Trascrizione completa di Utilities Have More Data Than Ever. Now What?

you for having me this morning. 28 00:01:45.511 --> 00:01:49.992 So yeah, Jason Klein, Vice President of Electric Operations for Amer, Illinois. 29 00:01:50.513 --> 00:01:54.654 I've been here for just over 30 years, so got a bit of experience. 30 00:01:55.214 --> 00:01:57.376 And, you know, really, why do I do it? 31 00:01:57.737 --> 00:02:00.519 Because it's really about power and equality of lives for our customers. 32 00:02:00.539 --> 00:02:03.042 So we serve 1.2 billion customers in Illinois. 33 00:02:03.862 --> 00:02:10.529 And without the energy for them to be able to do their tasks on a day-in and day-out basis, life would be extremely challenging. 34 00:02:10.589 --> 00:02:14.813 So, you know, it's really having a good quality of life for all of our customers. 35 00:02:14.953 --> 00:02:15.373 Terrific. 36 00:02:15.493 --> 00:02:15.994 I love that. 37 00:02:16.474 --> 00:02:21.878 And then Christina, you know, our regular listeners will recognize you, but why don't you give us the rundown of your background again, too? 38 00:02:21.918 --> 00:02:22.418 Thanks, Matt. 39 00:02:22.778 --> 00:02:24.119 My name is Christina Park. 40 00:02:24.139 --> 00:02:26.441 I lead energy and utilities at Skydio. 41 00:02:26.521 --> 00:02:30.584 Skydio is a drone manufacturing company, actually, here in the U.S. 42 00:02:30.844 --> 00:02:38.870 But interestingly, I got to Skydio because I was once a utility customer of Skydio, and I was in asset management at the New York Power Authority. 43 00:02:39.630 --> 00:02:40.530 for 15 years. 44 00:02:40.730 --> 00:02:58.616 And so why I do what I do is actually I tell people my job actually didn't change all that much from when I was at the utility to where I am now, because I really want to see utilities move forward and get more efficient and really connect the way that we do our operations and maintenance with the outputs and outcomes that are desired. 45 00:02:58.856 --> 00:03:02.837 And I just feel like in my 15 years at NYPA, 46 00:03:03.798 --> 00:03:06.661 I saw a lot of evolution, but frankly, not enough. 47 00:03:06.962 --> 00:03:16.795 And across the industry, I feel like we could really move the utility industry forward to make a bigger impact if we were willing to embrace technology and figure out how to operationalize it. 48 00:03:17.045 --> 00:03:17.405 Excellent. 49 00:03:17.425 --> 00:03:24.689 Yeah, so we've got some heavy hitters here, some great background, and you've all mentioned kind of the key words, which are asset management. 50 00:03:24.729 --> 00:03:29.672 So I want to get a survey of the landscape of asset management today. 51 00:03:30.272 --> 00:03:33.034 What is changing most quickly in this current environment? 52 00:03:33.114 --> 00:03:39.297 Is it aging assets, storm intensity, workforce turnover, cost pressure, customer expectations? 53 00:03:39.317 --> 00:03:43.960 Tell us more about the changing tide in asset management and how the role feels different 54 00:03:44.300 --> 00:03:46.203 today compared with even a few years ago? 55 00:03:46.223 --> 00:03:48.627 And I'll stay with you, Christina, to kick this one off. 56 00:03:48.767 --> 00:03:54.956 I think that what's most interesting is there are a lot of different factors that cause a case for change. 57 00:03:55.657 --> 00:03:58.882 And I think asset management is just becoming more and more critical because 58 00:03:59.302 --> 00:04:00.163 times are changing. 59 00:04:00.784 --> 00:04:09.071 So I think a lot of the factors that you've talked about, Matt, whether it's aging infrastructure or the aging workforce or all of the above, climate change is another one. 60 00:04:09.111 --> 00:04:12.655 We're seeing a rise in storms and fires just depending on where your territory is. 61 00:04:13.516 --> 00:04:17.199 But I think the case for change really comes from the fact that these are all happening at the same time now. 62 00:04:17.860 --> 00:04:20.062 And I think it becomes more and more difficult to ignore. 63 00:04:20.482 --> 00:04:41.293 Yeah, I would agree with Kirstina that, you know, really, I think a lot of around why asset management has become a more important cost pressure, customer affordability, and again, the combination of more storms and more intense storms, along with aging assets, you know, really just highlights the opportunity and the need for asset management. 64 00:04:41.393 --> 00:04:42.513 How do you look at your assets? 65 00:04:42.533 --> 00:04:47.496 How do you look at, you know, the risk associated with aging assets and how that impacts? 66 00:04:47.916 --> 00:04:48.937 operations going forward. 67 00:04:49.077 --> 00:04:49.477 Yeah. 68 00:04:49.797 --> 00:04:59.483 And I guess, Matt, all of the above, everything you mentioned, and what Jason and Cristina mentioned, I remember when I first joined my career, I was always reminded about the 1973 oil embargo. 69 00:04:59.703 --> 00:05:01.504 It was the impact on the utility system then. 70 00:05:01.937 --> 00:05:05.179 Right now we're going through a major escalation in the Middle East. 71 00:05:05.280 --> 00:05:07.901 And part of it is how will you treat you under business? 72 00:05:07.921 --> 00:05:09.202 Where do we get Transformers from? 73 00:05:09.242 --> 00:05:11.284 So I think this is the best time to be in that business. 74 00:05:11.864 --> 00:05:14.927 And from your perspective, we're going to go, I guess, in depth in a few minutes. 75 00:05:14.967 --> 00:05:19.550 But the biggest issue right now is that we cannot really afford to lose an asset. 76 00:05:19.610 --> 00:05:20.831 I would put it that way. 77 00:05:21.311 --> 00:05:26.135 The traditional way of, you know, consumer failure, ordering your transformer, installing the transformer life moves on. 78 00:05:26.655 --> 00:05:28.917 That is not really the norm that we live in right now. 79 00:05:28.957 --> 00:05:30.198 So you have to be very, very careful. 80 00:05:30.698 --> 00:05:38.547 And at the same time, this is the best

time to utilize all the software, hardware, AI, and all other tools we have to prolong the life of all our assets. 81 00:05:38.887 --> 00:05:42.711 Yeah, you mentioned that, you know, really not being able to lose any assets. 82 00:05:42.851 --> 00:05:47.116 Does that status kind of shift the balance of how utilities are treating assets? 83 00:05:47.476 --> 00:05:50.279 reactive work versus proactive work in asset management? 84 00:05:50.639 --> 00:05:51.620 It's a good question. 85 00:05:51.660 --> 00:05:55.903 Just imagine, as you know, almost every utility have different styles of transformer. 86 00:05:55.924 --> 00:05:58.125 You used to wait a year, year and a half for your order. 87 00:05:58.606 --> 00:06:01.728 Now you have to wait double that time, and you're competing with data centers. 88 00:06:01.748 --> 00:06:04.831 You're competing with people willing to pay more to get the same assets. 89 00:06:04.851 --> 00:06:11.577 So I think from our perspective, it's almost like having a very old car, and you want to prolong the life of the car another 10, 20 years. 90 00:06:12.117 --> 00:06:14.639 So the maintenance that is required is different. 