13:58] and [00:13:59] writing back to the [00:14:00] BMS.

[00:14:01] We typically take [00:14:02] about, four to [00:14:03] six weeks in order to [00:14:04] see, the [00:14:05] recognized utility [00:14:06] savings, and that's [00:14:07] as a result [00:14:08] of the utility [00:14:09] period. It typically takes [00:14:10] about a month to get a [00:14:11] utility bill. [00:14:12] And then using [00:14:13] independent [00:14:14] third-party [00:14:15] measurement and [00:14:16] verification, the [00:14:17] savings are passed through to the [00:14:18] customer

Edward: [00:14:19] Zach, there's a [00:14:20] lot of North [00:14:21] Star metrics you [00:14:22] can measure [00:14:23] how impactful a [00:14:24] solution, [00:14:25] a tech solution you've [00:14:26] invested in is, [00:14:27] performing as expected [00:14:28] or will, want to [00:14:29] be adopted by that [00:14:30] building next door. [00:14:31] But, like, [00:14:32] is there a metric [00:14:33] that you look at [00:14:34] or metrics [00:14:35] that you look at [00:14:36] to, say, "Okay, [00:14:37] this [00:14:38] solution is [00:14:39] better than the [00:14:40] rest or better than [00:14:41] existing, and [00:14:42] worth our [00:14:43] investment or [00:14:44] worth our [00:14:45] LPs looking [00:14:46] at it to, [00:14:47] adopt it in their [00:14:48] buildings"?

Zach: Yeah, a [00:14:49] lot of that depends [00:14:50] on what [00:14:51] the business model [00:14:52] is. [00:14:53] so if [00:14:54] you're an [00:14:55] AI-enabled [00:14:56] service [00:14:57] provider [00:14:58] that's just looking to [00:14:59] displace [00:15:00] a, [00:15:01] existing [00:15:02] analog [00:15:03] service provider, you [00:15:04] might [00:15:05] think about [00:15:06] it in [00:15:07] terms of [00:15:08] [00:15:09] speed of [00:15:10] delivery,

Edward: [00:15:11] Ühüm.

Zach: and [00:15:12] then, [00:15:13] accuracy [00:15:14] of output. [00:15:15] if you can [00:15:16] definitely [00:15:17] deliver Your [00:15:18] solution, [00:15:19] let's say it's [00:15:20] a [00:15:21] due diligence [00:15:22] report. [00:15:23] You can deliver it [00:15:24] significantly [00:15:25] faster and [00:15:26] significantly more [00:15:27] accurate. [00:15:28] And you can do [00:15:29] that at [00:15:30] a contribution [00:15:31] margin profile that [00:15:32] makes [00:15:33] sense. you're kind of just [00:15:34] pricing off [00:15:35] what the [00:15:36] analog [00:15:37] leader incumbent is [00:15:38] doing and just [00:15:39] trying to discount [00:15:40] a little bit [00:15:41] from that, right? Or [00:15:42] stay close to par and [00:15:43] say you can do it faster and [00:15:44] better. although I [00:15:45] like to discount [00:15:46] a little bit [00:15:47] because theoretically, if [00:15:48] you're [00:15:49] AI-enabled and [00:15:50] more efficient, you [00:15:51] should have [00:15:52] fatter [00:15:53] margins than [00:15:54] the [00:15:55] incumbent to sort of play [00:15:56] with. if you're [00:15:57] selling more of [00:15:58] a [00:15:59] technology [00:16:00] product or [00:16:01] agentic [00:16:02] [00:16:03] product, [00:16:04] yeah, one is [00:16:05] it, meaningfully [00:16:06] better than [00:16:07] what came before? [00:16:08] Right. In the [00:16:09] last wave, it [00:16:10] was things [00:16:11] going digital that [00:16:12] were, in this case, kind [00:16:13] of kept on [00:16:14] clipboards. [00:16:15] So you knew that the, [00:16:16] product and the data [00:16:17] integrity was gonna be [00:16:18] better, even if the [00:16:19] usability [00:16:20] was, clunky.[00:16:21]

