The energy transition is accelerating grid complexity.

Welcome to today's Energy Central Power session entitled Bringing Transparency and Clarity from the Back Office to the Field. Before we begin, I would like to thank IQGeo for making today's event possible. Now, I'd like to turn the floor over to our moderator, Mike Smith, for today to kick things off. Mike, welcome to the event. You have the floor. Mike Smith, All right. Thank you, PJ. Thank you to our panel who will be introducing in just a few moments. And thanks to our audience. Thanks for joining us today. We think we have some interesting insights and experiences to share with you that are not only interesting, but also very timely with a lot of what we see happening on the grid today. So, next slide, PJ. I'm going to share just a few opening remarks with you all to kind of like I say, set the table or frame the issues that we'll be covering. And I think a good place to start is just recognizing the complexity and the scale of today's electric grid. I think maybe a lot of you have seen this quote before where it's the largest machine in the world and requires a lot of care and feeding. And we're going to be talking a lot about that today, particularly in light of how the utilities themselves, the energy landscape and how to make the grid work more effectively and efficiently through all this energy transition, I think is a really important topic. And I think we're all looking for ways to do that more effectively and efficiently. One of the tools, of course, that are used very prominently for this is GIS or in the old days, we call it AMFM. A lot of people will call it geospatial solutions today. It continues to be a growing market. It continues to be a growing market. I was first introduced to this 35 years ago as an analyst studying GIS and SCADA systems. And, you know, I can remember utilities just spending tens and tens of millions of dollars, not only on the systems, but on the digitization of maps and data and data conversion. I think we've come a long way now where these systems are not only part of the mainstream utility enterprise, but they're really critical in terms of things like the connectivity model. Often the asset system of record resides here as well. And we're going to be talking about some of this, particularly as GIS capabilities are pushed out to those important field crews. So it's growing for a reason. It's a critical piece of the grid management puzzle. And we'll be talking about that today. We also wanted to touch on some of the big issues and challenges that are driving network management. So just at a very high level, there's a few we'll just touch on here. The first one we're going to talk about is this increase in demand. The load is increasing. I think we all see that. And when you look at some of the metrics around how the load is increasing, it is a little bit staggering. I heard one data point from a Midwest utility that had a data center coming in and they said, when this thing goes live, it's going to be the equivalent of like adding 150,000 population city to our service territory, all in one fell swoop. So the data center and the AI demand, of course, is a big piece of that. But there's also just electrification that the utility itself is doing. And that is, of course, EVs, but also electrifying homes. Everything from how you cook, how you stay warm, how you heat water, all that electrification is definitely moving in that direction and is moving the needle on the load. So utilities are looking for ways to be more effective and efficient in how they manage the grid, which is all part of that delivery puzzle. The second area we'll just touch on briefly is around grid modernization and renewables integration. Grid modernization, I think, is a term that's used to describe everything from putting in new poles, new infrastructure, towers, transformers. That's an important piece of that, of course. But there's also a lot of intelligence that's part of grid modernization, of course. And that's everything from digitization to doing asset inspections with drones and using AI to some of the more basic tools that are part of that digital landscape for things like managing the effectiveness of work crews and controlling different aspects of the grid, particularly as renewables come online increasingly. I think we all know on this call we're all reasonably well versed in the industry and the old central station generation to transmission to distribution to the customer at the end of the line. That's pretty much gone or is in the stages of disappearing. And that means you have to manage the grid different ways. So there's a lot of dynamics there. And some of those we'll be touching on today. And then the third thing I wanted to talk about was kind of the financial picture in this current landscape and what we see lying ahead. And this applies not only to the utilities, but also, of course, to the customers themselves. I would venture to say in my role as an analyst and consultant over the last year, I've spoken with either informally or had formal interviews with 50 or more utility executives. And I would say that every one of them, just about every one of them, has an affordability initiative for their customers. I think we can discuss and debate probably endlessly what the drivers or symptoms are that are driving these affordability initiatives. But the reality is that that's a pressure on the utility. And by the way, they need to address this affordability while they're facing increasing costs and supply chains. Another discussion I had with the utility executive about a year and a half ago on the East Coast in the Southeast. So there's a lot of growth in their service territory. They were planning several new subdivisions. And what they were running into was supply chain issues, which drives up costs. It extends projects. The metric he gave me was what used to take six to nine months now takes 12 to 18 months or even two years for things like transformers and other critical equipment as their service territory grows. So this is certainly not a static environment that utilities are working in as they are looking to improve their network management, improve the effectiveness of their field crews, and do so in a way that is, I'll say, integrated and even moving towards being seamless with the enterprise. So that's some of the things that we'll be diving in today. And I think we're going to go from here and start our discussion with our panel. So what I would like to do is introduce our panelists individually and ask each of them kind of a leading off question. So we're going to dive into that. Before we do, I'll just remind our audience that if you do have questions, please put them into the chat. PJ and I are monitoring those. And as they come in, we'll make sure we do our best to incorporate those into the discussion. So having said that with our panel today, we're really lucky. We kind of have like a representative cross -section of the industry from a small co-op to a large investor-owned utility to a federal power agency to one of the leading solution providers that's working with all those across the field. So I'm going to start with our friend Vijay Bajnath, who's the division CIO at Portland General Electric. There, he's responsible for Power Digital Solutions Division, where he leads all facets of IT for energy generation and supply, energy trading, risk management, field operations, work and asset management, geospatial engineering, construction, distribution, transmission, market services. Holy cow, Vijay. I'm glad we got you for an hour today. Prior to his role at Portland General Electric, he was the director of IT business solutions for New Jersey Resources, where he led technology planning, implementation and operations for both NJR's deregulated clean energy generation business, which was primarily wind and solar, and its regulated natural gas utility energy efficiency and midstream companies. He was also with PSEG, Columbia Pipeline Group, Waste Management and MX Energy. Vijay has a BS in computer science from Rutgers. He is a Six Sigma Green Belt and certified scrum master. He also has completed MBA coursework at the University of Houston and executive leadership courses at the MIT Sloan School for Executive Education. So Vijay, thanks for joining us today. We're definitely going to tap into some of your expertise. And Vijay will be with us for the first hour of our 90 minutes together today. And then he had another commitment that he has to run off to. But we're glad we have you here for the first hour and we're going to make the most of it, Vijay. So let me start off our discussion by asking you a question here. As you and your team, as you continue to look at the capabilities and the field crews, and of course, there's a lot of IT infrastructure and data is a big piece of that. What is a lesson learned or maybe two lessons learned maybe from the business and technical sides of the geospatial and network management initiatives that you're a part of? So there's always the technical issues, the difficulties. It could be around systems integration or getting the right data to the right people, those sorts of things. But there's also the business side. What are those business problems you're solving? So maybe just a couple of lessons learned as you all have moved forward with improving the effectiveness and efficiency