91 00:06:15.240 --> 00:06:29.651 As you mentioned, yeah, I think we have to be a lot more proactive, whether it's drones, it's GGOA, whatever we can, and pretty much all hands on deck and all the tools are, I guess, allowed to be used and expected to be used from a customer perspective, customer affordability. 92 00:06:30.712 --> 00:06:35.356 And I focus on Transformer, but pretty much it's every equipment that we talk about right now. 93 00:06:35.736 --> 00:06:37.838 And as Christina mentioned, we're doing all the stuff 94 00:06:38.458 --> 00:06:40.580 why we keep getting hammered by Mother Nature. 95 00:06:41.761 --> 00:06:44.423 So that's kind of it's a very hard equation to, I would say, to solve. 96 00:06:44.763 --> 00:06:52.389 But between the aging infrastructure, the Mother Nature is basically striking us left and right and customer demand growing up at the same time. 97 00:06:52.449 --> 00:06:55.452 Yeah, I think, Matt, I just chime in, you know, thinking about thinking about 98 00:06:55.852 --> 00:07:03.253 Lion assets, for example, you know, I think it's really a balance between reactive, proactive and reactive investment. 99 00:07:03.293 --> 00:07:15.456 So, you know, from a from a storm hardening perspective, for example, we're putting in composite poles that, you know, depending on the area within Illinois, you know, wood poles, high winds. 100 00:07:15.496 --> 00:07:22.537 You have those cascading events where composite poles can withstand that and stop the cascading event, which that's a good thing. 101 00:07:23.597 --> 00:07:26.818 You know, so from a proactive standpoint, we're working on that. 102 00:07:26.958 --> 00:07:30.119 But then, you know, there are going to be times where an outage does occur. 103 00:07:30.619 --> 00:07:33.800 So then how do you minimize that outage as best you can? 104 00:07:33.880 --> 00:07:37.701 Well, we're doing that with, you know, a lot of distribution and automation. 105 00:07:37.821 --> 00:07:48.043 So, again, trying to switch around whatever the impacted area is to restore as many customers as we can, you know, as quickly and efficiently and as safely as we can. 106 00:07:48.322 --> 00:07:55.426 Yeah, and I think from my perspective, having worked at one utility and then now working with many, I see that a lot of the problems are the same. 107 00:07:55.866 --> 00:08:12.715 And when we talk about how fast we can respond, whether it's in the storm response or some sort of emergency scenario, what I'm seeing across the board is that it comes back to your asset management strategy and what the condition of your assets were at the time that something happened, right? 108 00:08:12.755 --> 00:08:16.097 Whether it is a storm or a car hit a pole or... 109 00:08:16.997 --> 00:08:18.919 A squirrel kind of appeared out of nowhere. 110 00:08:20.019 --> 00:08:22.421 You can't control everything that happens to your grid. 111 00:08:23.121 --> 00:08:29.385 But at the same time, what I'm seeing is that there's a gap in the understanding, like an accurate understanding of your asset health. 112 00:08:29.405 --> 00:08:39.652 Whether your assets are poles, as Jason was saying, or transformers, as Ahmed was saying, or any of the millions of others that exist, having the confidence of knowing... 113 00:08:40.212 --> 00:08:48.099 the health of each of those assets in order to prioritize your maintenance plans in preparation for the unknown that could happen. 114 00:08:48.199 --> 00:08:51.621 And I think that is kind of the key of asset management these days. 115 00:08:52.142 --> 00:08:53.023 Yeah, it makes sense. 116 00:08:53.063 --> 00:08:57.166 There's limited time, there's limited budget, and it seems like everything needs attention. 117 00:08:57.206 --> 00:09:03.131 So how do you look at that health and decide where you're going to triage and put your attention first? 118 00:09:03.495 --> 00:09:04.375 I can start. 119 00:09:04.455 --> 00:09:08.017 So I think it's very important that we classify the substation by type. 120 00:09:08.037 --> 00:09:11.638 You got a switch gear and a power plant, a transmission, switching station. 121 00:09:12.319 --> 00:09:20.122 So I think initially, you know, of course, all the customers are very critical, but not every substation has the same, I would say, criticality as the other one. 122 00:09:20.182 --> 00:09:22.022 So that's the power of asset management. 123 00:09:22.142 --> 00:09:24.023 That's number one of kind of classifying the stations. 124 00:09:24.543 --> 00:09:26.424 And then I guess follow up to what Christina mentioned. 125 00:09:26.444 --> 00:09:30.846 I mean, if you're maybe doing one more analogy for the car back in the days, you were very lucky. 126 00:09:31.300 --> 00:09:32.661 if you get a check engine light on. 127 00:09:33.201 --> 00:09:34.803 Now the

car just tells you too much. 128 00:09:34.843 --> 00:09:35.904 It's like kind of almost entering. 129 00:09:36.344 --> 00:09:39.186 So we want to get, so I call it like the substation facts. 130 00:09:39.226 --> 00:09:46.211 So just imagine if you could very, very quickly get like a full record or full report of every station, very similar to your car. 131 00:09:46.231 --> 00:09:49.394 Like, you know, if you go to a Carfax, you know, every little detail about the car. 132 00:09:49.994 --> 00:09:58.567 And right now utilities, you know, from a safety perspective, they got all the gadgets inside the car to know how the driver is driving, you know, how he or she breaks, and all the stuff. 133 00:09:58.647 --> 00:10:00.430 So that's really, I think, is the importance. 134 00:10:00.450 --> 00:10:03.635 Like once we have implemented the data, but as I mentioned a few minutes ago, 135 00:10:04.317 --> 00:10:06.057 You need hardware as well. 136 00:10:06.117 --> 00:10:12.879 It comes to substation software as one aspect, but unless you install the hardware, and that also goes to the long-term vision from Asset Management. 137 00:10:12.919 --> 00:10:20.100 If you are installing a transformer now with the expectation that the life is going to be 40, 50 years plus, maybe you want to go put all the gadgets from day one. 138 00:10:20.440 --> 00:10:25.601 The issue becomes when you have a transformer that is already 67 years old, and you want to prolong the life. 139 00:10:25.641 --> 00:10:27.062 So that's what I would do. 140 00:10:27.102 --> 00:10:27.342 I would... 141 00:10:28.602 --> 00:10:43.482 add the intelligence and through the intelligence you will really identify which stations are going i would say at risk which component at risk and do like a pretty system-wide enterprise risk management i like to do it by substation first and then by equipment usually the transformer gets i guess the first place and so forth 142 00:10:43.642 --> 00:10:52.354 Yeah, I think Ahmed brings up good points in terms of looking at asset condition, asset health, and then the risk associated with that data. 143 00:10:52.374 --> 00:10:59.985 And then when you take that data, combine it with engineering expertise to come up with where we believe we need to spend the money. 144 00:11:00.705 --> 00:11:07.787 And, you know, at Ameren, we also have a grid plan that we file with our Commerce Commission every four years. 