Edward: Right. It was a low [00:16:22] bar

Zach: [00:16:23] yeah, now that you're in [00:16:24] the agentic era, [00:16:25] the question is, okay, [00:16:26] is this, product [00:16:27] so much [00:16:28] better [00:16:29] than [00:16:30] if the existing [00:16:31] software [00:16:32] provider just [00:16:33] delivered an MCP [00:16:34] server [00:16:35] and let you [00:16:36] interact with their [00:16:37] existing data?[00:16:38]

And that's [00:16:39] the sort of [00:16:40] major [00:16:41] question. I [00:16:42] think, we [00:16:43] rarely discover [00:16:44] categories [00:16:45] anymore where it's [00:16:46] like [00:16:47] pricing hasn't been [00:16:48] established by [00:16:49] [00:16:50] something

in the

Edward: [00:16:51] Ühüm.[00:16:52]

Zach: whether that's an [00:16:53] incumbent services [00:16:54] company, a [00:16:55] hardware, [00:16:56] systems [00:16:57] company. the [00:16:58] case of [00:16:59] the R0 [00:17:00] example, right, there are [00:17:01] companies like [00:17:02] Johnson Controls and [00:17:03] Honeywell and [00:17:04] Schneider, [00:17:05] many [00:17:06] hundreds of years old, [00:17:07] right, have been [00:17:08] selling with particular [00:17:09] pricing models. [00:17:10] so you're really [00:17:11] looking to come in [00:17:12] as, faster, better, [00:17:13] cheaper. I think [00:17:14] that's how you [00:17:15] win business. [00:17:16] it's very [00:17:17] competitive, right? You're [00:17:18] always [00:17:19] competing against analog [00:17:20] players. You're [00:17:21] competing against, [00:17:22] call it [00:17:23] Web [00:17:24] 2.0 [00:17:25] players who are [00:17:26] spinning up their own [00:17:27] agentic capabilities, and [00:17:28] then you're competing [00:17:29] against your [00:17:30] [00:17:31] direct, AI [00:17:32] native, crop of [00:17:33] companies[00:17:34]

for business.[00:17:35]

Edward: [00:17:36] Yeah. Jennifer, [00:17:37] according [00:17:38] to, some case studies, [00:17:39] you've [00:17:40] helped [00:17:41] Qualcomm save [00:17:42] about [00:17:43] 40%, uh, of their [00:17:44] HVAC energy. [00:17:45] you've also helped [00:17:46] Stanford, [00:17:47] save, about [00:17:48] 29%, both [00:17:49] impressive numbers. [00:17:50] what determines [00:17:51] where a [00:17:52] building or a [00:17:53] facility lands in [00:17:54] that range in [00:17:55] terms of setting [00:17:56] [00:17:57] expectations?

Jennifer: Yeah. [00:17:58] So the [00:17:59] baseline matters [00:18:00] significantly. We [00:18:01] don't promise [00:18:02] every building the [00:18:03] same percentage [00:18:04] because every [00:18:05] building starts in a different [00:18:06] place. [00:18:07] So at Ch- Stanford [00:18:08] Children's, for [00:18:09] example, we [00:18:10] measured [00:18:11] 29% HVAC [00:18:12] energy savings in the first [00:18:13] 60 days [00:18:14] without replacing their [00:18:15] HVAC. what we [00:18:16] found is that [00:18:17] buildings already have the [00:18:18] equipment and controls [00:18:19] necessary to operate much [00:18:20] more efficiently.

This [00:18:21] is exactly to Zach's [00:18:22] point. We [00:18:23] are BMS [00:18:24] agnostic. So [00:18:25] let me bring this [00:18:26] home to you, like what [00:18:27] waste looks [00:18:28] like. [00:18:29] It's really obvious [00:18:30] once you can see it. You [00:18:31] go into a conference [00:18:32] room designed for [00:18:33] 30 people [00:18:34] that's being [00:18:35] ventilated as though [00:18:36] 30 people are sitting in [00:18:37] it when it's [00:18:38] one to two people [00:18:39] sitting inside.[00:18:40]

You find [00:18:41] outside air [00:18:42] being brought in and [00:18:43] conditioned overnight [00:18:44] when very few [00:18:45] people are in the [00:18:46] building. [00:18:47] You find [00:18:48] equipment fighting other [00:18:49] equipment. Many [00:18:50] of our cases, we see [00:18:51] heating and cooling [00:18:52] going on [00:18:53] simultaneously in a [00:18:54] building. [00:18:55] So, the buildings aren't [00:18:56] intentionally wasting [00:18:57] energy.

