On this special episode of the Futurum Tech Podcast – Interview Series I am joined by Jennifer Baldwin, Utilities NA Industry Executive Advisor for SAP Industries and Mark Davis, Director, Enterprise Data Management Solutions at Intel. This is the sixth episode in a new series — done in partnership with SAP and Intel — where I will be speaking with advisors and executives across seven different industries on the state of their industry and how SAP Industry Cloud powered by Intel technology plays a vital role in the future.
The Future of the Utilities Industry
In our conversation we discussed the following:
- A recap of the last year in the industry including how COVID has impacted key trends
- Challenges that utilities organizations are facing with their assets
- How organizations are using technologies like AI and machine learning
- How SAP and Intel are working together to help these organizations continue to advance
The Utilities Industry, like many other industries, had to rapidly accelerate digital transformation last year. My conversation with Jennifer and Mark explores these changes and a little bit more. It’s definitely one you don’t want to miss.
If you’d like to learn more about the industry cloud and the Intelligent Enterprise strategy, be sure to check out our research brief: How Utilities Can Better Meet Customer Demands and Industry Challenges and Stay Abreast of the Competition by Focusing on Proactive, Data Driven Business Models.
Listen to my interview with Jennifer and Mark on your favorite streaming platform here:
Disclaimer: The Futurum Tech Webcast is for information and entertainment purposes only. Over the course of this podcast, we may talk about companies that are publicly traded and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors and we do not ask that you treat us as such.
Transcript:
Daniel Newman: Welcome, everybody to the Futurum Tech Podcast, the Interview Series. I’m Daniel Newman, principal analyst, and founding partner at Futurum Research and your host today. Very excited about this interview series. It’s the continuation of our SAP and Intel Industry Cloud Podcasts. This is the seventh, in case you have listened to all of them, and final recording. And if this is the first year listening to, now you know there’s a whole series of these. We talked to a number of different industries from consumer products and automotive to retail, oil and gas and more. And we hope you’ll hit that subscribe button and join us and listen in to our other interviews as part of the series and the rest of the Futurum Tech Podcasts.
Quick disclaimer for this podcast, this show is for information and entertainment purposes only. And while we will be talking to in about publicly traded companies, please do not take anything I say, or any of my guests say, as investment advice. Very study to have Jennifer Baldwin and Mark Davis. Jennifer is of SAP and Mark is of Intel. And we’re going to be talking about the utility space today and what is going on in that industry. It’s going to be a great and lively conversation. I’m sure of it. I don’t know this yet, but I believe it will be. And we really hope that you’re going to get a lot out of it. So without further ado, I’m going to bring my guests on, and Jennifer, welcome to the Futurum Tech Podcast Interview Series.
Jennifer Baldwin: Thank you. So yeah, my name is Jennifer Baldwin. I’m an Industry Executive Advisor at SAP in the Utilities Group. I actually started my career off at Hydro One, which is a large utility in Ontario, Canada, and I spent a number of years there working right from taking calls from customers to working in the front office, back office. And then, I moved over into the project [inaudible] and helping utilities with their large enterprise application and implementation. So I’ve got roughly about 19 years utility experience, because I probably started when I was five, obviously, and I’ve been at SAP here for about two years.
Daniel Newman: Welcome to the show. I can’t wait to tap into that experience and hear all about the background, and happy to have you here. So Mark, welcome as well.
Mark Davis: Yeah, I’m Mark Davis. I run Intel Geospatial. So our group is really focused on taking visual information from asset owners and finding ways to process that and run analytics to identify issues, whether it’s with conditions, asset management, a number of different use cases, which we’ll talk about. My background, I’ve actually been in the utility sector almost 30 years. Surprisingly enough, started also when I was very, very young and mostly around remote sensing. So it could be used in the areas of process control, environmental monitoring. So on the generation side, to the transmission to the distribution. So taking new technologies, sort of combining hardware and software and services to solve key problems. And so, based on my experience and background, what I’m doing at Intel, which I’ve been here about two years, is really trying to apply that, and as well as working with SAP, to look at different assets in the field. So whether it’s around vertical structures, like towers and poles, to the vegetation encroachments, which we’ll talk about.
Daniel Newman: Yeah, absolutely. Well, both of you being so young and starting your jobs at five, that’s very impressive. Prodigies, you are. So it’s actually been an interesting year with utilities, right? I think all of us have probably ingrained in our minds the headlines that ran through about Texas just a few months ago, which impacted a few of the industries that we talked. We had one with oil and gas and that was kind of a hot topic around the time we were recording that one as well.