145 00:11:07.947 --> 00:11:20.591 And we run projects through four different frameworks there from a, you know, reliability perspective, cost effectiveness perspective, affordability, and then equity. 146 00:11:20.651 --> 00:11:27.274 So making sure that we're spending the right amount of money in the right place at the right time, you know, to make sure that we're – 147 00:11:28.634 --> 00:11:31.685 you know, keeping service to our customers. 148 00:11:31.980 --> 00:11:37.361 Yeah, and so let's talk about the technology that you all are using when it comes to asset management. 149 00:11:37.541 --> 00:11:46.183 And specifically starting at the beginning, if utilities are evaluating what technology they're going to use for asset management, what are you really looking for? 150 00:11:46.243 --> 00:11:49.384 What are you really trying to solve as you figure that out? 151 00:11:49.724 --> 00:11:58.666 In my opinion, it's really how do you take the new data that you get and how do you get the value out of the data? 152 00:11:58.686 --> 00:11:59.946 So collecting data is great. 153 00:12:00.586 --> 00:12:03.028 But if you don't do anything with it, it's just more data. 154 00:12:03.509 --> 00:12:16.382 So how do you incorporate that new data into your processes, into your workflows, into your risk management systems to help you identify and evaluate where you need to spend the money? 155 00:12:17.243 --> 00:12:29.955 You know, so thinking about whether it's substation, whether it's line assets, taking that additional data, making sure that it's something that our engineering team and operations teams believe that is valuable. 156 00:12:30.476 --> 00:12:37.743 In that case, then they'll take it, use it effectively to improve our, you know, where we're going to spend the money and how we're going to spend it. 157 00:12:37.883 --> 00:12:41.946 I think it also has to do with understanding, well, what data do I want to collect? 158 00:12:42.126 --> 00:12:46.409 Because I think one of the mistakes is saying, well, I'm just going to go get data for the sake of data. 159 00:12:46.609 --> 00:12:47.830 Like sensors are expensive. 160 00:12:49.171 --> 00:12:51.172 Some of them have to be maintained, right? 161 00:12:51.212 --> 00:13:00.959 Like if your sensor breaks down or you have to spend more time or man hours going to maintain the data collection, that's not really going to add to your productivity. 162 00:13:01.379 --> 00:13:05.762 So I think actually kind of starting with like, what problem do we want to solve? 163 00:13:06.322 --> 00:13:13.050 and what is the data that we can collect and how much of it should we collect in order to get what we need. 164 00:13:13.911 --> 00:13:22.962 I think that's where utilities should start because I think I've also seen a lot of sensor deployment initiatives where it was just like, well, we have some budget. 165 00:13:22.983 --> 00:13:25.125 We're going to go deploy things out there. 166 00:13:25.946 --> 00:13:31.690 well, we don't know where that data is going and whether it's actually useful to us or whether it's getting to the person who needs to make the decision. 167 00:13:31.790 --> 00:13:34.452 So I would say that's a good place to start. 168 00:13:34.552 --> 00:13:41.697 And then it's also important to kind of architect the data flow to say, well, once I got it, who has access to it? 169 00:13:41.817 --> 00:13:42.677 Where is it going? 170 00:13:42.797 --> 00:13:44.419 How is it getting distilled down? 171 00:13:45.139 --> 00:13:47.801 Even from the drone

perspective, one of the challenges that we have 172 00:13:48.601 --> 00:13:59.066 saw once people started using them ubiquitously was, well, nobody has time to sit and look through like 20,000 photos to figure out, you know, here are the 20 problems that I had, right? 173 00:13:59.146 --> 00:14:15.153 So I think even for us at Skydio, we partner with other third-party AI post-processing vendors to take all of the images that we capture and still it down so that we can help utilities figure out, well, what are the 20 problems that actually exist? 174 00:14:15.549 --> 00:14:19.994 So I'm not wasting a bunch of man hours trying to look through the data that was collected. 175 00:14:20.214 --> 00:14:22.337 Yes, I mean, a great answer by Jason and Christine. 176 00:14:22.357 --> 00:14:28.744 I mean, the one thing I would add is the issue initially when you install a new sensor for a device. 177 00:14:28.784 --> 00:14:34.591 For example, if you had like a lightning arrestor or any device that you never collected any data from, that becomes very challenging because... 178 00:14:34.911 --> 00:14:36.892 You know, the workforce have never received any data. 179 00:14:36.912 --> 00:14:39.192 They can't really tell the value of the data. 180 00:14:39.552 --> 00:14:44.334 And that's going back to that point Christina just mentioned, is the importance of partnering with third party. 181 00:14:44.534 --> 00:14:48.075 And maybe the vendor who made the sensor in the first place, they provide a lot of insight. 182 00:14:48.235 --> 00:14:51.876 From an operations perspective, from my own experience, the biggest issue is like the false positive. 183 00:14:52.456 --> 00:14:53.836 So I think it was kind of mentioned here. 184 00:14:53.916 --> 00:14:56.697 It's like how you go from the data to intelligence. 185 00:14:56.837 --> 00:14:59.318 We don't want to have, you know, data every millisecond. 186 00:14:59.358 --> 00:15:01.358 We want the data only when it's needed. 187 00:15:01.438 --> 00:15:04.339 And I know it's very easy to ask, but it's a very difficult answer to it. 188 00:15:04.399 --> 00:15:04.619 Yeah. 189 00:15:04.859 --> 00:15:14.086 And beyond just, you know, knowing how to collect that data, I'm curious about the specifics of what's the most valuable data when it comes to a utility who wants to do maintenance planning. 190 00:15:14.106 --> 00:15:18.849 You can do inspection history, condition data, outage history, age, location. 191 00:15:18.889 --> 00:15:26.535 You know, what are the pieces of data that that you all found have been most valuable versus the ones that are just superfluous in some way? 192 00:15:27.396 --> 00:15:34.145 In my mind, I think it's really, there's probably three, inspection history, outage history, and then condition data. 193 00:15:34.545 --> 00:15:37.009 And then, you know, if you want to throw in a fourth, it'd be the location. 194 00:15:37.089 --> 00:15:42.876 So, you know, given, given, you know, having just one single point of data tells you one thing. 195 00:15:43.437 --> 00:15:46.438 having a combination of data around an asset tells you more. 196 00:15:47.218 --> 00:15:57.400 So being able to combine all four of those or three of those, you know, into, into overall condition or overall risk helps drive, helps drive a better picture. 197 00:15:57.620 --> 00:15:58.400 Yeah, I agree. 198 00:15:58.480 --> 00:16:02.081 I think that I don't think there's a single data point that tells the whole story. 199 00:16:02.761 --> 00:16:06.442 So as Jason's saying, you have, I would say condition history. 200 00:16:07.562 --> 00:16:11.063 And, and outage history is probably the most important because then you're 201 00:16:11.163 --> 00:16:20.552 You can say, well, the OEM says that my maintenance needs to be once a quarter, but at the end of the day, why do I see that these shear pins are breaking consistently? 