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How autonomous BVLOS drones and physical AI are transforming grid reliability with Trevor Perrott · Factor This

• 0:06
  SPEAKER_00: Whether we're talking about shifting from reactive to proactive wildfire mitigation or accelerating storm response or maintaining thousands of miles of aging transmission lines, utility teams of all types and sizes are being tasked with much more than operational efficiency.
• 0:21
  SPEAKER_00: To keep up, monitoring and maintaining grid assets require using tools that deliver speed, safety, and scale.
• 0:28
  SPEAKER_00: But many teams are still constrained by traditional field inspection methods that are slow, expensive, or visually limited.
• 0:36
  SPEAKER_00: Trevor Parrott, CEO and co-founder of Census Technologies, is working to change that paradigm through autonomous grid monitoring.
• 0:43
  SPEAKER_00: Census has pioneered long-range, beyond visual line of sight drone platforms, and data solutions that gives utilities a clearer, safer, and faster view of their field assets across massive service territories.
• 0:55
  SPEAKER_00: But what does it take to utilize drones in ways that create tangible value?
• 0:58
  SPEAKER_00: And how can utilities effectively pilot and scale these capabilities?
• 1:02
  SPEAKER_00: We're going to get the answers to those questions and much more.
• 1:05
  SPEAKER_00: So, Trevor, thanks so much for taking the time to connect.
• 1:08
  SPEAKER_01: Pleasure to be here, Jeremiah.
• 1:10
  SPEAKER_00: So I gave a brief primer.
• 1:12
  SPEAKER_00: We're going to get into all things drones and utilities, but maybe you could give us a little background about yourself and about census technologies and at a broad level.
• 1:20
  SPEAKER_00: Can you tell us how you tailor your aerial solutions specifically for the utility sector?
• 1:27
  SPEAKER_02: Sure.
• 1:27
  SPEAKER_02: So uh like you said, I'm Trevor Perry, Kafan, our CEO at CENTIS, where we focus on germ-enabled asset intelligence uh first with electric utilities, and then we're expanding to other markets down the wind of that.
• 1:42
  SPEAKER_02: But you know, we'll probably spend most of our time talking about what we're doing today.
• 1:47
  SPEAKER_02: Um, so my background uh spans airspace engineering, unmanned systems, and just generally scaling tech business, um, particularly in the industries that are heavily regulated, like aerospace.
• 2:02
  SPEAKER_02: Um and then, you know, for the utilities today, we're helping them really solve two problems simultaneously.
• 2:11
  SPEAKER_02: How do you collect, you know, data at a continental scale uh at resolution that's high enough to matter?
• 2:19
  SPEAKER_02: And then naturally that's going to create a big data problem.
• 2:23
  SPEAKER_02: So how do you deal with the the big data on the back end of that?
• 2:27
  SPEAKER_02: And really we're solving both sides of that, how to handle the collection and how to handle the big data it produces.
• 2:34
  SPEAKER_02: Um, you know, generally speaking, we uh you know are trying to tailor everything we do into enterprise workflows, so you know it's really more of uh you know enabling an action, enabling risk mitigation so that the friction from data collection to a solved problem is as low as possible.
• 2:57
  SPEAKER_02: Um, you know, our claim to fame is uh, you know, right now we're operating under a uh 107 and a 44807 ecosystem that lets the drones fly about 100 miles at a time from where they took off.
• 3:13
  SPEAKER_02: And uh doing that today is really you know what's enabling a lot of the value crop to take shape.
• 3:21
  SPEAKER_00: You you mentioned the the different industries that you're working in, and obviously we're gonna we're gonna focus on the utility space, but I I covered drones in a variety of sectors for for many years, whether that was construction or public safety or agriculture.
• 3:36
  SPEAKER_00: And one of the things that always stuck out to me is that it was a challenge to get some teams or even industries to get out of the way we've always done it.
• 3:45
  SPEAKER_00: And I mean that's just that's just a challenge with getting people to do different things.
• 3:49
  SPEAKER_00: But in the utility space, I think it's it's different because there's a recognition that there are these tools that can create these efficiencies that need to be adopted because the demand is is real in this space.
• 4:00
  SPEAKER_00: The way we've always done it isn't isn't gonna work in a way that I think resonates and people understand in this space and in a way that they don't in others.
• 4:09
  SPEAKER_00: And I was just curious if you've if you've seen that yourself and what kind of a practical difference that can make as you talk with different teams about adopting and using and scaling this technology.