of those field crews at Portland. Yeah, sure. Just making sure you can hear me clearly, Mike. Yeah, all good. All right, perfect. Well, good afternoon, Mike. Thanks for the introduction there. I would say, you know, if we start with looking at this through the business lens, I think one of the most important lessons we've learned is that the adoption of these technologies in the field, it's earned, right, through trust and through proven usability. So if I think back to when we first implemented our field operations platform, we assumed that if we delivered advanced geospatial capabilities, the crews would immediately recognize the value and adopt the capabilities. In reality, I think the turning point for us came when we invited the crews, the field personnel into our design sessions. And on the flip side, we spent time with our field crews, whether we were walking job sites or observing how they responded to, you know, emergency situations and such. Using those experiences helped us shape key features of these platforms, such as offline capabilities, simplifying a lot of the pain points that these folks have dealt with over the many years. So in essence, that co-design and partnership really went a long way in developing what I would say are champions in operations who help advocate for the usability and success of what we co-created. So that's on the business side. If I think through the technical side, I think one of the biggest lessons we learned was twofold. One, the need for a strong foundation as it relates to data and system integration. So as you mentioned on the introduction, geospatial network models touch almost every aspect of utility operations, whether we're talking about outage management, asset management, even vegetation, wildfire risk programs. And if the data is incomplete or inconsistent, then crews and field operations personnel immediately start questioning the value of the platform. So we focused a lot of time in those areas. The other part is system integration. So as we roll these technologies out, we want to make sure that the information is timely. There's minimal lags in terms of loading and usability. So if someone zooms into a particular area of our service territory, the refresh rates and such have to be quite responsive. So that user experience piece is tremendous when we look at systems like these. So I think bringing these two kind of lessons together, we've been able to build credibility with our workforce, and we continue to layer on new pieces of information and capabilities with higher levels of confidence. Those are great examples. And I have one follow on question for you. And you've kind of described some of it already. But as an analyst, when we look at how different stuff happens at utilities, one of the things, particularly when you start talking about data and systems integration, is the ownership question. And how do you partner with the leadership? So in this case, a CIO maybe with the VP of operations and or engineering, right? So can you talk a little bit about what that looked like to make sure that you had the right executive sponsorship and you agreed on the goals and that sort of thing? What did that look like in terms of how you built that partnership? Yeah, I would say it is still we're still building it and it's a muscle that we're building across our organization. I think the implementation of this field services kind of optimization platform helped jumpstart a much needed focus on data governance and data quality. So we were able to use this as kind of a platform to start building what that that architecture looks like, what roles and responsibilities both between IT and our operations team need to look like to ensure we're equipping our field personnel with the most timely and accurate information. I think what we're going to see in the next years is building on some of this work to expand across the enterprise. Okay, yeah, great. And you addressed a lot of those those challenges that often come up early and often. So it'll be interesting to keep the dialogue on with you a year from now and see how it's looking. But thanks for getting us started. We're going to move to our second panelist, Brad Millam, who is the director of engineering and IT at Southeast Missouri Electric Co-op or CEMO. In his 17 years at CEMO, Brad has taken on a variety of technical leadership roles, including being instrumental in CEMO's expansion into the fiber optic business. Prior to joining CEMO, Brad was a field engineer at Craighead Electric Co-op. He holds a BS in civil and electrical engineering from Arkansas State University. He's completed the executive program at the University of Wisconsin's Robert I. Kabat School of Business. Brad, thank you for joining us. CEMO is a really interesting utility. I love the fact that you all made a very probably difficult decision to start, but then very aggressively went into the fiber business to better serve your customers there in a rural community. And I've gotten to know some of your team a little bit over the years and you guys are doing some really neat stuff. So thank you for joining us. We're glad to have you here today. I do want to start by asking you a little bit about your field force there at CEMO. I think your landscape is fair to say in terms of technology is a little different than what they have at say Portland General Electric. But you face a lot of the same challenges. So I want to start with you and talk a little bit about the workforce. In the preparation for today's session, we've talked a little bit about some of the challenges there. So can you just talk a little bit about what you all have encountered in terms of maybe getting your field force to do things more effectively or efficiently? Maybe it's maybe it is the digital side of it, the technology side of it. And I think also buried in there is maybe as the new a new generation of workforce comes into the mainstream, maybe part of what's happening there. So just give us a little flavor of what that looks like in terms of the challenges there and how you are looking to move forward. Sure. Thanks, Mike. Yeah, as Mike mentioned, we are a small electric co-op. We are a little over 16,000 electric meters recently connected over 12,000. So we hit our 12,000 broadband subscribers. So a lot of changes over the last few years with the addition of fiber broadband and definitely brought on some some technology challenges. We had rolled out quite a bit of mobile apps and things like that over the last few years. But with with broadband, we had to make some aggressive changes and and they continue to this day. Really? A lot of those. I would say it's with our partnerships being a small co-op or resources are limited. So a lot of the partnerships that we've developed over the years, some some of them long term, you know, 25, 30 plus years and some not so not so long term. So just bringing out what we can and partnering with with solutions managers and things like that. You know, used to we would have to hard code quite a bit of things. And now with the use of APIs and things like that, it brings a lot of that back together. But from a 10,000 foot view, I would say just having awareness of all the different systems and solutions and the department. You can have one thing over here and make that better. You make something else worse somewhere else. And like Vijay discussed earlier, if if you put bad data in, you're going to get bad data out. So managing that also managing expectations of all the departments and and making sure that you build the workflows to where they benefit everyone. You're not making someone's daily job harder. The whole point of technology is to make it easier. And that kind of gets down into the thousand foot view. Being flexible, being teachable. You know, being smart about the decisions that you're making. Communication with the other departments, just having all that wrapped into one. It you can you can really make friends or enemies. So it's a it's a whole part of the whole part of the game here. You know, and the corollary to that is, and by the way, you hit on a lot of things, everything from partnerships to workflows to the for the need for both leadership and the workforce to be flexible. And of course, communicating and coordinating with other departments. Utilities are doing starting to do a very good job of breaking down those organizational and technology barriers that have been pretty firm in place for some cases decades. So that's a big piece of that. I did want to talk to you just for a second about your workforce as that has changed. You know, I'm old. I'm 61. So my generation is still, you know, we're not resistant to technology, but we didn't grow up with that. We didn't grow up with it in our hands. Right. Whereas now you probably have linemen and electricians and different technicians coming on board in their 20s where they literally grew up with technology in their hands. So are you seeing a difference there in terms of maybe ease of use, ease of integration, acceptance? Are you seeing a shift there? And is that going to help you all as you move forward? Well, you mentioned, I think you were willing to, you know, buy in on the technology. Absolutely. We've got some folks here that want more and more and more. We've got some that say, okay, this is enough. Let me process this. And then over time with that buy in, you get more