They're [00:18:58] doing exactly [00:18:59] what somebody [00:19:00] programmed them to do. The [00:19:01] Honeywells, the JCIs, [00:19:02] the Snyders of the [00:19:03] world, [00:19:04] they were programmed [00:19:05] sometimes years ago, [00:19:06] regardless of [00:19:07] what's [00:19:08] happening today. So I [00:19:09] think that's the [00:19:10] actual [00:19:11] interesting [00:19:12] trifecta. When you [00:19:13] combine how the [00:19:14] buildings are actually being [00:19:15] utilized, [00:19:16] you ensure that the [00:19:17] BMS is [00:19:18] operating to that [00:19:19] utilization, [00:19:20] and you [00:19:21] include environmental [00:19:22] data such [00:19:23] as [00:19:24] humidity, temperature from [00:19:25] outside, [00:19:26] and you bring [00:19:27] those all together, [00:19:28] and that hasn't been able to [00:19:29] be done before [00:19:30] quickly, [00:19:31] real time, you know, [00:19:32] at the by [00:19:33] second [00:19:34] intervals

Edward: Ühüm. [00:19:35] Talk about [00:19:36] the business [00:19:37] model, because if I [00:19:38] understood [00:19:39] correctly, R0 takes a [00:19:40] share of the energy [00:19:41] savings rather [00:19:42] than charging upfront, [00:19:43] which seems [00:19:44] much more aligned. [00:19:45] how does that change the [00:19:46] conversation with a [00:19:47] building operator who has [00:19:48] been perhaps [00:19:49] burned by [00:19:50] PropTech [00:19:51] promises, before?

Jennifer: [00:19:52] Yeah. So what [00:19:53] we did [00:19:54] was try to make the [00:19:55] economics very [00:19:56] different from a [00:19:57] traditional energy [00:19:58] retrofit, [00:19:59] in order to [00:20:00] remove the friction from the [00:20:01] buying cycle. [00:20:02] So [00:20:03] remove the reasons [00:20:04] historically [00:20:05] owners that have [00:20:06] not done the [00:20:07] projects, which [00:20:08] are [00:20:09] capital, [00:20:10] complexity, [00:20:11] disruption, long [00:20:12] payback [00:20:13] periods. And if [00:20:14] we can connect [00:20:15] directly to the [00:20:16] infrastructure that's already there, [00:20:17] we demonstrate the [00:20:18] savings quickly, [00:20:19] we make the economics [00:20:20] compelling [00:20:21] by [00:20:22] taking a portion [00:20:23] of the [00:20:24] savings.

And so there's no [00:20:25] upfront cost to the [00:20:26] customer, and [00:20:27] then we take a small [00:20:28] percentage of it, they take the [00:20:29] lion's share of it, [00:20:30] going forward. And we're [00:20:31] continuously [00:20:32] optimizing the building [00:20:33] so that the baseline is [00:20:34] reestablished. , [00:20:35] It's not just the HVAC [00:20:36] energy, as I [00:20:37] mentioned. There's also [00:20:38] the, [00:20:39] basically light [00:20:40] FDD [00:20:41] when equipment is [00:20:42] not operating as it should [00:20:43] be, or when, [00:20:44] boxes are stuck [00:20:45] or dampers are [00:20:46] stuck, or you see, [00:20:47] like, the [00:20:48] simultaneously heating [00:20:49] and cooling that I [00:20:50] mentioned, just buildings [00:20:51] not operating as they should [00:20:52] be

Edward: [00:20:53] Ühüm. Very, [00:20:54] very interesting. [00:20:55] let's move on to [00:20:56] the, zooming into [00:20:57] the NOI [00:20:58] and the portfolio [00:20:59] angle, for asset [00:21:00] managers. So, you [00:21:01] said that [00:21:02] energy is shifting [00:21:03] from a cost driver to [00:21:04] an asset lever. [00:21:05] what does that mean for an [00:21:06] asset manager running a [00:21:07] portfolio right [00:21:08] now?