202 00:16:21.232 --> 00:16:27.538 Or consistently in this location and this machine, but not the identical one in a different region. 203 00:16:27.658 --> 00:16:31.922 And I think that really helps root cause to understand... 204 00:16:32.863 --> 00:16:45.908 why the changes are happening or why certain assets are behaving differently or failing differently, which then helps you kind of get those patterns and then dispatch your response accordingly. 205 00:16:46.149 --> 00:16:49.790 Yeah, the one additional thing I would add is the external factors. 206 00:16:50.330 --> 00:16:59.014 So everything Jason and Cristina mentioned, I agree with, but I used to play with the equipment ratings and the ratings, they're based on a certain 24 hour ambient temperature. 207 00:16:59.694 --> 00:17:26.902 every year we break the record at least in the east coast in new york where i live you know the hottest year the hottest year you know it's like but if you don't go back and look at your equipment so two things are happening the load is going up but technically the equipment have been derated but we don't know so that's the beauty of of course you have like in a hot spot top oil all this kind of temperature so i mean the only thing i would add is you really need i'm not going to say like a climate change kind of group but you need to look at for example in new york city almost every other week now we have massive flooding i'm talking about like 208 00:17:27.362 --> 00:17:30.043 the whole city on the water, not like, you know, a few inches. 209 00:17:30.544 --> 00:17:37.307 So what's happening at the, of course, people are focused on the streets and all the stuff, but what's happening at the stations really are the switch gear under two or three. 210 00:17:37.367 --> 00:17:40.188 So it's almost like a mini Sandy that we get every year. 211 00:17:40.708 --> 00:17:44.670 So that's the only thing I would add to them is like, you know, the randomness of the weather. 212 00:17:45.150 --> 00:17:47.211 How does it impact the asset itself? 213 00:17:47.311 --> 00:17:49.012 And now it's

not just transformer. 214 00:17:49.092 --> 00:17:50.172 It's everything pretty much. 215 00:17:50.272 --> 00:17:52.333 And as Jason mentioned, you also have to look at the lines. 216 00:17:52.994 --> 00:17:55.795 You compare the lines outside the fence from inside the fence and so forth. 217 00:17:55.953 --> 00:17:56.173 Yes. 218 00:17:56.293 --> 00:18:02.278 And so there's all this data that you're collecting on the decisions about where and how much and how frequently. 219 00:18:02.799 --> 00:18:09.064 But we've also kind of heard that there's also the question of turning that data into, well, now what do you do with it? 220 00:18:09.084 --> 00:18:11.947 It's not just having data for the sake of data, I think we heard earlier. 221 00:18:12.007 --> 00:18:18.793 So where do you see utilities typically struggling when it comes to translating that field information into resources? 222 00:18:19.394 --> 00:18:27.954 taking action and you know what does it take to move from oh great we have data to all right here's the decision making process we're going to use based upon that data 223 00:18:28.662 --> 00:18:31.744 I think the struggle is actually in the utility silos. 224 00:18:32.645 --> 00:18:37.308 And, you know, Jason and Arvight, you can tell me how it is in your organizations. 225 00:18:37.388 --> 00:18:41.811 But a lot of times I see, especially in large utilities, that there are just many, many divisions. 226 00:18:41.891 --> 00:18:47.915 And those divisions are very large, and they have a leader, and they are sometimes spread out even geographically. 227 00:18:48.175 --> 00:18:50.977 And so I think even from the person who catalyzed, 228 00:18:50.977 --> 00:19:01.225 captures the data to the person who needs to analyze the data to the person who needs to make the decision, they may sit in completely different departments and may or may not talk to each other very much. 229 00:19:02.186 --> 00:19:05.889 So that's one of the challenges that I've seen across the board that... 230 00:19:07.631 --> 00:19:24.091 Aside from data standardization and data management, which are also challenges in and of themselves, it's just really trying to understand within the organization and get alignment and get agreement on this is what we're doing, why we're doing it, and this is the process that we're going to follow. 231 00:19:24.469 --> 00:19:26.591 Yeah, I think Christina brings up a great point. 232 00:19:26.611 --> 00:19:43.623 You know, with a large utility spread out, you know, across 45,000 square miles in Illinois, you know, communicating to one person in the southern part of the territory and communicating to someone else in the northern part of the territory, you might think the message gets out there and you might think it's consistent. 233 00:19:43.843 --> 00:19:45.584 And then you find out that it's not. 234 00:19:45.644 --> 00:19:49.867 So really, in my mind, it's around putting structure to that data. 235 00:19:49.987 --> 00:19:52.489 You know, what are we looking for? 236 00:19:52.569 --> 00:19:53.670 Why are we looking for it? 237 00:19:54.270 --> 00:20:00.813 who's gonna use it because who uses it might determine exactly what they're looking for or why they're looking for it. 238 00:20:01.714 --> 00:20:13.800 You know, and then bringing it back to, in my mind, to a central group, again, thinking about our grid plan around how do we use that data consistently, whether it comes from our north or south or east or west region, 239 00:20:14.360 --> 00:20:29.872 that we're looking at this information unilaterally, I guess is maybe the better way to say it, across the board so that we're making the best decision across Ameren's territory, not the best decision in the north or the best decision in the south. 240 00:20:29.932 --> 00:20:30.693 Yeah, that's a great point. 241 00:20:31.493 --> 00:20:36.737 One thing I would add is, as I mentioned, we went from having a data drought to a data avalanche. 242 00:20:37.238 --> 00:20:37.438 Yeah. 243 00:20:37.458 --> 00:20:53.775 so much data everywhere every which is great I think the one thing and again I've worked on planning a lot I worked in operations a lot and a planner versus an operator they need to see two different things the operator operates and Jason I think you have the whole you have you're the VP developing so 244 00:20:54.436 --> 00:20:58.858 He doesn't he or she doesn't have the luxury to do an analysis and a research and like a 10, I mean, they operate. 245 00:20:58.878 --> 00:21:00.079 So I think we have to differentiate. 246 00:21:00.119 --> 00:21:11.045 And the problem that I see personally, as we do all this kind of asset management 2.0, if you will, at the end of the day, it's all meant to guide the operator to do a better job in his or her decision. 247 00:21:11.768 --> 00:21:17.931 But the mistake I've seen is that we convert the operator job to an engineering or analysis. 248 00:21:17.991 --> 00:21:20.712 Or we don't have that group that analyze the data. 249 00:21:20.732 --> 00:21:24.333 So as Christina mentioned, you have all this data coming in and you said it's the control room. 250 00:21:24.813 --> 00:21:25.814 This is not their job. 251 00:21:26.234 --> 00:21:27.094 This is not the entity. 252 00:21:27.695 --> 00:21:32.997 There will be a lot of false positive, unfortunately, and every time there's like the wrong alarm, you know, you kind of lose credibility. 253 00:21:33.817 --> 00:21:39.124 But I think that kind of, Christina mentioned the drones, like you don't want to have like, you know, a picture of every poll. 254 00:21:39.284 --> 00:21:40.986 You want the 10, 20 that has an issue. 255 00:21:41.006 --> 00:21:41.927 So I think that's good. 256 00:21:42.408 --> 00:21:52.540 I'm not saying it's an easy problem to fix at all, but the control room and the user should get the absolute minimum, most important data to move. 257 00:21:53.145 --> 00:21:56.066 For example, if you have a drone, which is great, you