• 4:21
  SPEAKER_02: Yeah, I think a little bit of that in the electric utility space.
• 4:26
  SPEAKER_02: Um prior to 2018, there was really an attitude of ignorance is bliss in a lot of ways, meaning that um, you know, if we don't know that the problem is there, can we be held accountable for the existence of the problem?
• 4:42
  SPEAKER_02: The classic if the tree falls in the woods question.
• 4:46
  SPEAKER_02: Um and in 2018, um, you know, the major wildfire set in California, the campfire up in Northern California that did tens of billions in damage, really turned the paradigm in a couple ways.
• 5:01
  SPEAKER_02: First of all, not just those utilities, but the industry on whole uh pretty well became ineligible to buy wildfire insurance, at least at a coverage rate that's relevant.
• 5:14
  SPEAKER_02: You know, they they may be able to buy a couple points of risk mitigation, but nowhere near the uh you know the entirety of the loss that it would cause.
• 5:23
  SPEAKER_02: And the the second is that there was a legal change in that um the legal system came down with it, doesn't matter if you knew it or not, you're still accountable for the assets that you control.
• 5:38
  SPEAKER_02: Uh so when they ignite these, you know, multi-billion dollar fires, um, you know, they're on the hook where they know about it or not.
• 5:47
  SPEAKER_02: So, in the absence of being able to actually buy insurance, what is your next best thing?
• 5:53
  SPEAKER_02: And we call that asset omniscience, being able to know everything relevant whenever you want to know it.
• 6:00
  SPEAKER_02: Um and in look, like I was saying, in lieu of insurance, being aware of your assets is kind of the next best thing.
• 6:08
  SPEAKER_02: So um, yeah, there's definitely been a time where it was ignorance as bliss, and that that has changed to ignorance is not a valid answer.
• 6:19
  SPEAKER_00: Well, I mean, it it speaks to the the changing expectations across the board.
• 6:24
  SPEAKER_00: And you know, one of the things I wanted to ask you was around how you're helping utility teams quantify the value and ROI that's associated with these tools, but that assent omniscience that that really speaks to it.
• 6:38
  SPEAKER_00: Um, but but ultimately, is it more about direct labor savings or about how a utility can avoid the the liability that you just mentioned, or about reducing outage duration, or or maybe all of those?
• 6:52
  SPEAKER_02: Yeah, I think I think it is and all of them.
• 6:55
  SPEAKER_02: Um so it really depends on what utility you're talking to in terms of um, you know, which one is of highest priority.
• 7:03
  SPEAKER_02: But um, you know, wildfire mitigation is typically uh twofold.
• 7:08
  SPEAKER_02: You know, show me all the ignition opportunities and then describe what the fuel scape is like in the vicinity of that ignition point.
• 7:16
  SPEAKER_02: So it's a really uh two-sided problem.
• 7:20
  SPEAKER_02: Um in general, there's a coupling between uh vegetation management and severe weather.
• 7:27
  SPEAKER_02: So whenever vegetation becomes overgrown and encroaching on the power lines and then severe storms come along, the likelihood of not just now, but a long one, uh goes way up.
• 7:42
  SPEAKER_02: So um, you know, part of it is uh, you know, one half of the coin is protecting the customer experience and the revenue coming from the customer, and then the other half of it is um, you know, candling just not torching everything in the vicinity of the asset.
• 8:01
  SPEAKER_02: So it's uh opportunity seizure and risk mitigation in one solution.
• 8:09
  SPEAKER_00: Well, and as you said, I know it's always gonna vary depending on the utility, depending on the location, depending on the assets, but at a at a high level for the kind of long linear transmission and distribution corridors that we're talking about, how do fixed wing uh or VTOL platforms compare to a traditional uh helicopter or other inspection methods when you're talking about evaluating range, wind tolerance, and uh payload capacity?
• 8:38
  SPEAKER_02: Yeah, so yeah, the U.S.
• 8:40
  SPEAKER_02: power grid is about 7 million miles in length.
• 8:44
  SPEAKER_02: So it is a uh a very large asset on home.
• 8:48
  SPEAKER_02: Um but only about half a million of that is transmission.
• 8:52
  SPEAKER_02: So the other six and a half, the distribution network, is really where the asset intelligence is is hard.