But of course, as utilities, those are the kind of moments where it comes to mind, where you’re also hearing about big investments in infrastructure, and utilities, of course, are going to be part of that story as well. But it’s been kind of interesting year and it’s kind of one of those things that until it doesn’t work, everybody just kind of expects it to, but there’s a lot in terms of making it go. Kind of what were your impressions? Before I hop into the overall last year, I’m just kind of interested, are those kinds of moments like the ERCOT and what happened… Is that like the moment where your antennas go up and you go, “See what we do, mom, it’s a really big deal.”
Jennifer Baldwin: Yes. And it is a big deal because, as Mark and I both came from the industry, my parents still think I work directly for the utility and should be able to answer direct questions all the time. But yes, any time that utilities get in the news, like that. It’s not good, they don’t like it. And working, helping them, we don’t like it, but yeah, it’s been definitely an interesting year.
Mark Davis: Yeah, and what we’ve seen in our side is, while they’ve been talking for years about this shift to more virtual inspections and digital transformation, now having those systems in place would have been really nice with less people able to travel, contractors not being able to show up. And so the work we’ve been doing together with SAP for the last couple of years has really highlighted the fact that when COVID has sort of locked everyone down. And on top of that, the sort of extreme storms that we’ve seen across the country, whether it’s fires and wind on the west coast, or hurricanes in the Southwest area or the Gulf coast. And so these things are really becoming more prevalent. And like Jennifer said, utilities don’t like to be in the news. They want to keep the lights on and just keep things plugging away. So they like less attention to the regulators or less keeping customers happy. And that’s what we’ve been focused on.
Daniel Newman: Yeah, all the adage of there’s no such thing as bad PR, it just simply is not true for utility.
Jennifer Baldwin: Correct.
Daniel Newman: Well, Jennifer, let me hop in and ask you a question about the last year now that we’re there. So besides those kind of monumental black swan, those moments that unfortunately did put utilities in the headlines, the whole world’s been impacted, disrupted, COVID, it changed the way we lived, worked, communicated, it changed where people were working, all kinds of things went on. So I’m just kind of curious, what were some of the key trends that you saw that impacted this industry, the utilities industry over that last year? And did COVID impact it? Was there a specific impact tied to COVID?
Jennifer Baldwin: Yeah, I would say utilities of all sizes, from the mid-market, the mid-size, the co-ops, all the way to IOUs, are facing multiple challenges. You mentioned it earlier on the aging infrastructure, which then makes it difficult to meet customer needs. And regulators are requiring utilities to become more flexible, more agile. They like to throw around the word “innovative”. And customer expectations have been evolving based on their industry. The Amazon effect and the Walmart, they want that [inaudible] interaction with their utility. Some of these would be [inaudible] of COVID. Some of the things before that utilities were semi looking at, small things, like workflow improvements, that e-signature, things that didn’t have a lot of benefit and value, or perceived benefit and value, utilities now are re-starting up those digital initiative and kind of to address those challenges and the challenges that they have historically been facing.
They’re looking to accelerate digital utility of the future, digital transforming. They’re adopting more cloud or enable new services. And cloud really lightens the load of support for the utility. Utility resources aren’t having to worry about managing that infrastructure, managing the network, and they can provide flexibility and agile. There was a study by IGC that said 74%, and it was a recent study, 74% of utilities plan to spend more on cloud technologies in the next three to five years. And I think, if you were to look back even three or four years ago, the interest and adoption of cloud technologies compared to then to what it is today, is almost unrecognizable, to be honest. We were seeing utilities and really one of the outputs of hope, it is utilities really realizing that they need to change the way they work to be more innovative, to be more responsive. And COVID, some of the COVID helped push [crosstalk].
Daniel Newman: Absolutely. There’s quite a bit going on there. And one of the things that caught my attention too, is that some industries can kind of be born on cloud. They’re sort of asset light. You look at the amount of spend to sort of distribute, a lot of services fall into this bucket. Some e-commerce businesses certainly can start this way. They start with much lighter pull. This is heavy asset driven type of work.
You’ve got everything from your electrical grids. You’ve got major hardware and asset infrastructure to get electricity and to get natural gas, and it always seems from point to point. And so, it’s a different looking digital transformation. How do companies deal with that? Because it’s not just about moving to cloud, it’s so much heavier than that.