and more items off the list. You know, just over the last month, even this morning had a discussion over fuel tickets. So just the technology to get the information from getting fuel from the truck to the accounting department. It doesn't seem like it should be an issue, but, you know, just trying to streamline things and not have the guys take an extra five minutes of their time while they're filling their truck up to be able to get the information to where it needs to be. But, yes, you know, we have a pretty wide range, age range here. And I've got guys that are near retirement that are doing, you know, doing work on iPads that just three years ago took about four pieces of paper and a week to process this. So I think it's wonderful. And if you show value, they'll show you the work. Right. Right. Okay, great. All right. Well, thank you, Brad. We are going to move from a small rural electric co-op to one of the big federal power administration groups and Christine Budd. So, Christine, thank you for joining us. And I'll tell our group here a little bit about your background, Christine. You are the IT supervisor for maintenance and security support at Western Area Power Administration, WAPA. Christine's been at WAPA for eight years and she manages a team of IT professionals supporting the maintenance and security crews. Prior to WAPA, she worked in the localization industry managing global client accounts and project management teams. She has a background in IT systems, project management and global delivery services in her free time. Do you have free time at WAPA? Wow. Okay. All right. There you go. She enjoys gardening, going to the beach and trips to Disney with her children and family. That's awesome. So thank you for joining us today. And I've learned a little bit about what you all are doing in our run up to today. And your background is on the IT side of the house, but you work very closely with those field crews in engineering and operations. So maybe just start off, tell us a little bit about the work that you're doing here because part of that, I think, is the work itself, of course, but also the data that is being generated, how it's being used. And then we can talk a little bit about the traction you're getting with your field crews, similar to what we talked about with Brad from SEMO. So maybe just start, tell us a little bit about your implementation. Where is it? Because I know it does scale pretty big and there's probably some really neat opportunities there, but some challenges as well. So maybe just give us a little story there. Yeah, certainly. Thanks, Mike. Just as a clarification and caveat, all opinions are my own and are not representative as well, but as a whole or the federal government. But thank you for having me. So I work really close with my team and our maintenance crews. So that's going to be our linemen, our field crews, the foremen, the electricians. They go out in the field and they handle all of this. And we've got a couple of different perspectives you asked about here. One is, you know, the data and how's it being used and that technology traction. We have been using technology systems for our inspection and survey programs, line patrol, as our crews call them. For, you know, over 10 years, we recently moved to IQ Geo, which has been a new system for us. And part of the reason for doing that was for economies of scale. We needed a product that really was growing with the future and could help us better analyze the data and had better data controls. So the data that we get from the fields in our field crews are being used for making budgeting decisions. They're being used for making decisions on forecasting, not just individual pole and structure and line replacements, but even just something as simple as a cross arm individual components of the transmission poles and the structures that are out in the field. So the data that we're collecting helps us do budgeting, forecasting for cost, work efforts. How long is it going to take us to do these types of projects? Do we need to create a big project for this? Is this something that we have smaller tasks for? And then it also goes for helping us support our biggest goal, which is do what is right, do what is safe. And what we mean by that is how are we making sure our grid is safe, not just for alignment, but for our customers, protecting our assets, making sure that they're not going to go down or doing everything we can to prevent them from going down, whether it be as a result of vegetation or as a, you know, parts that have degradated over time and between like weather and other things that will impact our grid and our structures. So that's kind of like where that data goes. And one thing that it's shown us is that we have data gaps. And when we first moved into IQ.GO from our prior platform, we had all of this list of items that we were checking on our polls and our structures. And, you know, we spent a year getting into, okay, here's what we have. And then we've spent time looking over what we had and said, how can we make this better? And we've found points where we, where we've identified that we need some better data collection that we'll be implementing into our inspection and survey program here at WAPA. So it's, it's really helped us to see what we have and visualize where we need to go in the future with being able to maintain these assets, prove that we're maintaining these assets, meeting compliance and regulatory requirements that, and inspecting them and surveying them and patrolling them. So that's where a lot of that data goes. And then traction with the crews kind of like Vijay said, when we started this project, before we even spoke to any vendors, we pulled probably 5% of our line crews. We pulled someone from every region and in many cases, it was two people from every region were located over, we provide service over 15 states. So it was really indicative and really useful for us to make sure that we had our line crews up front. And the first thing that we did is, what do you not like about what you have now and how would you make it better? So when we went to go with IQgeo, we reviewed many, many different systems. And IQgeo was the one that could, could best fit with us. And like Brad, a lot of them did not want to change technologies. These guys, they, they're in their ways, but by including them in that process, we didn't have the type of pushback because they made the decision to switch. It wasn't IT coming back and saying, Hey, we're switching you. So we facilitated that conversation and helped them come to that realization on their own. So, so we've always had a lot of good buy-in. Yeah. I think having that seat at the table and having that voice gets, gets you a lot of mileage, particularly as you go deeper into the project. So I love that. Do what is right. Do what is safe. Um, you also talked about data gaps. And also I was going to ask you about scale, but 15 States, and I'm sure it's countless thousands of miles of transmission lines or maybe, you know, uh, more than 17,000 miles of transmission. There we go. There we go. Yeah. That's no small feat. Um, one thought that occurs to me that I wanted to ask you about, as you were describing that is standardization, because you have all the different resources. Right. So as part of the effort also in terms of addressing data gaps and data quality and just business process was standardization. One of the goals there so that people were doing the same from region to region. So the quality of the data improves the, the efficiency and effectiveness improves. It was that part of the move forward. So, um, about five to seven years before we moved to IQ geo, a, an initiative had taken place to bring WAPA out of the paper age and into the electronic age. So we did have some, we had a lot of standardization already built in. Um, so we didn't have to focus a whole lot about that. Um, there are some areas where we are working to improve standardization. Um, and we actually built a little bit of flexibility in our, um, deployment of our current system to account for those variations. Um, we did quality controls that we had upper and lower limits on what would be considered, you know, acceptable for certain ratings. And if someone wanted to go outside of that because of their regional reasons, sometimes things grow faster in Arizona than they do in North Dakota. Um, as an example, so something, something that might not be a fire risk for 10 or 15 years in North Dakota might be a fire risk within one or two years in Arizona. So we built some flexibility into our quality controls. So if someone needed to go outside that standard bounds, they could explain why. And when it comes up in a future audit, we have all of that documentation right there. And it's not just someone pulling something out of a hat, like, oh, this was bad, but no, really, it's actually not bad. Here's the note and here's the reason why it was done that way. So it's, we forced them better. We're getting more information out of the data that we get in, especially instances where it can't be perfectly standardized. Okay. Okay. Well, good. You're, you're managing, uh, quite a, quite a scope of work there. So, uh, thanks for your opening remarks. We're going to come back to you in just a little bit, but we also want to introduce our fourth panelist. Uh, Matt Roberts is batting cleanup for us today. He