• 9:00
  SPEAKER_02: Um, so you know, in some ways a helicopter can serve transmission corridors pretty well, but um, you know, when it gets down to you need three branch level fidelity, you know, over a distribution network, that that's where drones really start to uh you know take the cake bar nine.
• 9:20
  SPEAKER_02: Um so that can look like you honestly scan the entire metro, you know, and then you're not just getting the power lines, you're getting everything in that field of view.
• 9:33
  SPEAKER_02: And uh that's a really good context for things like storm response.
• 9:38
  SPEAKER_02: Um so the distribution lines is where handling most of the problems and therefore most of the value resigned.
• 9:47
  SPEAKER_02: And that's why we've been working on things like how do you make fixed link drones applicable for metropolitan areas for suburban areas, um, because that's where the uh the ROI really you know punches out favorably.
• 10:03
  SPEAKER_00: Yeah, and then there's a there's a technical piece to that and a business piece to that, but then also the the regulatory piece to that.
• 10:10
  SPEAKER_00: And you touched on on part 107 earlier, and we can, I mean, regulation is is one of the bigger topics uh across the the drone space.
• 10:18
  SPEAKER_00: So I don't want to go all the way down the rabbit hole, but at the at the same time, maybe you could talk about how you're helping utility teams navigate FAA rules or secure waivers and build out a beyond visual on a site BVLOS framework.
• 10:32
  SPEAKER_00: Um these regulations are are literally evolving uh and right in front of us.
• 10:37
  SPEAKER_02: Yeah, so it took us a decade to build it.
• 10:41
  SPEAKER_02: Um, but but what we eventually got to was a um you know platform reliability history and a SOP standard operating procedure workflow that uh the MPA is comfortable with us um you know almost using as a cookie cutter from one utility to another so that their programs can kind of near one another and um you know operate from the same playbook, if you will.
• 11:09
  SPEAKER_02: And uh that that common standard is really what um you know I think gives us credibility as a as a company for you know just helping repeat what's already been done.
• 11:23
  SPEAKER_02: Now that uh you know sounds great and all, but don't don't overlook the 10 years that it took to get from from A to B with that.
• 11:33
  SPEAKER_02: So the relatory environment that's coming is going to be uh a fun chapter, I think, whenever you know you're really entertaining very high uh drone to human ratios, you know, is where the throws can come from.
• 11:50
  SPEAKER_02: Uh really getting out of a paradigm of drone pilots and into automation managers, you know, I think is a very interesting paradigm uh coming down our way.
• 12:02
  SPEAKER_02: So, you know, no longer we quote flying the drone.
• 12:07
  SPEAKER_02: Um, you know, we are um again just managing a robotic fleet.
• 12:15
  SPEAKER_00: Well, and that that 10 years of of context, I think, is key that you're able to provide your clients because one of the pieces of feedback I would always hear or see was around, oh, we'll wait until regulation evens out or changes.
• 12:29
  SPEAKER_00: And I mean, first of all, that's I mean, who knows when that's gonna happen or even what that means, but there's efficiencies you can take advantage of today and platforms like like yours or experience like that, like you can put that to work in a way that you also can't snap your fingers and just make that happen when they're when we do get part 108, which is I mean, essentially what what's gonna come after part uh part 107.
• 12:53
  SPEAKER_00: Um, you know, you touched on the the what it means to capture data at a level that is gonna be useful, but then also the inherent challenges that come with so much data that that teams don't know what to do with it or data gets into the silos.
• 13:10
  SPEAKER_00: Can you can you talk a little bit about how you're able to leverage the power of this data, which out without falling into data paralysis?
• 13:19
  SPEAKER_02: So I'll use the uh wildfire mitigation example to answer that.
• 13:25
  SPEAKER_02: So again, zooming out the highest level, there are 1,100 power line ignited wildfires in the US every year over a 7 million mile span.
• 13:37
  SPEAKER_02: So you have 1,100 needles inside of the 7 million mile haystack.
• 13:43
  SPEAKER_02: So the task becomes how do you find them, right?
• 13:47
  SPEAKER_02: And uh really this is where physical AI is really helping solve the big data problem.
• 13:54
  SPEAKER_02: So, you know, at this point, everybody's used to playing around with anthropic chat GVT and every you know flavor of ice cream like it from an LLM point of view, but really a uh oncoming AI frontier is doing it, you know, in the physical domain.
• 14:12
  SPEAKER_02: And you're seeing it with uh you know AI generated videos that hit your Instagram feed and and so on, you know, though those are early things, but actually applying it to you know real domain assets like paralyzed.