Jennifer Baldwin: It is, and one of the challenges that utilities face, is all around the data. So we’re seeing all these new data sources emerging that now the utility must integrate into their existing legacy ecosystem and try to analyze it and interpret that data. So what we’re seeing is, utilities starting to invest in tools to capture and analyze that and store the data really quickly, which can help them drive better business decisions. And cloud, as I mentioned earlier, those cloud technologies provides that flexibility to more effectively integrate that data and kind of predicatively use it so it’s ensuring that the right data is consumed by the right person at the right time across the utility lines of business.
Daniel Newman: And Mark, I’d love to get your take on this one too through the Intel lens.
Mark Davis: Yeah. And if you think, when she was talking about different types of data, just to sort of drill into that a little bit, one is guys in the past would have clipboards and colored pencils to try to keep up with assets and what was going on, or if they rely very heavily on service providers. Now, you have guys running around with iPads, or there’s drones, there’s satellites capturing data, even you think of Google street view type cars driving up and down the streets with their assets right there. So then what happens is, you have the challenge of this information. While it’s really rich and valuable, one is, how do you draw insights out of it? Or if you want it to run analytics, how do you do that? And then, at the same time, what we’ve seen is it’s very siloed.
And so, a contractor may be hired to bring in and look at the vegetation encroachments for fear of branches hitting lines or bringing down the power lines and stuff like that. But then, he gets his work done and it goes in a folder, it goes in a hard drive, and no one ever accesses. So how could this data be shared and utilized in a more cost efficient and timely fashion? The same time, what’s happened is, maybe in the past on these assets, they’d have like a 10-year cycle for inspection or five-year. Because of these storms and some of the changes, some of them are going to an annual cycle, same team, same crews, same ONM budget, but now you got to do five, 10 times as much inspection. So how do you do that? And so, they’re being pushed for automation, to do it in a smarter way.
But then, as Jennifer said, the backend tools don’t necessarily manage this types of visual information, these new workflows. How do you change that? The same time is the fact that they’ve relied on these multiple contractors for years. How can you get the most from these contractors so they deliver data in a way that now can be structured and utilized, or if you want to run machine learning on it for that matter? And then the last thing I think that’s heard is, these utilities often cover multiple states, massive areas, thousands or millions of components they got to keep up with. And they have one recall on a certain part.
And now, they’re trying to figure out where is that part? And while you would think that utilities have an absolute understanding of exactly, let’s say where all the poles are in their service area, it’s a real challenge for them. Because of storms changing, new polls go up in a hurry just because they’re trying to get the lights back on, and then the backend system doesn’t match. And now, they’re trying to almost chasing their tail to keep up with this stuff. So just the mode of trying to understand where my assets are, the health of my assets, the condition, prioritizing my maintenance, is a struggle and it has been getting worse. And so that’s just some examples.
Daniel Newman: Yeah, it’s a little bit like the architectural drawings of what’s going to get built and then the as builts.
Mark Davis: Exactly.
Daniel Newman: The as builts keep changing, but sometimes you don’t get the as builts updated every time. And so you’re like, “When did that pole end up there?” But I think also, like I said, it is a business that has in some cases, some of this infrastructure is decades, if not older, and it doesn’t all just get replaced overnight. And as much as people would like to think that you can just flip a switch, and that’s a utilities joke I guess, and get this thing just changed over, it can’t be. But at the same time, new technologies need to be adopted. You kind of alluded to this and I want to dig into this a little bit. You talked about automation, but one of the things…
Well, I know both companies, both SAP and Intel. Is she learning? Is artificial intelligence? These have to be part of the answer. We have to be looking and incorporating these things to help utilities get to the next level, be more predictive in issues, handling maintenance more proactively getting, ahead of outages and storms, and being able to also proactively deliver better consumer experiences. Talk a little bit about what that looks like.
Mark Davis: Yeah, what we’re seeing is, it’s happening in two main areas. First, sort of around the inspection. So can I do inspecting in a smarter way? What we’ve been focusing on, together with SAP, is on the visual aspects. And like I said a moment ago, when you’re trying to take your system of record that says, “Here’s where all my assets are on my poles and here’s what’s hanging on those poles.” When you get visual information back, or let’s say pictures, what is the visual reality? And often they don’t match. So how can you start sort of applying the two to get a better understanding on not only where things are and the conditions, but then how to prioritize your teams. And so from an inspection point of view, there’s two perspectives: The ground perspective, which gives you a certain view, which is really like the traditional where you have a foot patrol or someone looking at the lines of the poles, or maybe they get a bucket truck. And obviously, they want to get the most out of their crews.