Jennifer: [00:21:09] Yeah. So owners are [00:21:10] under [00:21:11] incredible pressure right now [00:21:12] to find NOI, [00:21:13] net operating [00:21:14] income. , In many [00:21:15] markets, we [00:21:16] can't simply [00:21:17] assume rent growth will [00:21:18] solve the [00:21:19] problem. you [00:21:20] mentioned the vacancy [00:21:21] rates that buildings are [00:21:22] continually [00:21:23] seeing. It [00:21:24] doesn't mean that [00:21:25] leases aren't [00:21:26] fully leased out, but [00:21:27] the buildings aren't [00:21:28] occupied, and we've seen that over [00:21:29] the past six years.[00:21:30]

So [00:21:31] owners don't necessarily [00:21:32] want another large [00:21:33] capital [00:21:34] program. Energy is [00:21:35] really [00:21:36] attractive because it's one [00:21:37] of the operating [00:21:38] expenses they [00:21:39] can control. As you [00:21:40] mentioned, [00:21:41] energy is a [00:21:42] significant line item [00:21:43] in operating a [00:21:44] building. If I [00:21:45] can improve building [00:21:46] performance using [00:21:47] infrastructure you [00:21:48] already have, [00:21:49] that's a very [00:21:50] different economic [00:21:51] [00:21:52] proposition than [00:21:53] asking you for another [00:21:54] major capital [00:21:55] investment[00:21:56]

Edward: Mm-hmm. [00:21:57] Mm-hmm. you work [00:21:58] across commercial [00:21:59] real estate asset [00:22:00] classes. is there a [00:22:01] particular asset class that is [00:22:02] moving faster [00:22:03] towards, [00:22:04] operational [00:22:05] efficiency, as the [00:22:06] lever, or [00:22:07] any one that stands out?[00:22:08]

Jennifer: Yeah. [00:22:09] So I, I [00:22:10] think the key here [00:22:11] is we are [00:22:12] seeing the [00:22:13] supply [00:22:14] wherever the building is [00:22:15] complex enough that [00:22:16] the owner has [00:22:17] real pressure [00:22:18] on operating [00:22:19] performance. Can be [00:22:20] commercial real estate, [00:22:21] healthcare, [00:22:22] higher ed, [00:22:23] large, large corporate [00:22:24] campuses. [00:22:25] What's interesting is [00:22:26] that the motivation [00:22:27] is often different.

[00:22:28] A commercial [00:22:29] owner, [00:22:30] serial owner, like we just [00:22:31] said, [00:22:32] would lead with [00:22:33] NOI. [00:22:34] University may care [00:22:35] about energy and carbon [00:22:36] commitments. A [00:22:37] hospital [00:22:38] has [00:22:39] enormous [00:22:40] energy [00:22:41] intensity, but also [00:22:42] really strong [00:22:43] operating [00:22:44] requirements. So [00:22:45] the underlying [00:22:46] technology problem is [00:22:47] really similar, [00:22:48] but the [00:22:49] motivations are very [00:22:50] different for the buying [00:22:51] classes. And I think [00:22:52] healthcare is a, is [00:22:53] probably a, [00:22:54] a really strong [00:22:55] example [00:22:56] because it's [00:22:57] one of the best [00:22:58] tests of the [00:22:59] thesis because you don't get [00:23:00] to optimize [00:23:01] energy at the [00:23:02] expense of the building's [00:23:03] [00:23:04] mission. operating [00:23:05] requirements come [00:23:06] first. the [00:23:07] significance of achieving [00:23:08] 29% [00:23:09] HVAC energy savings [00:23:10] at Stanford [00:23:11] isn't just the [00:23:12] percentage, it's that you [00:23:13] can use [00:23:14] intelligence [00:23:15] to find [00:23:16] substantial [00:23:17] savings [00:23:18] while operating [00:23:19] within a very [00:23:20] demanding [00:23:21] environment.