• 14:28
  SPEAKER_02: And in that, what we're doing is we are you know taking uh you know 7 million miles of data would be like eight petabytes.
• 14:38
  SPEAKER_02: You know, it's a a huge data volume, and boiling that down to show me a map of the 1100 points I need to worry about.
• 14:47
  SPEAKER_02: And when you take it from eight petabytes down to 1100 points on a map, it's suddenly a lot more ingestible and actionable.
• 14:57
  SPEAKER_02: Um, so really using physical AI to move us from looking at pictures to looking at indications on maps.
• 15:07
  SPEAKER_02: Now, that's an oversimplification of you know, you've got to have a lot of good training data on what's it what's encroachment mean, and um getting comfortable enough with, hey, this is gonna be an 80% solution this year, it'll be a 90% solution next year, it'll be a 95% solution, and it very well may take 10 years to get to 100.
• 15:35
  SPEAKER_02: Um, so it's just kind of uh, you know, having an acceptance of here's the the stat, which is leaves and bounds ahead of what we've been doing, and then there's a maturation curve uh toward perfection, and getting comfortable with the we're not perfect today is an important part of the mining set.
• 15:57
  SPEAKER_00: But I mean, those are the specifics that can create that kind of tangible value that ultimately is what everybody wants and and needs to see.
• 16:06
  SPEAKER_00: And I don't know if how how you've seen it, but I think a lot of teams look to provide a baseline for that or enable that as a pilot program or as something small, but then being able to scale that into something bigger or across the enterprise, there's just there's inherent challenges with that.
• 16:23
  SPEAKER_00: Um, can you talk about any insights that you've you've had when it comes to what it means to transition a pilot to uh scale or just how to approach taking these taking these this value that you can create as a as a pilot beyond that?
• 16:43
  SPEAKER_02: I think it's just being crystal clear with you know, this is what the pilot is going to deliver, and this is how it's gonna scale thereafter.
• 16:53
  SPEAKER_02: I I think a lot of times, you know, not just run companies, but businesses on the whole will get in a lot of trouble when they oversell what a pilot will produce.
• 17:03
  SPEAKER_02: The kind of truth is there's absolutely an economy of scale.
• 17:08
  SPEAKER_02: And um, you know, if you want stellar ROI, you've got to be able to say, hey, the quarter million miles that I control, I'm gonna go for all of it.
• 17:19
  SPEAKER_02: You know, whenever you're trying to uh, you know, you own a quarter million miles and you say, show me the ROI on these 10, you know, it's tough whenever you tell you up just the deployment costs to go out and look at the tent.
• 17:35
  SPEAKER_02: So there's absolutely a scale-related inflection point that um, you know, I think a lot of times um folks see the potential, but they're bound by a budget that's almost too small to kind of unlock what the returns would be.
• 17:52
  SPEAKER_02: Unfortunately, we're getting into a chapter where enough utilities have taken enough early risk that the ROI is demonstrable, and thus those first followers get a lower level of of risk uh in terms of uh is the technology mature?
• 18:11
  SPEAKER_02: Is the ROI math really sound?
• 18:15
  SPEAKER_02: So on.
• 18:16
  SPEAKER_00: Yeah, and those operational realities, budget limitations, I mean that connects into as well whether uh a utility or how a utility can weigh their options when it comes to utilizing a service provider versus building and maintaining their own their own fleet, that that eternal question of of buy buy outsource versus build.
• 18:38
  SPEAKER_00: I mean, ultimately, there's no there's no one answer to that.
• 18:42
  SPEAKER_00: I mean, it all again it depends on what what somebody's trying to do.
• 18:46
  SPEAKER_00: But what's what's your advice or what have you been able to see when it comes to asking better questions as that kind of buy versus build issue comes up for teams as they look to leverage and use this technology?
• 19:00
  SPEAKER_02: I think a lot of it has to do with um get getting the utility through the you know, a lot of times they'll say we we need extreme control, you know, is like kind of a default position.
• 19:14
  SPEAKER_02: And uh I respect that.
• 19:16
  SPEAKER_02: And to be honest with you, I like to have control over things as well.
• 19:20
  SPEAKER_02: But there's uh a little bit of a missing fallacy in that, which is that um, you know, you're gonna have control over the uh the technology that can do it, but you also gotta go a step further and build all the infrastructure around it to employ its outputs.