is the, a utilities director at IQgeo. His career has spent, has been spent within the utility industry, focusing on solutions like we're all familiar with, like SCADA and ADMS and asset management and intelligence systems. He's based in Atlanta, uh, where his expertise is instrumental in driving the business development of IQgeo's utility solutions across North America. His expertise has proven to be invaluable in helping utilities optimize their operations and enhance their overall efficiency. And that's a big topic for us today is around the efficiency. So, um, Matt, welcome. Thanks for joining us. I'll just, you know, one of the things that's, that's great about this panel is we not only have those three examples from three very different utilities, but also your experience in looking at and working with, I would imagine, dozens of utilities. So you can kind of compare notes on some of the different experiences. So on that, um, with those different experiences and your perspective from working with all these folks, um, where are you seeing those wins in the field? And we got a little bit of a sense of that from our opening remarks from our other panelists, but, uh, is it, uh, getting traction with the technology? Is it leveraging data more effectively? Is it about interfacing? Is it creating efficiencies? And of course there's probably a technology and data piece and a people in process piece. So it's a very big open-ended question to, to get you started, but you know, what are those wins that you're seeing and maybe a little bit of the backstory behind that? Mike, I appreciate the kind introduction and I, you know, similar to you, Mike, I consider myself the lucky one here, considering, you know, my, my job is almost a panel of being able to talk to different utility executives, uh, weekend and week out. But, you know, when I'm speaking with these folks and really, regardless of the size of the utility, some of the big common wins that just live throughout are one of the biggest ones is, is closing that field to office gap. Uh, Brad mentioned it earlier of, you know, what can I do or what can the, the field personnel, the linemen do, uh, that, that goes on and helps the accounting department. Those two extra, you know, two extra field entries, two extra button clicks that helps out another, uh, another department. And, you know, I'll, I'll, I'll be honest. A lot of times when we say that the, the line guys go, ah, you know, I really don't want to spend the extra three minutes, fill it in that data. Right. But they, you, you start to win when, you know, they filled in a data correction and that next morning, that data corrections there, they're starting to see that their, their inputs are being accounted for. And it's showing up in, in, in the software itself. And, you know, I kind of on the note about the data itself is we're seeing wins on data quality over data quantity. So if we think about, oh, 10 years ago, 15 years ago, uh, all the utilities were buying, you know, implementing all sorts of different BI systems and saying, well, we've got the data. We just don't know what to do with it. Right. And we've, you know, we've turned out to realize that even if you've got the data, if the data's incorrect, and even if just one of those 10 data sets are incorrect, the field doesn't trust it. So a big win is putting the correct field data collection, you know, kind of technologies into those folks' hands to where they know that they're inputting the correct data. And when they come back and view it one, two, five years later, it's that single source of truth that they can rely on. They can run the trace on and trust the results. And I think what I'm starting to see more and more is kind of field efficiencies across different types of work. So many utilities still, still to this day, we've got, you know, if you think about an asset, an asset goes through a design, it goes through construction, it goes through an operation maintenance cycle. And then lastly, you know, it, it runs till failure goes out during an outage. For the field team, that set of work, that could be 10 different mobile tools that the utility is in the line guys are interacting with each and every day. Right. And where we're starting to see some gains is in measurable gains is when they start to, you know, realize that, oh, you know, I've got these 10 different types of work, but I'm working from a common interface. I'm working from the same tool that I used to do my as built as now I'm, you know, up in the helicopter doing my inspection. It's, it's not a new face that I've got to learn. It's not a lot of change management. It's just different work at hand. Right. Yeah, that's, that's a big development over time. And the seamlessness of being able to do something like that is, is, I was going to say it's immeasurable, but it probably is measurable in terms of how folks used to do stuff and how they do it. Going forward. One follow up with you is those are some great field examples. I found interesting that when Christine was making her opening remarks, she started with budgeting and forecasting. And I think when we think about field crew automation and intelligence in the field and that whole world, we may not run to budgeting and forecasting right away. But obviously that's an important piece of that. Are you seeing when you're out meeting with different utility leaders, are you seeing that they're recognizing the value of not only that field piece, but what we'll call the back office piece and that seamless integration there? 100%. 100%. So it's, and that's the, the office is the input of the office is from the field. So having the ability to, you know, look and see that this transformer has had, you know, 10, 15 different maintenance requests against it and being able to go into a CapEx meeting and say, Hey guys, we've, we've got the data to support that. You know, this manufacturer or this specific asset is, you know, we need to plan for its replacement. So being able to really use those field insights, correlate them to the asset and, you know, for better or for worse, have an eyes wide open look at what assets need to change, need to be upgraded, need to be reinforced, you know, in the next six months, three years, five years, look ahead. So we can, we can get into the budgets. Right. And as you described that, you're getting dangerously close to me asking you about AI. Because I think that's going to be part of what that looks like going forward. But I want to hold off on that just a little bit right now, because I think there's some interesting stuff we're going to hit on there. So thanks for your opening remarks, Mac. That was great. Vijay. I want to come back to you. It definitely has some renewable energy and clean energy goals. I did look into this a little bit just to summarize by 2030, 80% reduction in greenhouse gas emissions from power served to customers. By 2040, zero greenhouse gas emissions from power served to customers. So going from 80% reduction to zero in 10 years over the next 15 years. And then also by 2040, net zero greenhouse gas emissions across company operations. So this is where you get into the scope one, scope two, scope three emissions. And as you get further in scope, it gets a little harder and trickier. So those are regressive goals. But the thing that's always to me when I look at goals like that, I think those are interesting and compelling and important. But to me, in the back of my mind, there's always a little, and by the way, we need to keep reliability and rates the way they are. So particularly on the reliability side, because I think that's where we can have a more immediate impact in our discussion today. What are some things that you see in that shifting landscape driven by this energy transition? How does that factor into how you're leveraging geospatial technology and doing network management? Because those are all things that are changing the very grid that you're working on. So how are you using those systems and processes and technologies to keep the reliability up while still being part of that energy transition? What does that look like? Yeah. Thanks for the question there, Mike. You know, let me start off by saying that our clean energy goals, these are not abstract aspirations. These are real goals and objectives that are fundamentally reshaping how we manage the grid. So from a tech standpoint, geospatial information network management, they're more critical than they've ever been for us to achieve these goals. So unpacking that a little bit as we bring on more renewables distributed generation and storage. You know, one can say the grid is no longer a one way delivery system. It's highly dynamic, which means that we need near real time visibility on how assets circuits and customers are connected and how these assets are performing. So leveraging these field system operations platforms, GIS information is key to providing us the ability to model, monitor and adapt to changes in that ecosystem very quickly. You know, from the planning side, I'd say that we're using geospatial analytics to identify where solar or EV adoption is accelerating and how that ties to upgrades to equipment. So reliability is never at risk. On the operation side, I think our crews are relying on accurate connectivity and asset information so that they can maintain safety while working in this evolving grid