They want them to repairing and fixing things versus just looking or fishing for issues. And then now, you’re getting more of this advanced overhead inspection. So let’s say more and more utilities are using drones to capture multiple shots at different angles on the pole, but then what’s happened is mother utilities. You have inspectors now sitting in a room with their eyes, just wanting to poke their eyes out because they’re looking through millions of pictures. So can I use AI to sort of identify the components, look for conditions, and really point that out, so you can get your subject matter experts quickly assessing and validating the inspections. And then from a mapping perspective, and while that’s great, it’s extremely detailed information. They’re probably finding 60 to 70% more issues when they can look at these images from above than just the guys on the ground.
And then, they almost have a problem. I’m seen more issues than I saw before. And this is where SAP comes into optimize the workflows and then the priorities from it for fixing those things. Then on the mapping perspective, imagine being able to just take your entire service area covering multiple states, quickly assess where you have encroachments that’s closer than either that the regulatory utility commission provides or that your utility has set for a clearance distance from trees to your lines. In the past, it took guys as walking the lines and noting that, or an expensive approach where you can take light laser scanning, let’s say, to understand the vegetation. Now, there’s aircraft services that are capturing entire states a couple times a year. And so, you could process that in a matter of minutes to say, “Here’s your high risk areas.”
And so for us, we think of it is taking a recipe or orchestrating these different types of concepts. You may say, “I want to identify which poles have vegetation near them, which ones have components that could cause a spark, like a transformer refuse.” And that combination, now, is a risk priority to say, “Hey, I have bushes and sparking components, I needed to clear that first” versus just go clear these 50 miles. And so, the tools that we’ve been deploying allow, we call it AI orchestration, to run custom recipes that a utility can select and optimize for their workflow. And then those insights are served to their subject matter experts, who then can take action. And so then, that’s corrective actions is if pushed by the SAP, to get their work done in an efficient manner. So those are just a couple of examples.
Daniel Newman: Yeah, so you mentioned a few things that definitely caught my attention. I liked the specificity, sparks and foliage and things that could potentially burn fairly easily. But overall, what you’re really kind of are talking about is defined models. You’re talking about models that have been predefined, that various utility companies can employ and deploy into their businesses to streamline the utilization of ML and AI. And these are real world examples of how it gets scaled, right? Because the thing is, most of these utilities companies have thousands of these, if not more, types of locations where certain, whether it’s computer vision models or certain data models, are going to help optimize services, make sure that you’ve managed, safety is being in consideration, that automation and outreach to customers is being done proactively. We all know, I don’t think many people… I think utilities are right there with cable companies. Most people don’t have a really positive feeling about the interaction they’re going to get when. But this is an opportunity to improve it. Jennifer, you want to weigh in here?
Jennifer Baldwin: Yeah. I was just going to say one of the trends that also came out of COVID recently in serving utilities, that 50% of utilities from an IOU or mid-market have said they’re going to increase their automation operations with a whole emphasis on those technologies by 2025. So between now and the next four years, a large majority of utilities are putting…
Daniel Newman: Yeah, you would expect that. And I think that the data is pretty well validating that this is a trend. It is an investment area that these companies have to make. I wouldn’t even say hand-make or negatory. I think the companies that aren’t making an investment, they are going to be putting themselves at risk of significant disruption or having the erosion of quality to the point where they’re going to lose levels of customer satisfaction that are required to be in this business. And I know choice is sometimes not as big of a priority here as in other industries, but, there is more and more choice. And I think this is going to be something to consider, which brings me here to kind of the last thing I want to talk about, and I’d like to hear from both of you about this, is the partnership.
So, a lot of things that you alluded to, Mark, when you were explaining the use of AI and ML, certainly is done at the chip level, the semiconductor level, which is what Intel obviously is building around AI. And you’re helping build frameworks and you’re helping build models that can be extensible for companies, but they need that application layer. They need that software, and the two companies have partnered very deeply. Because in order to visualize this stuff, see this stuff, pull this data into the usable ecosystem, it takes the chips and the infrastructure, and then it takes the application. You guys have been partners for many years. What does that partnership look like? How are you guys able to together create more benefit for the utility space?
Mark Davis: Yeah. I’m glad you actually brought up the chip part. So Intel, that’s what people think of when they think of Intel, is the chips and sort of the compute-heavy and PC-centric. And Intel actually has also been through ongoing with a digital transformation the last several years to become more data centric. And [inaudible] of the data is where the challenges are and the needs in the market. And so while we’ve always sort of enabled the ecosystem to evolve the new areas, whether it’s in the energy sector and others, our group Intel geospatial actually has been building this software platform with SAP, on AWS, to solve some of these key needs around managing big data, doing AI orchestration and running AI, and then allowing basically enhance the core of EAM or ERP tools that SAP has been delivering for years.