• 19:38
  SPEAKER_02: And that's where I think a lot of uh a lot of folks are putting the cart before the horse in some ways, uh, meaning that uh you know the thought is, oh, I need the drone to collect, and it's no, not really.
• 19:55
  SPEAKER_02: You need a a program to collect, convert to intelligence and act on this.
• 20:03
  SPEAKER_02: And um, you know, I I've seen I'd say remarkably few of the um utilities have been able to execute all three of those components concurrently, you know, 10 tens a given sequence.
• 20:20
  SPEAKER_02: And I think the the time to the ROI realization is actually a lot shorter if you're investing in in those ideas concurrently.
• 20:31
  SPEAKER_02: So um, you know, I think it's a long-winded way to say that um looking at it very much from uh uh enterprise programmatic point of view is going to succeed a lot more than looking at it from a purely uh aviation, I gotta fly something point of view.
• 20:53
  SPEAKER_00: Well, and some of that connects, I mean we we've already talked about the the impact that the technology is making in wildfire mitigation, but I mean the impact it it's making is profound in some ways because I think it's it's tools and technology that that rather than reactive maintenance, it enables predictive operations.
• 21:13
  SPEAKER_00: Um can you talk a little bit about that that shift in in mindset, both what that enables just from an operational level, but then also just as a utility being able to provide a different type of service and being able to protect these assets in a different way?
• 21:32
  SPEAKER_02: Well, you're entirely right, Jeremiah.
• 21:34
  SPEAKER_02: The the unsung hero of what this is enabling is to literally predict the future and do so with a high level of accuracy.
• 21:45
  SPEAKER_02: Um, you know, I think I forget who uh uh the quote ought to be credited to, but the best prediction of the future is the past.
• 21:54
  SPEAKER_02: And I would extrapolate that a little bit to say the uh the trend line is the best.
• 22:00
  SPEAKER_02: You know, estimate of what the future is going to hold.
• 22:03
  SPEAKER_02: Um, so so an example of this is um recently we had a utility customer tell us that because their asset intelligence game is now so elevated, they actually got to defer$200 million of repairs by two years.
• 22:23
  SPEAKER_02: They could actually prove that the degradation they thought was going to happen by now hadn't happened yet.
• 22:30
  SPEAKER_02: Uh and these things are going to need to replace, but two years from now.
• 22:35
  SPEAKER_02: So, you know, being able to reallocate$200 million of capital is you know real money.
• 22:42
  SPEAKER_02: And uh, you know, depending on your organizational structure, if you're an investor in a utility, that's a major impact to the shareholders' point of view.
• 22:53
  SPEAKER_02: Um you know, being able to reallocate that for your employees as well, that that's the kind of stuff that I think is not getting talked about enough, is that there there are gains from just being able to see it all when you want to see it.
• 23:09
  SPEAKER_02: And in this example, it was you know delaying$200 million for repairs.
• 23:17
  SPEAKER_00: Well no, that that concept, if we want to see what's next, we need to look to the past.
• 23:22
  SPEAKER_00: There's there's a ton to that on on how many different levels.
• 23:25
  SPEAKER_00: So, but um and I'll ask, is there, you know, when it comes to what's next, is there a single operational milestone or metric or shift that you're keeping track of that you think is is a real indicator in terms of where things are, where they need to go, or how they're coming together with how drones are being utilized across the energy sector?
• 23:44
  SPEAKER_02: So I can you know comment from Census point of view and then zoom out and just talk macro level uh for a moment.
• 23:53
  SPEAKER_02: So kind of the big paradigm that Census is moving into is moving to uh what we call a node-based network.
• 24:01
  SPEAKER_02: So in that we are parking docks and drones at a node and then trying to cover the map with nodes.
• 24:09
  SPEAKER_02: So one of our nodes serves about a 30-mile radius or 2800 square miles.
• 24:15
  SPEAKER_02: Um so using uh the electric grid as kind of asset class number one to drive where those nodes are getting placed, it is kind of natural that you're going to be able to monetize other revenue streams from within that field of view.
• 24:34
  SPEAKER_02: So, really, these nodes are meant to, you know, they answer questions that you can answer from space, a frequency of on demand.
• 24:44
  SPEAKER_02: And um, you know, that's enabled by being able to operate flight remotely, um, being able to operate multiple drones to one human, uh, and the physical AI of turning enormous quantities of data into a usable dashboard.
• 25:02
  SPEAKER_02: Uh, so all those tech, I think technology convergence is really the uh you know the headline that kind of defines things on whole as well.