If you can [00:23:22] do this in [00:23:23] healthcare, which is, [00:23:24] gold star [00:23:25] of, operating [00:23:26] requirements, says a [00:23:27] lot about what's [00:23:28] possible [00:23:29] elsewhere

Edward: taking a [00:23:30] tangent here [00:23:31] relevant to healthcare, I [00:23:32] wonder if this, [00:23:33] savings can trickle down [00:23:34] to healthcare [00:23:35] savings, [00:23:36] eventually. [00:23:37] one step at a time. [00:23:38] One can only hope [00:23:39] so [00:23:40] you've described the North [00:23:41] Star [00:23:42] as autonomous [00:23:43] buildings. [00:23:44] What does that look like [00:23:45] in practice, and how [00:23:46] are, how far away [00:23:47] are we from [00:23:48] autonomous buildings from [00:23:49] an energy [00:23:50] efficiency [00:23:51] perspective?

Jennifer: Yeah. [00:23:52] So I think of [00:23:53] autonomy as a [00:23:54] continuum. Today, [00:23:55] most buildings [00:23:56] tell us what's [00:23:57] happening. [00:23:58] Then software started [00:23:59] telling us what's [00:24:00] wrong. We're moving [00:24:01] towards systems that [00:24:02] can determine [00:24:03] what should [00:24:04] happen, [00:24:05] take the appropriate [00:24:06] action, and then [00:24:07] measure whether it [00:24:08] worked. So [00:24:09] in my perspective, [00:24:10] the North [00:24:11] Star is a building that [00:24:12] [00:24:13] continuously [00:24:14] identifies, [00:24:15] senses, [00:24:16] understands, [00:24:17] decides, [00:24:18] acts, and [00:24:19] continuously [00:24:20] optimizes.

A [00:24:21] building engineer, [00:24:22] we mentioned the clipboards [00:24:23] earlier in the [00:24:24] conversation. A building [00:24:25] engineer shouldn't have to [00:24:26] spend the day [00:24:27] navigating [00:24:28] dashboards and thousands of data [00:24:29] points. [00:24:30] They should be able to [00:24:31] ask, "What's [00:24:32] wasting the most energy in [00:24:33] my building today? [00:24:34] Why did my [00:24:35] costs increase [00:24:36] this week versus [00:24:37] last?"

[00:24:38] Ultimately, the building [00:24:39] should already be addressing [00:24:40] the things it's [00:24:41] authorized to [00:24:42] fix. [00:24:43] And I [00:24:44] think this is really [00:24:45] important, and it's a [00:24:46] really great time to be [00:24:47] alive because it's [00:24:48] the [00:24:49] first time that we can [00:24:50] use software [00:24:51] and AI, to [00:24:52] continuously [00:24:53] address and fix [00:24:54] [00:24:55] automatically

Edward: it's always a [00:24:56] convergence, right? I [00:24:57] mean, a lot of these [00:24:58] conversations and these [00:24:59] technologies, it seems [00:25:00] like they've been [00:25:01] around for longer [00:25:02] than, than what the [00:25:03] impact they've had. But [00:25:04] it's [00:25:05] now with [00:25:06] AI, with the [00:25:07] regulation, [00:25:08] and [00:25:09] with better [00:25:10] hardware as well, [00:25:11] communicating to [00:25:12] the [00:25:13] software, , to, [00:25:14] report on the data to act [00:25:15] on it, and [00:25:16] we're finally [00:25:17] seeing it, which is super [00:25:18] exciting.

[00:25:19] Zach, what do you [00:25:20] think is something [00:25:21] that building [00:25:22] owners aren't [00:25:23] taking into [00:25:24] account [00:25:25] when they think about [00:25:26] operational [00:25:27] efficiency? Or [00:25:28] what do you think they're not [00:25:29] asking, when, when they are [00:25:30] considering adopting [00:25:31] technologies like [00:25:32] R0?