So if you think of a workflow, right? So the utilities are very procedurally oriented. They have thousands of things to do. On any given day, they want to follow operating procedures and maintain compliance. And so you think of it, let’s say they said, “Hey, I’ve got to look at these whatever thousand miles today for inspection.” So that work process starts in SAP to say, “Hey, I have inspections that are required. I got to get this work done.” And that pushes over to Intel to say, “Okay, where’s the data coming from? Is it coming off of a car, an iPad or a drone, or is it available from the contractors?” And then we’ll run these routines, and it may be, let’s say it’s an inspection routine, and so we want to geo locate the assets. We want to do a component inventory, we want to do a defect detection, something like that, serve it up to their SMEs to do the review. Then, it’s handed back to SAP to say, “Hey, I need to take corrective action. I need to update my system, my equipment records, or do capital planning.”
So the combination of what we’ve been working on together is take some key workflows, really leverage and enhance the value of the investments that the utilities have already made with SAP to do this work order optimization, or asset management planning, those kinds of things, and then we can enhance it with AI automation in the structuring of this visual data. So that’s sort of where we’ve been to make these workflows a little bit more streamlined and deployable at scale.
Jennifer Baldwin: And what I would say to add to that is, it’s also SAP and Intel working seamlessly together, helping utilities kind of move beyond the historical, just monitoring their assets and more to diagnose diagnosing, and really looking at asset optimization and performance. So us working together, being able to provide the ability to be ahead of failures, minimizing outages and downtime, which not only increased with customer satisfaction, which we had mentioned earlier, but also regulator satisfaction because regulators are pushing utilities to invest in all these technology. So SAP and Intel are really working seamlessly together to help that.
Mark Davis: I like what you said, sort of the application layers. The utilities, they want to get work done. They don’t necessarily care about the sausage making or what’s going on in the background, but they want it to be consistent, they want it to be easy, and they want to leverage best of breed capabilities. So, to me, if a utility solves the problem of finding, let’s say broken insulators or flashed insulators or these components, an insulator in New Jersey is not that different from an insulator in New Mexico or California for that matter. So leveraging standards, leveraging sort of proven workflows, as well as following some of like the EPRI guidelines. The Electric Power Research Institute has data schemers and methodologies that they’ve done the research and work utilities. And so if you can follow this best practice or a common approach, it helps the whole industry.
So these guys don’t want to reinvent the wheel. They want to make sure that what they’re doing works. And so, I think looking across a whole country and different types of customers to solve these common problems in a consistent way is really valuable. And to what Jennifer said is, a utility has to satisfy their shareholders, their customers, us, where the lights turns on or off, as well as a regulator. So there’s this balance of doing that. And what they’re stressed with is they need to do that maintaining proper operations and maintenance budgets, but then really maximizing their capital that they have out there. Where do I put the next pole? Or where do I hang the next 5G antenna to improve my capabilities? It’s a tough battle for them as to making those decisions.
Daniel Newman: Absolutely, and there’s so many ways technology can help. I got to kind of leave it here. I will say that this is a great example of where industry focused solutions cloud can make a ton of sense, right? I mean, building things that look repeatable, scalable, I say very pareto, there’s an 80/20 effect. There are those kinds of things where every utility has some very consistent challenges and issues. And then, of course, each has their unique ones, but using the consistent challenges to build models and architectures and frameworks that can be scaled and deployed. That’s why industry clouds are so hot. It’s happening, for you guys have mentioned in utilities, but it’s also happening in other industries, whether it’s financial services, healthcare, everyone’s looking for ways to say, “What can we build once and deploy many times at scale?” And it makes a lot of sense.
So let me leave you guys here. Jennifer, thank you for joining.
Jennifer Baldwin: Thank you.
Daniel Newman: Mark, great insights. I really appreciate having you guys. I hope we’ll have you guys back on. We can talk more about this in a future segment here. But with that, it’s time to say goodbye. I hope everybody enjoyed the show and enjoy these podcasts that we did, the Futurum Tech Podcast interviews, alongside SAP and Intel. That’s seven of them. So if this is the first or the second or the third, there are several more to go listen to. And I hope you’ll do that. If this is your industry, we hope you got a lot of value out of all the experience that both Mark and Jennifer brought to this podcast. Hit that subscribe button, join us, follow us on Twitter, all those good things. We love having you. For this show and for this episode though, it’s time to say goodbye. We’ll see you later.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