don't want to send them a 24-7 feed. 258 00:21:56.186 --> 00:21:58.367 You know, this is not like, you know, like watching a game. 259 00:21:58.568 --> 00:22:01.729 You want to send them only like, you know, so that's my thing. 260 00:22:01.749 --> 00:22:03.330 And it's a very difficult task. 261 00:22:03.430 --> 00:22:06.151 And usually it is the task of asset management. 262 00:22:06.391 --> 00:22:08.932 Okay, you guys are going to bring new equipment, new sensors. 263 00:22:09.733 --> 00:22:13.395 Just give, as I mentioned, and the utility is massive, really. 264 00:22:13.415 --> 00:22:15.175 And between the same utility, we do things different. 265 00:22:15.195 --> 00:22:16.076 We use different equipment. 266 00:22:16.476 --> 00:22:18.457 So you have to really tailor it based on the customer. 267 00:22:18.477 --> 00:22:20.458 In this case, the customer would be operations. 268 00:22:20.738 --> 00:22:21.279 Absolutely. 269 00:22:21.299 --> 00:22:23.240 And I think something's interesting. 270 00:22:23.260 --> 00:22:30.306 You know, Christine and I have had a conversation about asset management on this podcast with some representatives of smaller utilities. 271 00:22:30.786 --> 00:22:34.389 Ahmed and Jason, you guys have experience at some very big utilities. 272 00:22:34.449 --> 00:22:39.593 And Jason, you even just mentioned how sometimes that geography can be a unique challenge. 273 00:22:39.613 --> 00:22:46.659 So I'm curious to dive in more into how asset management shifts when we are looking at the bigger utility landscape. 274 00:22:46.679 --> 00:22:47.079 Things like 275 00:22:47.499 --> 00:22:51.285 institutional knowledge could be tougher to track or disseminate at a larger scale. 276 00:22:51.865 --> 00:22:59.536 What other sorts of changes occur when a utility has to manage assets across a much larger geography and system footprint? 277 00:22:59.808 --> 00:23:00.068 Yes. 278 00:23:00.248 --> 00:23:12.633 So, you know, I really think it comes down to, again, back to having a strong process around what you're going to do with the data and making sure that that's understood across across the enterprise. 279 00:23:12.673 --> 00:23:17.115 So I'd say years ago, there was a lot of institutional knowledge. 280 00:23:17.255 --> 00:23:22.697 And sometimes that institutional knowledge is walking out the door and then you're hiring somebody new that doesn't have any of that. 281 00:23:23.517 --> 00:23:25.179 So, so what do we do? 282 00:23:25.219 --> 00:23:26.781 How do we have the data? 283 00:23:26.841 --> 00:23:28.102 How do we have the information? 284 00:23:28.142 --> 00:23:33.667 How do we have it in a standard place so that somebody with 35 years experience knows where it's at? 285 00:23:34.108 --> 00:23:43.317 And somebody with five weeks of experience knows where it's at, and can come to similar similar conclusions based on the data, not based on what their gut tells them. 286 00:23:43.545 --> 00:23:44.446 Yeah, absolutely. 287 00:23:44.566 --> 00:23:49.672 And I think, and I've said this, I think probably on another podcast, but I mean, I've lived it. 288 00:23:49.732 --> 00:23:56.380 When I was hired in, I was an engineer apprenticing for the lead hydro engineer, probably in the country. 289 00:23:57.181 --> 00:24:01.046 And I was with him for over 10 years, 13 actually, until he... 290 00:24:01.466 --> 00:24:02.287 retired, right? 291 00:24:02.327 --> 00:24:05.211 But the goal had always been like, oh, well, she's the apprentice. 292 00:24:05.231 --> 00:24:06.673 She's going to learn everything from him. 293 00:24:07.094 --> 00:24:11.780 And once he retires, she's going to plug all the leaky holes in this entire organization. 294 00:24:11.880 --> 00:24:14.083 And every time there's a problem, that's who we're going to call. 295 00:24:14.724 --> 00:24:18.889 And, you know, clearly I am not there anymore and I am not plugging the holes. 296 00:24:19.590 --> 00:24:29.914 And that is something that I think has just been a shift in the culture in the utility landscape where it's just I mean, Jason, I think I think you are evidence of it. 297 00:24:30.194 --> 00:24:34.636 It was normal to stay 30 years, 40 years in a career, work your way up. 298 00:24:34.696 --> 00:24:35.856 You become the expert. 299 00:24:35.977 --> 00:24:37.077 Everybody relies on you. 300 00:24:37.117 --> 00:24:41.879 But you have a wealth of knowledge and experience that goes out the door when you retire. 301 00:24:42.759 --> 00:24:47.041 And I think that at least for me, when I was still at the utility, that was kind of our 302 00:24:47.561 --> 00:24:53.484 our heartburn year to year just saying, well, the class of retirees is just coming in waves. 303 00:24:54.264 --> 00:24:58.286 And yet, you know, fresh grads out of college are not coming in the same waves. 304 00:24:58.886 --> 00:25:03.969 And it really takes, I think, a decade or more to really understand like one part of a utility. 305 00:25:04.149 --> 00:25:06.710 So I think that is also, as I said in the beginning, 306 00:25:07.070 --> 00:25:10.633 the case for change because it's just not the norm. 307 00:25:10.673 --> 00:25:14.075 It's not the mindset of a 22 year old coming out of college anymore. 308 00:25:14.255 --> 00:25:14.755 Absolutely. 309 00:25:14.775 --> 00:25:28.205 And, you know, so again, some unique areas that the larger utilities have to deal with, but there's also, I'm sure some, some universal truths that, you know, maybe the smaller utilities can learn from what the larger utilities are doing. 310 00:25:28.225 --> 00:25:31.567 Is there anything that comes to mind when it comes to those sorts of lessons learned? 311 00:25:32.245 --> 00:25:39.553 One thing I could add, I guess as Jason mentioned, I've learned significantly because I had two managers when I was in Con Ed. 312 00:25:40.634 --> 00:25:42.737 They were like 30 plus years in the company. 313 00:25:43.277 --> 00:25:44.078 They taught me a lot. 314 00:25:44.218 -->