environment that may have bi-directional power flow. So it increases the, I call it the safety measures that we need to take as a utility managing this dynamic grid. Right. And then just one more point on that. So the integration of things like vegetation information, wildfire and weather information paired with this geospatial data is key for us to proactively manage any sort of climate driven risk as we go down this decarbonization journey. So let me pause there. It looks like you're going to ask a question. Yeah, I'm keeping some notes here. You know, you touched on one thing that is kind of a pet interest of mine. You mentioned planning. And, you know, the way that I've always looked at it is, you know, your IRP and your planning function historically, traditionally top down. We have this much generation. We have this many customers. We expect the load to grow so much. And I'm oversimplifying. But and here's our fork, our 10 year forecast. Right. Now, all of a sudden. You've got generation all over the place. Right. And EVs all over the place. So that top down approach doesn't necessarily work. You have to really look at bottom up. You know, this part of our service territory. We expect to have double EVs in the next 10 years. You know, I'm in here in Northern California. You can look to certain communities. Very high EV penetration. Berkeley, Davis, probably close to 50 percent. Other areas in the Central Valley, it's probably under 5 percent. So those sorts of things affect what that load forecast is going to look like over a 5, 10, 20 year period. Are you starting to see the planners working more with some of that distribution data that maybe you're seeing as part of that mix in terms of how they're going to how they're going to move forward with that? Yeah, I think in theory, just so I won't get into the details about that, but the answer is yes, you're going to have to look at things very differently moving forward here. You know, we spend a lot of time in the industry talking about things like the duck curve. Right. Everyone that's been in the industry knows about the duck curve. Oh, yeah. And now with the factors you just described, how does that shape actually look over a day, week, month, year period? And, you know, I'd venture to say that that duck curve, while it still might maintain a similar shape, I think it's slowly evolving. And things like electrification, the adoption of EV, the penetration of rooftop solar, customer driven, customer side driven resources are going to change the way we're able to react, respond and forecast demand on our system in ways that we probably never had to think about before. So in addition to everything we're speaking to, I think having robust information around low forecasting and maybe risk management and profiling type of tools, paired with the information we're speaking about today, will be key to really capturing what that future looks like. Yeah, it's all part of it. And boy, the richness of the data is going to be super, super critical. 100%. 100%. We do have a couple questions from the audience. So I'm going to open this up to the panel. So let me just fire away here. Given the current divisive trade and tariff landscape in North America, what are the primary challenges in energy sharing, pricing and operations within the continental power grid today? So I think it's a really big question that is kind of a very high level view of some of the things we're talking about today. But I think it will be interesting just to spend a few minutes on that in terms of how do you see this impacting for our three utility panels, your utilities specifically, and then, Matt, maybe some of the things you're observing, utilities you work with. So what are you all seeing with the divisive trade and tariff landscape? Very well stated, whoever wrote the question. Anybody want to jump in on that? I'll jump in, but it's not going to be an answer everyone loves. A lot of our grid modernization and like transformers, major components are years out on procurement cycles. So I don't know that we've actually seen how tariffs and trade are really going to impact that yet. And then, you know, WAPA being a federal entity, we have very particular requirements when we go to source. So we actually have a smaller pool that we can source from to begin with. And when we do our planning, we're planning five and 10 years out and sometimes 15 and 20 years out. We do very, very long forecasting. So what's happening today? It might have an impact. We haven't seen that directly yet. And I think that's still kind of more yet to come. But it is coming, I think. I think we can probably agree on that for sure. Vijay, I see you nodding. You experiencing similar things with Portland? Well, I guess in general, I think what Christine hit on is spot on. In addition to that, I remember over the course of the last nine to 12 months, there were, you know, discussions in the news around trade, you know, trade tariffs and such importing and exporting energy to and from the U.S. to neighboring countries. And being a Pacific Northwest utility and operating where we do that is something that, you know, caught caught my attention and others attention. Because let's face it, we operate in a market on the West Coast that's very, you know, as you mentioned, the EV penetration, the electrification is driving as well as data centers. It's driving a huge surge in demand for electricity. And at times the need to import or export power to adjacent systems is there. So as these discussions around trade as it relates to energy imports and exports develop, it's something we keep a close eye on because that fundamentally, I think, impacts our strategy around how we manage power costs. For an example. Changing times for sure. And these are big questions and big issues. I don't think we'll solve them today, but I think we got some good perspectives there. We do have another question from the audience. I'll just, and again, I'm going to ask this to the panel. Although, Matt, I may ask you to take the first swing at this one. It's an interesting conversation about data quality with entering data directly in the field. How do we do quality control? How do we, how do we quality control that, that being the data entered in the field? And have we created more work? So, Matt, maybe your experience working with different utilities and getting them to kind of absorb organically kind of that data entry piece in the field. And, you know, I think we've all heard and seen and experienced the stories. I'm here to fix this thing, not to be a data entry clerk, you know, but I think the more seamless you make it, the better. So what are you seeing and hearing your utilities about that? So I certainly resonate with agreeing with the last point of the last thing you want to do is create more work by introducing, you know, a new technology. And there's some real thoughtful ways around that introduction or eliminating that introduction new work. And I really think it lives on the, you know, the tailored experience that that field user is receiving at that point of data entry. And being able to let's let's pick on a data correction request, for instance, being able to say, you know what, that poll was not on this side of the street. It's on that side of the street, being able to simply mark that up, move that over. And Brad, you had mentioned, you know, APIs in your opening opening bit. But, you know, having the supporting technology to be able to just go, you know what, we're going to pick that change up at night. And that next day is going to, you know, it's going to appear in your mobile solution or whatever field solution you're using. And really try to take the human out of those data corrections that we as an organization are willing to just, you know, let pass through. Okay. What are some of the other experiences there relative to making sure you have that data quality capacity with the field crews really driving that now? So some of those other, you know, the validations would really be at the point of entry. Let's ensure that when we're putting that field data in that somebody doesn't on the Panasonic Toughbook, you know, hold zero down for 10 seconds and eliminate them from even inputting an incorrect bit. And really having a bit of call it first time right type automation to where the most, if not all the errors are taken away at the point of data entry. So you don't create more work by having, you know, the posters or somebody comb through this massive queue of work being like, oh, look at them. Another, another wrong KVA on a transformer better go correct this. Any anybody else have some thoughts on that around the data quality issues and, and particularly with an eye towards getting your field crews more participatory there? Yeah. Go ahead. Go ahead, Christine. So some of our consumers of data from the field had a lot of concerns when we migrated. So we actually worked with them and our field crews around quality controls that were built in to our newest solution. So data fields that are free form are limited to certain types of data. If I need a integer value, there is a, you know, a maximum and a minimum integer value that are allowed. And if it deviates from that, then it gives them an error. So these are things that seem kind of no brainer, but if you're working on the iPad or a computer in the field, it's super easy to fat finger, you