Zach: [00:25:33] I think a [00:25:34] lot of people [00:25:35] wait [00:25:36] for the [00:25:37] [00:25:38] municipal punitive [00:25:39] legislature to [00:25:40] come [00:25:41] before they [00:25:42] act

rather than [00:25:43] [00:25:44] anticipating that it [00:25:45] will [00:25:46] arrive in some way, [00:25:47] shape, or form. [00:25:48] this is [00:25:49] done by staying [00:25:50] engaged in [00:25:51] [00:25:52] communities, seeing where the wind's [00:25:53] [00:25:54] blowing. but the landlords who've [00:25:55] been in New [00:25:56] York who've [00:25:57] been looking [00:25:58] at the [00:25:59] impacts of Local Law [00:26:00] ninety-seven for the [00:26:01] past [00:26:02] three, four [00:26:03] years are in much [00:26:04] better shape now that it's [00:26:05] actually starting to [00:26:06] bite than the [00:26:07] people who [00:26:08] are just [00:26:09] really [00:26:10] waking up to it because they [00:26:11] have to, [00:26:12] today. that's [00:26:13] probably one area [00:26:14] where I think, [00:26:15] [00:26:16] everybody most likely [00:26:17] can, [00:26:18] improve. there was [00:26:19] also [00:26:20] the other [00:26:21] side of that is [00:26:22] there was a, big [00:26:23] push [00:26:24] that there was gonna [00:26:25] be... [00:26:26] This was [00:26:27] back in [00:26:28] the Biden [00:26:29] [00:26:30] administration. There was [00:26:31] certainly [00:26:32] more of a [00:26:33] belief that [00:26:34] more of [00:26:35] these types of [00:26:36] regulations would happen at [00:26:37] the federal level, [00:26:38] and that [00:26:39] obviously [00:26:40] hasn't [00:26:41] happened in [00:26:42] the second Trump [00:26:43] administration, and a [00:26:44] lot of those [00:26:45] initiatives are [00:26:46] getting rolled back, [00:26:47] and [00:26:48] international pledges and [00:26:49] things like that.

[00:26:50] So [00:26:51] I think [00:26:52] [00:26:53] the Argument [00:26:54] against what I just said [00:26:55] [00:26:56] is, if people have been too [00:26:57] focused on [00:26:58] that [00:26:59] and how it was gonna change their [00:27:00] business in the medium [00:27:01] term, that would've [00:27:02] been time and [00:27:03] money [00:27:04] not well spent [00:27:05] because a lot of [00:27:06] those [00:27:07] initiatives didn't [00:27:08] accelerate. In fact, they [00:27:09] were kind of [00:27:10] reversed or sort [00:27:11] of [00:27:12] deprioritized. [00:27:13] so sorry to [00:27:14] talk out of both sides [00:27:15] of my mouth on that one, [00:27:16] but

Edward: No. [00:27:17]

Zach: interesting to [00:27:18] look at [00:27:19] retroactively

Edward: [00:27:20] [00:27:21] 100%, I think it's super [00:27:22] relevant. And I mean, we, [00:27:23] we always hear, [00:27:24] like, the comparisons [00:27:25] between Europe and [00:27:26] the US, [00:27:27] especially conversations [00:27:28] around energy [00:27:29] efficiency and [00:27:30] sustainability [00:27:31] in the built [00:27:32] environment. in Europe, they're [00:27:33] more, [00:27:34] regulation-driven, while in the [00:27:35] US, they're more [00:27:36] investor-driven.

[00:27:37] but political will, [00:27:38] political priorities do [00:27:39] matter ultimately, [00:27:40] in the [00:27:41] US. and when it comes to [00:27:42] local regulations, [00:27:43] like N- New [00:27:44] York being a great [00:27:45] example, but also [00:27:46] across the board, kicking the [00:27:47] can down the road unless [00:27:48] something's super [00:27:49] urgent will always be easier [00:27:50] 'cause there's always [00:27:51] fires to be put out in a [00:27:52] building, in a portfolio.[00:27:53]

But to your [00:27:54] point, Zach, [00:27:55] the operators [00:27:56] that have [00:27:57] framed this, [00:27:58] push towards [00:27:59] more [00:28:00] operationally [00:28:01] efficient, teams, [00:28:02] the ones that have [00:28:03] seen it as an [00:28:04] opportunity instead of a, a [00:28:05] stake, instead of a [00:28:06] punishment, are [00:28:07] now ahead, and [00:28:08] now that they actually [00:28:09] need it because [00:28:10] rents aren't going [00:28:11] up as much as they [00:28:12] used to and they [00:28:13] really have to focus on the [00:28:14] operations, now they're, [00:28:15] they're ahead.