00:25:46.941 And then I had a mentorship from an executive level. 315 00:25:46.961 --> 00:25:48.223 So I think once you have somebody to 316 00:25:48.940 --> 00:25:51.683 talk to you at Eric Curry, the problem is most of those people retired. 317 00:25:52.904 --> 00:25:56.488 And I personally believe maybe their expertise is very needed right now. 318 00:25:56.528 --> 00:25:58.991 So whether they come back as a kind of freeze retirement or something like that. 319 00:25:59.391 --> 00:26:09.361 You know, podcasts like this one and Energy Central and others is very, very critical because I mean, I will tell you something very interesting is I don't really believe you need more pilots. 320 00:26:09.942 --> 00:26:10.643 We just need to talk 321 00:26:11.270 --> 00:26:39.977 among one another you know benchmarking is very critical like really and I've been very fortunate to talk to like a lot of global utility just to find out what's happening you know you know I'll give an example of usually when people like engineers utility engineers they travel to Europe and if how was your trip nobody talks about you know the Eiffel Tower oh everything is underground like so it's this simple yeah their vision is okay so how come they could do it the street is like 2,000 years old so there's really no need to reinvent everything I think if we do like work 322 00:26:41.577 --> 00:26:45.440 That would be very clear, but as Jason mentioned, we're losing a lot of talent. 323 00:26:46.581 --> 00:26:50.584 But at the same time, we have a new way of thinking, like the data, the analysis. 324 00:26:50.684 --> 00:26:52.045 We have a lot of tools they didn't have. 325 00:26:52.505 --> 00:27:00.511 So somehow between the knowledge, hopefully it's a good knowledge transfer, succession planning and eternity before they departure, and the data. 326 00:27:00.631 --> 00:27:05.455 And now AI, again, I'm very careful when I say about AI, but I believe AI could also help as well. 327 00:27:05.727 --> 00:27:06.187 Yeah. 328 00:27:06.267 --> 00:27:21.836 And, you know, Matt, I think whether whether it's a large utility or a small utility, all utilities have assets, all utilities have risk and making and making informed decisions based on that around your asset condition and around the risk associated with that. 329 00:27:22.176 --> 00:27:25.878 It doesn't matter if you're, you know, super small or a huge utility. 330 00:27:26.498 --> 00:27:27.138 We all have that. 331 00:27:27.398 --> 00:27:28.099 We all have that. 332 00:27:28.399 --> 00:27:32.141 So, you know, I think that's common, just common across the industry. 333 00:27:32.646 --> 00:27:32.966 Excellent. 334 00:27:33.146 --> 00:27:36.029 And so now, you know, we've been talking about the state of things today. 335 00:27:36.049 --> 00:27:43.155 I want to shift towards looking to the future and how we keep this reliability that's so critical in the coming years. 336 00:27:43.715 --> 00:27:52.563 You know, at its core, what do you

think utilities need to be doing today to prepare for, let's call it the next five years of operational pressure that we know is coming down the pipeline? 337 00:27:52.583 --> 00:27:52.783 Yeah. 338 00:27:52.963 --> 00:28:03.291 I think I'd start with, you know, again, I mentioned it earlier, it's around having a good structure, having a good process, and then setting the strategy on how you're going to use the data. 339 00:28:03.971 --> 00:28:08.394 Because, you know, culture eats strategy all day long. 340 00:28:08.975 --> 00:28:14.639 So if you have that strategy on what you're going to do, but then you build it into your culture, 341 00:28:15.639 --> 00:28:24.405 you're going to have much gain, much more value out of the data, out of the asset management and help drive, help drive your plans going forward. 342 00:28:25.226 --> 00:28:31.270 And quite honestly, we got to get some, some of the, some utilities have a lot of historical data. 343 00:28:31.710 --> 00:28:33.191 Some folks are just capturing it. 344 00:28:33.631 --> 00:28:38.875 So you got to start the process now to be able to be effective, you know, five, 10 years down the road. 345 00:28:39.040 --> 00:28:49.933 Yeah, and I would say we learned a lot reliability wise from resiliency, like from like first time events, you know, the first massive heat wave, the first massive wildfire, the first earthquake. 346 00:28:49.953 --> 00:28:51.475 So unfortunately, we'll be getting a lot of this event now. 347 00:28:51.495 --> 00:28:52.837 Of course, they're all resiliency. 348 00:28:53.575 --> 00:28:54.696 But what really changed? 349 00:28:54.776 --> 00:28:57.458 I mean, I would say a lot of utilities, you know, the 100 plus years. 350 00:28:57.498 --> 00:29:00.921 So that got us all the way to like the year 2025 and beyond. 351 00:29:01.562 --> 00:29:05.966 Now we really have to make some changes, you know, for the next 5, 10 years from now. 352 00:29:06.506 --> 00:29:09.529 I would say the change in the workforce is very critical. 353 00:29:09.549 --> 00:29:12.992 Yes, it doesn't impact directly the reliability, but the way we behave, the way we think. 354 00:29:13.747 --> 00:29:17.990 One thing that we have now that they have in the past is people cannot lose power anymore. 355 00:29:18.070 --> 00:29:19.771 I mean, their life literally stops. 356 00:29:19.811 --> 00:29:23.193 That's a very big change compared to the past. 357 00:29:23.254 --> 00:29:29.518 But I would say just to stick with the theme of this podcast is I think you mentioned before, you know, you have a capital. 358 00:29:29.898 --> 00:29:31.979 The capital is very tight now with customer affordability. 359 00:29:31.999 --> 00:29:32.500 So you want to have. 360 00:29:32.980 --> 00:29:51.513 what i call the data into dollars so like what's the most important data to provide the most cost effective kind of investment for the utility for the customer and so forth and one thing i would say like you know substations are the biggest assets we have and and i would say one more time is that they very they're all very critical but they don't have the same weight if you will 361 00:29:52.033 --> 00:30:18.913 so reliability we still follow a humanistic approach but we need to be very careful like you know what's the outcome and one thing we haven't discussed today is the whole physical and cyber security so while you're doing all this stuff as management you have physical attacks on substation again there's a lot of unfortunately other places globally are going through a lot of escalation right now so there are some stuff so basically we could learn from anything that's happening globally and we could implement here and we could use network like we're having right now 362 00:30:19.313 --> 00:30:21.915 and others to learn what worked well, what didn't. 363 00:30:22.075 --> 00:30:26.198 Yeah, and I think I would add one more word to this, which is scalability. 364 00:30:26.399 --> 00:30:32.603 So I think over the next five years, utilities, you're not going to have more people, you're not going to have fewer assets. 365 00:30:32.723 --> 00:30:38.488 If anything, you're going to be asked to expect more infrastructure, respond to more extreme weather events, 366 00:30:38.868 --> 00:30:45.351 and deliver even higher levels of reliability while navigating the workforce challenges and the increased cost pressure. 367 00:30:45.391 --> 00:31:01.580 So I feel like utilities really looking forward need to think beyond solving today's problems, but the focus should really be on building systems and workflows that can handle tomorrow's demands without having the safety net of adding more people or trucks, right? 