• 25:13
  SPEAKER_02: Um, you know, I mentioned earlier the idea of moving from L into physical AI, I think is going to be, you know, progressively more and more important as time goes on.
• 25:27
  SPEAKER_02: Um you know, one of the things that I celebrate, to be honest with you, is a um kind of the uh reallocation of capital from things like the metaverse into things that are real, you know, that we depend on for real to live our life, you know, our power lines of roads, our houses, that kind of thing.
• 25:46
  SPEAKER_02: So uh glad to see that kind of directional change from a um, you know, just a macro point of view.
• 25:54
  SPEAKER_02: And then the other side of it, I think, is geopolitical.
• 25:58
  SPEAKER_02: Um, so it's no secret that America is doing a lot of you know anti-China movement from a policy perspective is the release of drones.
• 26:09
  SPEAKER_02: And I I do empathize and understand the pain that's particularly being felt by uh law enforcement public safety use cases, um, you know, because they were used to a very good product at a very low price.
• 26:26
  SPEAKER_02: Now, the problem with that is that our adversaries have been very good about value manipulation.
• 26:34
  SPEAKER_02: You know, they brought a very good product to our market at a very low price.
• 26:38
  SPEAKER_02: And if it were priced fairly, it'd be many, many thousands of dollars more per unit.
• 26:45
  SPEAKER_02: And suddenly, then you could have Western competition at that price point.
• 26:50
  SPEAKER_02: Um but in the free market ecosystem, we uh can't leave the uh the Western OEMs of comparable platforms, we're not subsidized to the same degree to be able to offer it at the same price.
• 27:06
  SPEAKER_02: So it's just kind of a classic example of um you know supply and demand.
• 27:13
  SPEAKER_02: And whenever you've got an entrant in the market that's so cheap, um, you know, it's really, you know, you need capital to get deployed, and if you can't make a return on it at that price, who will invest and no one?
• 27:27
  SPEAKER_02: And this, I hope, is going to be just a broader, you know, wake up call for the Western world.
• 27:34
  SPEAKER_02: I thought I thought COVID was going to uh ring our bell loud enough, but apparently not.
• 27:40
  SPEAKER_02: On uh you know, we we need solid supply chain that is honestly priced, and we need to buy goods uh and services that are honestly priced.
• 27:54
  SPEAKER_00: Yeah, sometimes those bells need to be rung multiple times or from multiple areas before people people notice.
• 28:01
  SPEAKER_00: Um, you know, all that all that makes sense in terms of in terms of what's next with the with the technology, with the regulation, with the the geopolitical element of it.
• 28:11
  SPEAKER_00: And so much of it, I mean, we got to see what happens, so much of it is beyond any one person or even industry.
• 28:17
  SPEAKER_00: And I think a lot of that uncertainty breeds a sense of like, all right, well, let's let's wait or like let's see how a certain thing shakes out.
• 28:26
  SPEAKER_00: But you know, this this technology, these solutions are creating value today.
• 28:31
  SPEAKER_00: And like, is there anything else you can can say just in terms of the value created today and how that enables that, how a company or a team can be in a better position tomorrow, that like not waiting today, the kind of difference it it makes for them tomorrow when you're starting from something or have a foundation that can be further built out as the technology changes, as a regulatory environment further evolves.
• 28:57
  SPEAKER_02: The hyperbole that I've been using of late is what if you could cancel blades of grass on the continent?
• 29:04
  SPEAKER_02: You know, and uh that that's really the the frame of mind that that I'm trying to keep our team in and honestly invite um you know the rest of our industry to you know drink dream of such a thing.
• 29:20
  SPEAKER_02: And you know, again, cat having blades of grass is a hyperbole, but what if you could um you know see every crack in every road and be able to forecast what that's going to be like over the next 10 years?
• 29:35
  SPEAKER_02: And what if you could do that with vegetation on parallel?
• 29:40
  SPEAKER_02: What if you could do it with uh you know mitigating hurricane insurance fraud, being able to scan metro right before and right after a hurricane, and suddenly you can give the truth to both the consumer and the insurance company.
• 29:55
  SPEAKER_02: Um, you know, these are the kinds of things that are going to uh, no exaggeration, free up trillions of dollars of capital in the economy.
• 30:05
  SPEAKER_02: You know, one one example is that because the utilities cannot buy meaningful wildfire insurance, they have to hold huge sums of cash on their balance sheet in lieu of insurance.