know, a number and a letter when everything's right beside each other. So that's been probably one of our biggest gains is actually using the functions within our system to build data requirements into, and then into the fields. And also if the, if there's only three choices available, make it as a dropdown. Don't let them hand, hand key those things that, you know, really is just a yes, no, A, B, C, or D answer. Great. And Brad, I think you, you had something to add as well. You're muted. There you go. Sure. Can you hear me now? Yeah, gotcha. Good deal. Just to echo what Christine said. If you've got that data on a, on an iPad and you're out in the field, it, you may fat finger, you know, a meter number or a transformer number, or, you know, a pole number. So lots of things can happen. We've, we've had instances where our guys went to a duplex. They changed out both meters to, you know, a new type of AMI meter and they got transposed and it took a month or two to figure that out. And, you know, you, you don't have, your membership or your, your consumers will, will question your, your accuracy on, on everything. If, if you can't figure out, you know, which meter goes where. And so that's, that's been a big concern. We've had two AMI rollouts over the last 20 years. And, you know, it, it was the same then as it is now. It's just now we can actually make the change in the system from the field instead of, you know, a day or two later through, you know, through a non automated process. So just having the accuracy, the time that it takes to, to, you know, make sure what you're putting into the iPad is, is what's actually out there. I would also like to say it's, it's kind of like a balloon effect. So if, if you fix something over here, you're, you're going to push the balloon out somewhere else. And it, it never ceases to fail. And it's not just, you know, with, with this technology, it's with any process that, that you try to streamline or, or work through. So, or implement. Right. Right. Very good. We do have a few more questions coming in from our audience. So I would like to dive into a couple of these. And I will ask the panel. So this is an interesting one, particularly for some of us who've been around GIS and the field automation space for a long time. What is the delay average in terms of updating information between the real maintenance action in the field and the completed report that is actually, you know, the data piece? How has this been impacting responses and analysis for making decisions? And as I keep an eye on the clock, Vijay, I'm going to ask if you want to take a swing at this before you have to jump off. So that delay from the work is done and it's documented in a digital format and usable for all these different things that we've been talking about today. Yeah, I was actually just typing a note saying it's time for me to drop off here. So for us, we're trying to do things as close to real time as possible. We're not there yet. Right. But today we have integrations and such that run very frequently. So I would say the delay is not it's not too lengthy. So I would say intraday within maybe one one hour, maybe maybe a little longer than that. But we're trying to push things as quickly as possible. And we are re-architecting some of this so that we're more we're more near real time. So that's kind of the next step in maturity for us, because to the point, timely information is is what folks are looking for. And it just helps continue to build confidence in the information they're using to make very important decisions. Yeah. And and I think I'm looking back at my notes from some of your earlier comments. One of the things that impacts is safety. And and I think that that's, of course, at the at the forefront of most utilities operationally and their mission. And so this real time isn't just a nice to have. There's some actual very real world implications safety being at or near the top of that list, I think. So that's a that's a big one. I do want to open this question up around that delay. Delay is the term that was used here from the work being performed to it being fully reported, recorded and usable for all these different use cases. So does anyone else have anything to share? And by the way, Vijay, thank you so much for joining us. We will be sure to follow up with you and glad you were able to sit in with us today. Thank you for having me. Have a good day. Very good. Take care. So who else has some experiences they can share around that that real to near real time goal of field data? Ours here at WAPA is very near to real time as well. With our with our geography and how far spread apart we are, we do have a lot of instances where field crews are fully offline and disconnected. But in terms of the work that's being performed, anything that's actually in a connected state and has an active data connection, that information and data is relayed and shared within 30 minutes of being uploaded. Wow. OK, so when when we have live syncs, data updates, push out, we have them push out twice an hour. And so if it's a manual update, because a lot of times they're in less connected zones and they'll just manually choose to sync and push that data, then, you know, it'll be within half an hour of of when they push that back. So is. Which is a little bit of a conundrum. Yeah. So what is that? So, you know, you have a crew out in a line somewhere in North Dakota, right? And they're doing the work. So do they just. What does that look like in terms of execution? Getting it into the system. It's their work is so seamless. You know, they literally they drive up to our structures and our IQ Geo system pops up the structure for them. They know exactly what they're looking at. They're looking to see if there's any changes from what they reported last year. And if they are, if there are, they'll update it right there on the page and then submit it and then move on. If they're. If it's the same, they just look at it and be like, okay, I'm moving on. They'll just submit it and move on in a live connected environment that information sends up right away. If they don't have data services at that point because they're in the middle of nowhere, then when they do have that data service connection, there is this tiny little arrow at the top and at the bottom for them to sync. They press it, they go on their way. They don't even have to do anything else. Oh wow. And it'll be available for. In y'all the in office recipients have access to it right away. Anyone who's offline. It's 30 minutes later. They'll have access to it. We're within 30 minutes. Okay, great, great. We're getting more coming in from the audience. This is awesome. Do either of you want to speak to this current question a little bit more and you know, Brad, you have a. You have a team there. Matt, you have the benefit of looking at a lot of different utilities. Again, that delay. What's your experience been there? Good or bad? Matt doesn't have anything. I would say kind of like Christine said. The office personnel will have quite a bit more data than than the field and they'll have it quicker. However, if we do have an offer, you know, an outage going and operations is manning dispatch. Usually any changes that we make back feeds, things like that. Able to turn on certain sections of the line. Those will reflect out in the field for the outage map pretty much within minutes. Would it be better if we could affect those changes from the field? And, you know, so then you get into are they out there to repair the line? Are they out there to make the outage map look better? So that's kind of what we we struggle with here. I'm sure many other places across the country as well. So earlier I mentioned meter exchanges. So if those are done from from an iPad, those pretty much immediately go into the system and you can see that change. However, on similar and we could make it happen if we change a transformer. A transformer usually takes some some paper trail to make happen and probably not going to be into the system for about a week, two or three days to a week. So we've kind of got a mix of mix of those. Okay. Okay, good. I am going to jump to the next question here. And I think you all may have have an opinion or an experience to share on this. How are your utilities using GIS for substation preventive maintenance inspections and corrective maintenance? So where does GIS fit into that world within the substation fence? Do you all have any experiences to share there? We use some other systems connected with our GIS system as well. And our GIS system, it literally houses all of our transmission lines, our substations, every facility that's associated with WAPA. Not uncommon. And we it does integrate with both our IQ Geo implementation as well as other data services that we use for preventative maintenance and corrective maintenance. Right now we don't have those in our IQ Geo instance. But the tools that we do have for that, you know, connect to our asset management systems. And the systems that are being utilized for, you know, building work orders on things that need to be replaced, work that needs to take place within the substation itself. And then in regards to how we're using IQ Geo, GIS is we wouldn't have IQ Geo if we didn't have GIS because we'd have to manually map out where everything is. Right. That's no fun. Matt, how about you? What are you seeing and