368 00:31:01.600 --> 00:31:06.743 So I think creating processes is always, you know, that's an arduous, 369 00:31:07.863 --> 00:31:14.226 task, but it really needs to be repeatable, standardized, and efficient, and really communicated across the organization. 370 00:31:14.366 --> 00:31:24.912 So I think from my standpoint, kind of coming out of the utility world and into the tech world is, I think this is where we can make a really big difference, not because it's new, but because it helps teams scale. 371 00:31:25.132 --> 00:31:33.796 So I think even for us at Skydio, we reached a point where we realized, well, we can manufacture more drones, we can make different versions of drones that do different functions. 372 00:31:34.276 --> 00:31:55.388 But the real unlock for scalability was going to be in remote operations, the ability to operate the drones when the pilot is not there on site, when the pilot is operating multiple drones at the same time in multiple states and territories, and being able to get eyes out in the places where it would take a very long time or require a lot of danger to get a person to roll a truck. 373 00:31:55.528 --> 00:32:03.313 So I think that is one example of how technology has to look at scaling, but I do think that utilities absolutely need to

think about scale. 374 00:32:03.493 --> 00:32:14.457 Amit, if I would just may, this is a very important point that Christina mentioned is I believe the strong partnership between utilities and the market, vendors, technology provider is very, very critical. 375 00:32:14.798 --> 00:32:18.519 You know, Christina is lucky because she was in the utility and now she's in the other side. 376 00:32:18.879 --> 00:32:20.640 Like there'll be a lot of benefit from something 377 00:32:21.719 --> 00:32:25.742 There'd be a lot of benefits, you know, for utilities to work with, you know, entities like, you know, Christina and others. 378 00:32:25.762 --> 00:32:28.403 So you could bring in technology for usage. 379 00:32:28.563 --> 00:32:37.409 And so as utilities build in these processes, these strategies, what should they be looking at as the signal that, all right, things are working well? 380 00:32:37.469 --> 00:32:44.514 What are the tells that it's, you know, the operational strategy is working or not working? 381 00:32:44.714 --> 00:32:47.576 So the good, bad news is that we have a lot of storms. 382 00:32:47.856 --> 00:32:49.957 We have a lot of heat waves now, a lot of cold fronts. 383 00:32:49.977 --> 00:32:50.738 So you don't have to wait. 384 00:32:51.432 --> 00:32:54.193 of the year 3000, you know, things are happening pretty much every week. 385 00:32:54.693 --> 00:32:57.835 So you could always kind of evaluate the performance versus expectation. 386 00:32:57.855 --> 00:32:58.675 So I'll just put it over. 387 00:32:58.695 --> 00:33:00.195 Yeah, I think, I think I'm at it. 388 00:33:00.215 --> 00:33:02.977 It's really around what is, how's the system performing? 389 00:33:02.997 --> 00:33:03.837 Is it performing better? 390 00:33:03.857 --> 00:33:04.777 Is it performing worse? 391 00:33:05.277 --> 00:33:07.718 You know, are there fewer unexpected failures? 392 00:33:08.199 --> 00:33:11.340 You know, are we continuing to do things proactively? 393 00:33:11.780 --> 00:33:14.441 You know, I think that's, I think that's really the telltale signs. 394 00:33:14.601 --> 00:33:22.946 Yeah, and I think it's, when we think about success metrics or KPIs, I don't think it's measured by how many inspections you perform, necessarily. 395 00:33:23.006 --> 00:33:24.907 It's measured by your reliability and proof. 396 00:33:25.387 --> 00:33:41.097 So really looking at metrics that are more in line with how many forced outages have you had, how many repeated truck rolls have you had, what is the restoration time in the event of an outage, or even looking at your inspection backlog and saying, well, how long is that? 397 00:33:41.777 --> 00:33:42.678 Kelly hit it down. 398 00:33:42.698 --> 00:33:46.400 So I think those are some of the metrics that I would suggest to look at. 399 00:33:46.640 --> 00:33:46.880 Excellent. 400 00:33:46.900 --> 00:33:48.381 Yeah, that's good insight. 401 00:33:48.501 --> 00:34:01.949 And to kind of wrap a bow on this conversation and again, making it forward looking, I'd love to ask each of you, what specific role do you see better data and better data feeding into more automated workflows? 402 00:34:02.269 --> 00:34:07.012 How will those play into the next generation of utility operations and utility assets? 403 00:34:07.520 --> 00:34:21.923 I would say maybe I have to think about this, but if we were to create like a new KPI or kind of performance metrics that measures for every new device, for example, the data into action, for example, again, you put a certain sensor. 404 00:34:22.884 --> 00:34:26.084 Yes, you get like millions of data points per day, but that's what we were looking for. 405 00:34:26.144 --> 00:34:30.025 Okay, so whether it's a near miss, you know, kind of reducing O&M. 406 00:34:30.045 --> 00:34:35.827 So that's maybe the only thing I would add is a whole new structure of metrics, not safety, not KD and all the stuff. 407 00:34:36.867 --> 00:34:40.512 for every installation or for every data points we're adding, here's the outcome. 408 00:34:40.632 --> 00:34:45.939 And for example, like Cristina mentioned, you know, it's not, okay, it's not about doing a lot more, I guess, inspection. 409 00:34:45.979 --> 00:34:51.787 It's what do the utility not know that now this inspection or this picture of this drone is providing. 410 00:34:52.067 --> 00:34:56.371 Yeah, I think I'd add in, you know, it's really around having more data. 411 00:34:56.411 --> 00:34:58.573 I think Ahmed said earlier, we got a data avalanche. 412 00:34:58.913 --> 00:35:01.556 So we went from having no data to lots of data. 413 00:35:01.576 --> 00:35:10.844 And how can how can our new tools, how can our new technology help us evaluate that data, analyze that data, predict what we should be working on and what we shouldn't be working on? 414 00:35:11.905 --> 00:35:16.910 You know, because again, given given the new, you know, the new era that we're in, 415 00:35:17.590 --> 00:35:21.073 You know, guys like me that got 30 years of experience, well, that's all well and good. 416 00:35:21.133 --> 00:35:23.174 But a lot of people want to say, show me the numbers. 417 00:35:23.555 --> 00:35:38.566 So, so, you know, if you, if you have, have the truth, have the statistics to help prove what your gut tells you, um, just provides that much more, uh, you know, evidence benefit on, on why you should be, should be, or shouldn't be doing a certain project. 418 00:35:38.626 --> 00:35:44.048 Yeah, and I would just piggyback on that to say the future isn't about collecting more data. 419 00:35:44.088 --> 00:35:47.169 It's about shortening the path from the insight to the action. 420 00:35:47.329 --> 00:35:51.231 So obviously you can't start when you don't have the insight. 421 00:35:51.291 --> 00:35:56.853 Then you're just depending on the tribal knowledge or the history or whatever standards you've been using before. 422 00:35:57.213 --> 00:36:00.174 But I think after that, it's really saying, well, we