• 30:19
  SPEAKER_02: And make no mistake, the cash came from their customer.
• 30:23
  SPEAKER_02: You know, you want cheaper electricity?
• 30:26
  SPEAKER_02: How about we start with three up the trillion dollars of cash just sitting on the sideline?
• 30:32
  SPEAKER_02: And um so making the power grid insurable again, I think is going to be a symptom of the capability to count the blades of grass on the combat.
• 30:44
  SPEAKER_00: Gosh, that insurance piece is is just so so critical.
• 30:48
  SPEAKER_00: And it's one of those like how how things are are changing in the space or how utilities need to operate, like those sort of market conditions or reality that don't have anything to do with uh the technology or the infrastructure, like it's the the market reality of it that is that needs to impact decisions.
• 31:08
  SPEAKER_00: Um, you know, I'll wrap up with a question that I love to ask industry leaders, which is tell me something powerful.
• 31:13
  SPEAKER_00: You know, is there a piece of advice that anchors you or a critical perspective that you feel the broader sector is missing, or an insight from entirely outside the energy space that's relevant here, which I think you're a good person to ask since you do work across so many different sectors.
• 31:27
  SPEAKER_02: You know, I I think the powerful thing is that um, you know, so I use the word omniscience, right?
• 31:35
  SPEAKER_02: And I'm a big etymology person, so I try and uh you know use the right words at the right time for for what I'm trying to take like.
• 31:44
  SPEAKER_02: And omniscience is one of those things that maybe it cannot be achieved you know, in the classic definition.
• 31:52
  SPEAKER_02: Um but I love the thought exercise of what if it could.
• 31:57
  SPEAKER_02: You know, what what if you could achieve uh omniscience?
• 32:01
  SPEAKER_02: And uh what is what is everything that comes from it?
• 32:05
  SPEAKER_02: Yeah, since the way we frame it is that um asset omniscience is the cornerstone of value creation.
• 32:12
  SPEAKER_02: And what we're saying there is that if you cannot measure your starting condition, uh how are you ever gonna actually know if value increased or decreased?
• 32:24
  SPEAKER_02: And that's where this idea of omniscience comes from.
• 32:28
  SPEAKER_02: Um, you know, whenever you um really back out just everything that it would unlock.
• 32:37
  SPEAKER_02: Right.
• 32:38
  SPEAKER_02: And you know, I've used the wildfire mitigation here with utilities as a big talking point.
• 32:44
  SPEAKER_02: Hurricane insurance fraud is also something that annoys me both personally and professionally, and I'd like to see it go away.
• 32:53
  SPEAKER_02: Um and yeah, I think that the powerful thing is that if you can open your mind to dream of a world that doesn't exist yet, and then throw on the engineering hat to make it happen.
• 33:07
  SPEAKER_02: Um, yeah, that's what I think we need in all corners from capital to the folks that are doing the engineering to make it happen to our our business leadership of if we can sit out and be bold enough to say it can be done, it just might happen.
• 33:25
  SPEAKER_00: Well, you know, there's that old expression of you don't know what you don't know.
• 33:29
  SPEAKER_00: And if you don't have that kind of asset omniscience, that that awareness of what is out there, what the the condition of all those people, then you just don't know it.
• 33:38
  SPEAKER_00: So uh having that knowledge, having that understanding just opens up opportunities that you're not even thinking about because again, you don't know what you don't know.
• 33:49
  SPEAKER_00: That's uh Trevor Parrott, I really appreciate you taking the the time to connect.
• 33:54
  SPEAKER_00: Uh census.com, ton more info there.
• 33:57
  SPEAKER_00: And I know you guys are on all the socials, so uh appreciate the time and looking forward to catching up soon.
• 34:05
  SPEAKER_00: Hi question, I appreciate the opportunity.
• 34:08
  SPEAKER_00: As always, thank you for listening to the factor this podcast.
• 34:13
  SPEAKER_00: Please do like and subscribe wherever you find your favorite podcast.
• 34:17
  SPEAKER_00: Let us know how we're doing.
• 34:18
  SPEAKER_00: You can find me on LinkedIn.
• 34:20
  SPEAKER_00: I'm Jeremiah Kerpelwit, and always looking forward to hearing your feedback.
• 34:24
  SPEAKER_00: Tell us what we can do better with the show, or if you have an idea for an episode, please get in touch, stay in touch.