hearing from the utilities that you all are working with around substations? Where does that touch what you all are doing? On a lot of the inside the fence assets, what we're seeing is, and we're really being the recipient of a lot of new systems. So a lot of EAM systems are implementing asset performance management systems on top where, you know, there's some predictive maintenance and capabilities within that. And where IQ Geo and where I'm seeing seeing us fit in and have fit in is being the recipient of that. You know, we need to go look at this circuit breaker and similar to what Christine said about the transmission inspection or the transmission structures, you know, being able to have your work served up to you, the correct work. While you're standing in front of that asset that maybe your APM system said, all right, well, we need to, you know, check oil levels, review the windings, things like that. All right. Okay. All right. You know, Brad, while we're with you, I'm sorry, Matt, while we're with you, you know, we're talking about maintenance and predictive maintenance and we're edging closer to where AI is going to be very impactful in that space. So I think it's a fascinating topic. I see the applications on the customer side and the operations side. But when you start talking about some of the maintenance things, you know, some really interesting work being done there in terms of being able to model transformers, for instance, and how you can be a little more predictive with them. So how do you see this being applied for the work that you see utility field workers doing? And are there maybe some quick wins that they can be achieving given that they've got a lot of data? And of course, that's what feeds AI. So are there some things that you all are seeing? And I know you all have some new things going on in the AI space. So maybe you can just share a little bit about what that looks like, particularly again, that field side of things being working more intelligently, more predictively. A hundred percent. So one of the big areas that we see is on image recognition for inspection as a whole. So, you know, currently a lot of utilities are relying on folks eyes. They're relying on drones. And then that video and photo data goes and it's reviewed, you know, somewhere else. Where I see a tremendous amount of impact is, you know, still have those same data collection technologies, but have the AI be plugged in right there to where, you know, what was taking me, I don't know, 10 hours to review, you know, 5,000 photos I'm doing in minutes. And, you know, even taking it a step further from that and applying that AI, not only to, you know, visually recognize, all right, hey, this cross arms cracked, we need to replace it, but then have a prescriptive nature to it to look at the overall structure and say, oh, well, we need to replace it with this. And when we referenced your standards on cross arms for this type of pull, I'm immediately going to help out the designer at that next stage and apply the AI that bit. And I think one of the last bits I want to talk about on the AI is where I'm seeing more of a cultural AI being we've got a number of journeyman linemen who are going to be retiring out of the workforce here shortly. And there's a number of apprentices. And those journeyman linemen and those folks that have been at the utility for the last 30 years, it's unbelievably difficult to teach or for them to sit down over lunch or sit down, you know, over sit down over lunch or over a meal and then to explain everything they know of when they look up at the pole and see that porcelain insulator that they installed 30 years ago. They can not, well, you know, that's actually a defunct porcelain insulator. And I know that because the skirt, you know, the bevel of it goes this way, but being able to use AI to work with those senior linemen, get all of their know-how and use computer vision AI to help out those apprentice linemen to be able to, you know, take a photo of that insulator and the AI is already trained. Based off of, you know, what somebody had spent 40 years doing, but is now retired, but it feels almost as if they're still looking over the shoulder because they've got the knowledge of that line guy within the technology they're using. Right. Yeah. And I think as an industry, we're on that path. We can certainly see there's a lot of interesting work with drones doing line inspections or even vegetation management, recognizing species and things like that. But to bring it back a little bit, moving towards having that trained model capability is going to enable a lot of that. And that takes time. But I think we're definitely on the path there. Brad and Christine, while we're talking about AI, before we move on, are you all either working with this today or are you looking at areas where it could be impactful for you all in the future? We are not presently working with AI on our fields, but it is something that we have been parts of conversations with off and on for about seven years. Brad and Christine, when we first started having the conversations, the just the man hours required to even consider training on the thousands of different things that could could be an issue was just not a task that we could take on on our own or even in partnership with some of the with some of the research facilities. It's not something that's abandoned. It's a conversation that as technology has evolved is starting. Looks like she froze mic. Okay. Yeah, I wasn't sure if it was on my end or on her and Christine, I think you froze. Are you back with us? Okay. So Brad, I want to jump over to you and I actually have a question I've been holding here. I want to ask you before we get to some of the next one. It looks like Christine is back. So Christine, I think we lost you there for about 30 seconds, but I think you're back. I think you're back. You with us. I saw our movement. Okay. So Brad, let me let me ask you a little bit about starting with AI and just a broader technology question. Where do you see technology having an impact for someone like a small rural co-op like CMO in terms of you being able to not just continue to deliver on your mission, which I'm assuming has reliability and rate stability and safety and affordability all built into that mission. But how can you continue to deliver on that even more effectively, more efficiently? And what is the technology piece there, be it AI or some other things that you all are looking at? Mike, speaking about AI, I would say we have two of our core systems that are moving to AI products or platforms. Some are even projecting Q4 this year. I would say what we have seen, the first part is going to be data mining and reporting. I think that's going to be the main focus for now. There's also going to be that part of its learning data as it's mining the data. So the possibilities are going to open back up and probably be as unlimited as we're able to allow it to be. I guess I would say it's going to be it's going to be that part to where the human is going to have to. Be OK with with what it is, the information that is given back. Yeah, I think we're so used to, I think, as people and as an industry, well, going with a gut maybe or being intuitive. And I think being more along the lines of data driven decision making, I think, is where we're pointed. Well, what's interesting is, you know, you're you're you're you're a small rural co -op and AI obviously scales in both directions. Southeast Missouri Electric Co-op is using AI now to improve their efficiency and operations. So I think that's that's a big lesson learned. The broader question, where else are you seeing this tech not AI or just technology kind of moving you all forward, particularly with those field crews and the work that you're doing? I know you all have your share of storms going through there because I've heard some of the stories and seen some of the pictures. So where's technology impacting that? Quite a bit. I mean, so one of the meetings that we we've had several times is is FEMA. We've had several FEMA level events this year, last year and even the prior year. And there's a whole lot of invoices and timesheets, all these things that if you could get them into one data set or link all these data sets together and have AI pull out the information that's needed. Because the list of questions coming from the from FEMA and the state level is is unrelenting. And there's a lot of data to go through to be able to get that. And I think I would be able to help us answer some of those questions faster than several sets of ideas going through stacks of paperwork. Right. Right. And a lot of that has a significant financial component to it. Right. When you're talking about FEMA and state agencies. So, yeah, that's that's that's that's not lost. We're already into the multiple millions of dollars just for 2025. OK. All right. And that won't change. That won't go away. It's always going to be there. So I do want to jump back to Christine, who's back with us. I think we lost you there for a minute, but I see you moving. So it's actually you. So I had a question I wanted to ask you and then we're going to have a couple quick wrap up questions with the panel. Your IQ geo implementation is is it a pretty large scale as you've talked a little about your service Terry across service territory across 15 states. What are some of