get to the action. 423 00:36:00.194 --> 00:36:01.875 We did the right action in the right order. 424 00:36:02.775 --> 00:36:06.537 And I think data is really only valuable when it changes what somebody is going to do next. 425 00:36:06.878 --> 00:36:07.318 Absolutely. 426 00:36:07.338 --> 00:36:11.642 That's a really great and valuable note for us to wrap this conversation on. 427 00:36:12.162 --> 00:36:16.626 I do want to throw us to, before we let you guys go, our lightning round. 428 00:36:16.986 --> 00:36:20.869 This is where we're going to ask you just a couple rapid fire questions. 429 00:36:21.089 --> 00:36:27.334 One sentence, one word from each of you just to get a little bit more peek behind it all. 430 00:36:27.755 --> 00:36:31.958 So from each of you, what is the most exciting development in the industry today? 431 00:36:32.268 --> 00:36:34.451 My opinion, I'd say it's probably three things. 432 00:36:34.651 --> 00:36:40.357 Advanced tools for utilities, AI, and then really just all the increased automation that there is on the system. 433 00:36:40.838 --> 00:36:46.845 I think for me, it's the move from reactive operations to proactive data-driven decision-making. 434 00:36:47.310 --> 00:36:52.613 I think it's how important asset management is right now with all the escalation that is happening in the Middle East. 435 00:36:52.733 --> 00:36:56.195 So now it's time to go back and take a look at everything we do asset management. 436 00:36:56.315 --> 00:37:00.897 On that note, what is one metric all utilities should be watching more closely than they already are? 437 00:37:01.138 --> 00:37:04.259 I think it's affordability versus reliability. 438 00:37:04.980 --> 00:37:09.342 You know, for a long time, customer sentiment has been around. 439 00:37:09.862 --> 00:37:10.863 Are they having reliable? 440 00:37:10.883 --> 00:37:12.063 Do they have reliable service? 441 00:37:12.684 --> 00:37:16.626 And here recently that has shifted to do they have affordable service? 442 00:37:17.146 --> 00:37:20.850 So, you know, I think it's really that affordability versus reliability. 443 00:37:21.070 --> 00:37:23.172 So, yes, Jason answered that. 444 00:37:23.192 --> 00:37:31.601 So I'll just add, like, maybe the current use of tools, technologies as a partnership to address the point Jason mentioned. 445 00:37:31.621 --> 00:37:37.607 Like, you know, basically go outside your bubble to get more knowledge, more expertise to go back and do it in an affordable manner. 446 00:37:38.067 --> 00:37:40.550 Yeah, and for me, I would say it's inspection to action time. 447 00:37:40.690 --> 00:37:43.113 So finding an issue is only the first step. 448 00:37:43.213 --> 00:37:46.877 The value I think comes from how quickly you can prioritize it and address it. 449 00:37:47.117 --> 00:37:48.939 And last one, I'll get personal with it. 450 00:37:49.039 --> 00:37:51.182 What is your proudest career accomplishment? 451 00:37:51.803 --> 00:37:55.946 I'll go first, and I'm not sure this is my career, but maybe it may be an industry accomplishment. 452 00:37:55.966 --> 00:38:00.749 So when I started 30 years ago, we measured storm response in days and weeks. 453 00:38:01.470 --> 00:38:07.374 And now we're measuring storm response in minutes and hours or even seconds if it's automation. 454 00:38:07.434 --> 00:38:14.439 So, you know, I think that shift from it to, and Ahmed said earlier that, you know, people just can't go without automation. 455 00:38:15.059 --> 00:38:15.759 electric anymore. 456 00:38:15.819 --> 00:38:24.582 So that shift from how we've responded years ago to how we respond today and how the system is configured today, I think is a huge accomplishment. 457 00:38:24.982 --> 00:38:25.322 Oh, yeah. 458 00:38:25.362 --> 00:38:31.063 I was going to say for me, I think it's building a bridge when I transition between roles. 459 00:38:31.103 --> 00:38:35.245 So I think I spent most of my career in engineering and then moved to asset management. 460 00:38:35.385 --> 00:38:40.326 And I was really proud of being able to having been the one to design power plants and 461 00:38:40.686 --> 00:38:51.932 commission them and roll up my sleeves and be in the field and then come into a strategy role, but be able to bridge those who are out there doing the work and those who are strategizing the work that needs to be done. 462 00:38:52.852 --> 00:38:54.013 I think I was really proud of that. 463 00:38:54.133 --> 00:38:58.735 And then in my next phase of my career here, going from the utility 464 00:38:59.195 --> 00:39:06.439 to the technology vendor side, being able to bridge those who are keeping the lights on to those who are trying to make the technology that helps do that. 465 00:39:06.939 --> 00:39:11.982 I really enjoy working together with all of these different personas and trying to . 466 00:39:12.263 --> 00:39:17.906 Yeah, and for me, I was chosen to be the IEEE, Planet Positive Utility of the Future, 467 00:39:18.665 --> 00:39:18.945 chair. 468 00:39:19.525 --> 00:39:23.327 So what's interesting is, you know, I've been involved with climate change a lot and it's always negative news. 469 00:39:23.367 --> 00:39:24.327 You're all going to die. 470 00:39:24.367 --> 00:39:25.187 The end is near. 471 00:39:25.848 --> 00:39:32.190 So when I found that this called planet positive, so not only do they believe that who will survive will end up being positive. 472 00:39:32.850 --> 00:39:37.392 So I kind of work with them too, because I believe the eternity has a very important role in helping the planet gets better. 473 00:39:38.152 --> 00:39:52.132 everybody's welcome to join so that was something very interesting that happened recently i'm looking forward to working with a lot of global uh leaders students professors the whole nine yards to make the plant a better place and again thank you very much it's been a great being on this podcast with jason 474 00:39:52.578 --> 00:39:53.018 I appreciate it. 475 00:39:53.179 --> 00:39:53.699 That's wonderful. 476 00:39:53.719 --> 00:39:56.202 Yeah, thank you guys all for joining us today. 477 00:39:56.222 --> 00:40:00.726 This is a terrific conversation, and I enjoyed kind of getting each of your perspectives. 478 00:40:01.066 --> 00:40:01.887 Yeah, thank you very much. 479 00:40:01.927 --> 00:40:02.828 I greatly appreciate it. 480 00:40:03.048 --> 00:40:03.428 Likewise. 481 00:40:03.729 --> 00:40:04.089 Excellent. 482 00:40:04.129 --> 00:40:07.773 And thank you also to Skydio for making this episode possible. 483 00:40:08.113 --> 00:40:15.040 Skydio helps utilities move beyond outdated time-based maintenance to smarter, safer, and more scalable condition-based maintenance. 484 00:40:15.440 --> 00:40:20.402 Powered by autonomous remote-operated drones, over 280 utilities trust Skydio. 485 00:40:20.822 --> 00:40:29.506 Because with real-time aerial data and remote inspection, utilities can spot issues early, reduce forced outages, and make confident, efficient, cost-effective decisions. 486 00:40:30.327 --> 00:40:32.548 This has been an episode of Power Perspectives. 487 00:40:32.588 --> 00:40:36.089 Thank you so much for joining us today, to our guests and to all of our listeners. 488 00:40:36.390 --> 00:40:37.290 And we'll catch you next time.