Now [00:28:16] they, can cope with [00:28:17] it much better, than the [00:28:18] competition.

[00:28:19] Jennifer, [00:28:20] last but not least, [00:28:21] collaboration [00:28:22] superpower. If you could [00:28:23] partner with one [00:28:24] person, [00:28:25] historic or living, [00:28:26] real or [00:28:27] fictional, who [00:28:28] would it be?

Jennifer: [00:28:29] Okay, [00:28:30] so [00:28:31] I think what [00:28:32] always interests [00:28:33] me is [00:28:34] building [00:28:35] businesses using [00:28:36] [00:28:37] technology. [00:28:38] So I would [00:28:39] give, a very [00:28:40] well-known [00:28:41] example, [00:28:42] although [00:28:43] most people are gonna [00:28:44] be surprised by [00:28:45] this. I would say [00:28:46] I would pick Walt [00:28:47] Disney. [00:28:48] I think [00:28:49] he [00:28:50] didn't [00:28:51] just think [00:28:52] about technology as the [00:28:53] product. [00:28:54] He used [00:28:55] technology [00:28:56] to [00:28:57] push [00:28:58] boundaries of [00:28:59] animation, sound, [00:29:00] physical [00:29:01] entertainment, [00:29:02] completely changed the [00:29:03] physical e-environment [00:29:04] [00:29:05] experience.

And [00:29:06] to me, [00:29:07] that's [00:29:08] an [00:29:09] example of the best [00:29:10] technology that [00:29:11] disappears into the [00:29:12] experience. [00:29:13] everything just works [00:29:14] better. [00:29:15] you can use that [00:29:16] to make the [00:29:17] environment better [00:29:18] for people who are [00:29:19] running the [00:29:20] experience, [00:29:21] experiencing the [00:29:22] [00:29:23] experience, all behind the [00:29:24] scenes

Edward: Well, [00:29:25] I mean, Walt Disney, [00:29:26] ended up being [00:29:27] a big real estate [00:29:28] guy.

Jennifer: That's [00:29:29] right

Edward: I think in, [00:29:30] in [00:29:31] Orlando, [00:29:32] Disney can write their [00:29:33] own laws,

[00:29:34] [00:29:35] effectively

Jennifer: [00:29:36] exactly, and that's why m- [00:29:37] most people [00:29:38] don't [00:29:39] associate Disney [00:29:40] as a [00:29:41] real estate mogul, [00:29:42] They associate with the [00:29:43] films or the [00:29:44] characters. the [00:29:45] business and the [00:29:46] technology in the background [00:29:47] is [00:29:48] phenomenal

Edward: who would've thought Mickey [00:29:49] Mouse, make sure [00:29:50] you pay your rent on [00:29:51] time. [00:29:52] Zach, [00:29:53] who's your collaboration [00:29:54] superpower this [00:29:55] week?