the next steps in the journey? You've established it. You're doing great work with it. Are there things you're looking at as you go forward? Well, now that we're stable, the crews are using it. Here's three more capabilities we want to incorporate into what we're doing. What does that look like? Yeah. So we have a multifaceted aspect for managing what that infrastructure environment looks like. We have maintaining the technology piece, the cybersecurity vulnerabilities. So we part of us is we want to stay current with what is actively being maintained and supported by IQ geo. So that's kind of one one aspect of it. And we're actually going through a project right now where we are update upgrading from earlier versions of IQ geo to the newest version of IQ geo. And that'll that's been a project that we've been working on for almost a year now. So we'll be super excited once that wraps up here within the next couple of months. But we also have regular touches with our linemen and our field crews. I have a number of folks on my team who actively go out with the field crews. They'll go out with them for inspections. Sometimes they'll go out with them on the helicopters. They get to do all the fun stuff. And part of that is that we meet with our crews regularly to hear out. What do they not like? What could be better? And what is their wish list? And we take that and we prioritize between budget and the various projects that are going on and our team allocated resources to, you know, set up a plan for, okay, when are we going to implement this? And there are some items that get tabled. So, you know, one thing that our crews have been really looking forward to is being able to bulk update assets when they go out and perform maintenance on a line. And that is actually a feature that we're going to be getting with this upgrade. So rather than having that customized for us, we decided to hold off on that. But we're also looking at things like how does our IQ Geo integration correlate with our ESRI planning? So we're coordinating IQ Geo with when we update ESRI, you know, making sure that our technologies will still be compatible with one another and, you know, planning and forecasting and budgeting for that. And then what other uses do we have within WAPA? Some use IQ Geo more than others. But one of our big goals over the next year is to onboard our vegetation groups so that they have the ability to go out to the field and provide their vegetative updates. So our alignment will do inspections on the poles. They'll do vegetation inspections as well and include that with theirs. But some of our regions have their own vegetative specialists that they'll send out to do inspection. So we're looking to onboard them in a way that won't be impactful to our transmission structure inspection program. So that's kind of a big goal that we have over the next year. And then we're always looking at how technology is changing. You know, I know that IQ Geo is looking to have ties in with more AI over the future. And that's definitely something that is in the government strategy. So we'll be looking to see if that's something that fits within WAPA strategy and how do we get that to talk with what we're doing out in the field and our drone program. And, you know, that that central pillar of technology and how can we support these and get the true data drive from that. That's a lot. It really is. I'm happy to hear that the crews that are doing veg management are also doing asset inspections. I think you can get some real economies of scale there. So I think that's pretty interesting. I'm keeping an eye on the clock as we get close to the end of our little get together here today. I did want to ask each of you a question and I'm just going to go across the panel starting with you, Brad. So I'm going to you're going to be CEO for a day, maybe COO for a day. And you know that you have a great you have great field crews, great leaders, but they need to be more effective and more efficient. So what is that thing that you would do if you were in that seat? You know, maybe it's one or two things. You know, I look at the world sometimes through the lenses of technology data and people in process. So is it is it is it somewhere in that realm or what does that look like? You know, you're putting your slamming your fist on the table. These are the things that we're going to do to improve our field crew effectiveness. You're the COO. What do you what do you got? First thing I would do is is ask ask the crews their pain points and then just go after that low hanging fruit. Pick them off one by one as we can. Most effective, you know, most efficient way possible. OK, how about incorporating technology into that? You're identifying pain points. You're probably going to have different technology initiatives that are incorporated with their work processes. How would you go about that to make sure that in two years we're going to be at or near real time on all of our field data? Go after the partners, say, you know, speak with many of the industry partners that are out there, not just one. Also talk with our folks in house. They have a strong background in making systems work and they have done an excellent job doing that. And I've got full trust in them. So go at it. Multi faceted, you know, in house partnerships and just making the technology work and not not hinder. Right. And not doing technology for technology's sake, I'm sure. Yeah. Aligning it with with those pain points and that low hanging fruit. Great. OK, now we're going to jump over to WAPA and those 15 states. And you're responsible for operations for 15 states at WAPA. Christine, what are those things you're going to do to make those field crews more effective and efficient? You know, like like Brad said, we're we're looking for what are those pain points we meet. I'm going to meet with them. What's making them inefficient? I'm going to see what what gaps there are. And, you know, in the instance of technology, that's one thing that we have been able to help with. You know, sometimes it's a matter of I don't want to click three different buttons. I want to click to how how can we how can I reduce my time doing this when nothing has changed? That right there is probably, you know, one of the biggest points of any efficiency is there is nothing to do here because everything looks good. And yet I have to spend X amount of time saying that everything looks good. So, you know, making those AOK instances easier to document for them. And then for the items and the issues that do exist, you know, for for the linemen, inspections aren't their favorite thing to do. They do it because it helps keep them safe, our customers safe and protects the assets, help keeps the grid running. You know, they they really want to be out there doing the other work, you know, installations, maintenance and everything else. So helping them to where they can more easily do the work that they really enjoy is is also a goal. Yeah. And it'll make them ultimately more effective, too. If you streamline some of those more mundane tasks, they can they can tackle the bigger challenges. That's great. All right, Matt, you're going to wrap it up for us here. You're COO of a utility. You need to make your field crews more effective and efficient. What are you going to do? I think the big thing, Mike, is we've just got to to start the legacy systems in the paper. They're so comfortable because we know them. But we've got to start. And I think and I echo what Christine and Brad said and what Vijay said earlier. We've got to start with a small group of field users that we're going to put in charge. We're going to let them dictate and most importantly, have a bit of those field users that garner the respect of their peers. So when they see them really excited about the technology that's being implemented and the changes that are coming, that the folks around them start to hear about. It starts to get a reverberation and you get this. I think I'm going to steal this from from Vijay, but the momentum and the earning of the technology adoption to where when you come six weeks later and say, hey, we helped out with meter swap outs. Now we're moving to inspections that everybody's happy and eager to to be part of that. And they're honestly what we've seen is they're they're they're fighting over. All right. Well, I want to be in that next focus group that gets to define what the inspections look like and really kind of build this groundswell of innovation and belief that everybody's in the driver's seat. It's starting with those line and those field teams as number one. Yeah, thank you, Matt. Matt and thank you to our panel. It's interesting. We're talking a lot about technology. Boy, boy, the people in process side. That's just so, so important. But I do want to thank our panel. I'll thank Vijay. I'll get back to him. I want to thank our audience for joining us. I want to thank IQ Geo. This has been great. I really appreciate it. And I'm going to hand it back over to PJ to wrap us up. Thanks, Mike. Thanks, panel. This is a fantastic conversation for our audience. Please look for an email containing a link to the replay. And please take a moment to complete our survey at the end of the session. Your feedback is greatly appreciated. For everyone here at Energy Central, thank you for joining us. This concludes today's Energy Central Powers session.