Zach: I usually [00:29:56] go thematic, [00:29:57] but, [00:29:58] this time I'm just gonna [00:29:59] take it back to tennis 'cause [00:30:00] I've, I've been watching the [00:30:01] Laver Cup [00:30:02] a lot, [00:30:03] which, for those [00:30:04] of you who don't know, it's kind of [00:30:05] tennis's answer to [00:30:06] golf's Ryder [00:30:07] Cup. It's a [00:30:08] bunch of top [00:30:09] players from Europe [00:30:10] against a bunch of top [00:30:11] players from the rest of the [00:30:12] world, team [00:30:13] competition [00:30:14] created by [00:30:15] Roger Federer, [00:30:16] different location [00:30:17] every year, [00:30:18] named after [00:30:19] tennis great Rod [00:30:20] Laver. the [00:30:21] teams have [00:30:22] captains, and the [00:30:23] captain of Team Europe [00:30:24] is Yannick [00:30:25] Noah, [00:30:26] who is a [00:30:27] legendary, tennis [00:30:28] player, has [00:30:29] a really [00:30:30] fascinating story. [00:30:31] Family came [00:30:32] from Cameroon, moved [00:30:33] to France. [00:30:34] won the French [00:30:35] Open, in the [00:30:36] early '80s, became [00:30:37] a national [00:30:38] star. [00:30:39] then he became [00:30:40] a, [00:30:41] reggae [00:30:42] sensation. so [00:30:43] he's both [00:30:44] skilled in, [00:30:45] tennis and [00:30:46] music. his [00:30:47] son, [00:30:48] Joakim, played in the [00:30:49] NBA for many [00:30:50] years, so [00:30:51] clearly a great dad [00:30:52] also. [00:30:53] But I heard an [00:30:54] interview with their vice [00:30:55] captain, Tim [00:30:56] Henman, [00:30:57] last night talking about [00:30:58] working with Yannick [00:30:59] Noah, and he said he just [00:31:00] has this, [00:31:01] very [00:31:02] calm, [00:31:03] spiritual [00:31:04] confidence about [00:31:05] him and really [00:31:06] high [00:31:07] EQ, and he's able [00:31:08] to [00:31:09] communicate really, really well [00:31:10] with the players, and he [00:31:11] knows sort of [00:31:12] what to say to them at [00:31:13] the right time [00:31:14] and [00:31:15] when is too much, [00:31:16] when is too [00:31:17] much too much, and [00:31:18] when is too [00:31:19] little too little. [00:31:20] so I'm gonna go this time [00:31:21] with, Yannick [00:31:22] Noah. I just [00:31:23] think it'd be [00:31:24] amazing to work with [00:31:25] him [00:31:26] on pretty much [00:31:27] anything

Edward: [00:31:28] Tremendous. [00:31:29] Never disappoints.

Zach: [00:31:30] maybe we just [00:31:31] do like a [00:31:32] tennis [00:31:33] themed [00:31:34] reggae, mixtape together [00:31:35] to start off before [00:31:36] we like jump [00:31:37] into starting a whole [00:31:38] business.

Edward: yeah. [00:31:39] yeah. that seems like [00:31:40] a good way to ease [00:31:41] into a relationship

[00:31:42] What do you think, [00:31:43] Jennifer?

Jennifer: [00:31:44] Love it. I have a lot of tennis [00:31:45] research to [00:31:46] do. reggae and [00:31:47] tennis.

Edward: [00:31:48] Reggae tennis star. [00:31:49] Jennifer, where [00:31:50] can Tangent [00:31:51] listeners and [00:31:52] commercial real estate [00:31:53] owners and operators [00:31:54] learn more about [00:31:55] R0 [00:31:56] and connect with [00:31:57] you?

Jennifer: You can find us [00:31:58] at R0. [00:31:59] I'm [00:32:00] also on [00:32:01] LinkedIn. If you're an owner [00:32:02] and operator, I'd [00:32:03] really encourage you to [00:32:04] look at your own [00:32:05] building, [00:32:06] ask how much of your [00:32:07] operations are [00:32:08] based on what's [00:32:09] actually happening in the [00:32:10] building right now [00:32:11] versus schedules, [00:32:12] assumptions that were [00:32:13] established [00:32:14] years, decades [00:32:15] ago.

That's [00:32:16] usually where the conversation [00:32:17] gets interesting, [00:32:18] and I'd love to have it with [00:32:19] you

Edward: [00:32:20] Jennifer, Zach, [00:32:21] thank you so much [00:32:22] for coming to Tangent [00:32:23] today[00:32:24]

Jennifer: Thanks for having us

Edward: [00:32:25] [00:32:26] [00:32:27] [00:32:28] [00:32:29] [00:32:30] Muchas [00:32:31] gracias. If you learn [00:32:32] something new or [00:32:33] enjoy the [00:32:34] conversation. Text a friend [00:32:35] the link to this [00:32:36] episode right now.

[00:32:37] [00:32:38] You can find [00:32:39] links, [00:32:40] resources, and ways to connect [00:32:41] with us in the show [00:32:42] notes [00:32:43] [00:32:44] [00:32:45]