Hypercube Podcast Transcript

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Host: Adam Sroka
Guest: Ryan Ciesielski

Intro: Welcome to the Hypercube podcast, where we explore how companies in the energy and utility sector leverage data analytics to make smarter decisions and accelerate business growth. I’m Adam Sroka, founder of Hypercube, a strategic consultancy that supports asset owner-operators, traders, route-to-market providers, and energy services companies to unlock the power of data.

If you’re interested in hearing real-world examples of how data and AI are advancing the energy sector, this is the show for you. 

Hello, and welcome back to the Hypercube podcast this morning. I am honoured to be joined by Ryan Ciesielski, easy one to say. Ryan is director of GI Geospatial Data, Analytics & Technology for National Grid, UK and US. Ryan, if you’d like to introduce yourself and what do you do for the audience, please?

Ryan Ciesielski: Thanks for the the really decent pronunciation there. It’s quite a tricky one. So yeah, I’m a geospatial professional and I work with, I’ve been working in the geospatial industry for 22, 23 years now. I love all things geospatial data analytics technology. It’s my passion as well. I don’t really ever switch off because geospatial is everywhere.

When you stand on the ground, it’s geospatial. It’s everywhere. So yeah, so that’s my thing. It’s my passion and my professional life too. 

Adam Sroka: I always ask guests, what is it their organisation does, but I don’t think many people that listen to this podcast don’t know National Grid, but would you like to give us a rundown of maybe what your part of National Grid does?

Ryan Ciesielski: Okay, now obviously National Grid is a really big company, right? It’s, we’ve got 40, 000 plus employees across the UK and US and there’s, it’s a big organization. We do big work, right? So yes, electricity say gas transmission distribution UK, US. It’s transmitting power to customers, not just being like, you and I, but business owners, hospitals, police stations, airports, railway stations.

And it allows you to give a different context of customer, if because it’s customer just masks. Actually there’s real people, real businesses, real organizations, institutions as a customer. So with that in mind, so from a GIS perspective, everything about our entire network is stored perpetually.

And it’s my, and my team, and my colleagues responsibility, all of the GIS professionals, geospatial professionals, it’s our job to look after that digital view of the network within our data and technology systems. So everything, obviously, everyone will be familiar with, Google Maps, Google Earth.

We’ve got exactly the same sort of idea from a technology perspective to represent the our network geographically, geospatially, geometrically within our technology platforms. So we have to store it somewhere and it’s within GIS. 

Adam Sroka: Rough order of magnitude, what kind of volumes of data are we talking about?

Ryan Ciesielski: It’s insane. So overhead lines, tens of thousands of kilometers overhead lines England and Wales. There’s Depends who you ask, like 380 major substations with thousands of assets in the U. S. So the U. S. covers like the eastern seaboard, so the whole of New England, New York, Upstate, Downstate, City, Long Island.

So you’re talking, hundreds of thousands of kilometers of overhead lines, towers, poles, a smaller substation, so like you’ve got the transmission stuff. If you wish to reveal the right stuff, but then you’ve got the distribution stuff. Now in term, this is a bit, I think this is a really good question actually, because not that long ago I moved into my group, director role and I’ve now been like, I’ve been analysing the US for the last six months.

In the UK, from a transmission perspective, It’s a transmission network. It’s big stuff over big distances to big substations. But when you look at distribution networks in the UK, the density, because the customer are physical buildings, homeowners and stuff, the geospatial data sets are completely vast.

You’re talking of millions and millions of data points, lines, and polygons, right at the core of the GIS data system, millions. It’s unbelievably complex. It’s. 

Adam Sroka: Can’t be many organizations in the world with better, richer kind of problem cases and data sets. 

Ryan Ciesielski: Oh, it’s amazing. I love it. So that’s one of the that’s the reason why I’m at National Grid.

It’s not like a sales pitch or anything, like it’s an amazing company. When I was in the Armed Forces previously, and when I was in the Armed Forces, the military domain, very mature in terms of data, intelligence, digital systems, sensors, satellites, you name it, were absolutely spoiled. But because it was analysing, that geospatial intelligence view was analysing country level problems, when I navigated to national grids in my second career, I was like, whoa, wait a minute, It’s pretty much everything that I was doing in the 40s, I’m working, I’m in the National Web, I’m working with satellite data, aerial photography, fixed wing, rotary photography, LiDAR, BIM, drawn footage, you name it, absolutely every single geospatial data source.

acquisition source, we’re getting to leverage all of those amazing technologies now, and so yeah, it literally does, and because National Grid, and again, as with other, mainstream utility companies, they’re managing country level or regional footprints, so it’s such a big area, and, That you need to do some analytics and tech at scale.

You need to leverage all these innovative technologies. So yeah, it is. There’s so many problems to solve. It’s so diverse. I’m sure I’ll be able to give you some examples later on. 

Adam Sroka: Ooh, yeah you’ve learned a lot of different acquisition sources there, different formats, technologies, begs the question, what are like the biggest data challenges National Grid are facing in this space, do you think?

Ryan Ciesielski: Like the one instantly that I think of and it’s really to help like the audience understand the size of the problems that we’re trying to solve. The problems are so big. At National Grid, we call it, we’re doing big work. That’s our thing, that we’re, there’s a campaign, we’re doing so much big work.

We really are doing so much big work. It’s just monumental. But when you think about all that big work, all this new infrastructure they’re building within strategic infrastructure, onshore, offshore, modernizing the grids, enabling the energy transition for all, all of that good stuff.

Because it’s so big and there’s so much work going on, that’s the challenge. Because you’ve got a landscape today that you need to manage, a network today that you need to manage, and you need to evolve, and you need to try and generate new value, extract new value for customers, so it lowers bills and maintain the network safely and efficiently, but we’ve got this whole we need to get to 2030.

Or we need to get to the next date that we agreed for net zero targets. And we’re building so much new stuff and we’ve got all this new data. So if you try and manage the 2B, and then you think about your core enterprise sort of strategy, that needs to be ready. So when I say enterprise architecture strategy, I mean everything from, systems to applications, to data architecture, information architecture.

All of that sort of stuff needs to be aligned to deal with all that work. But it’s so difficult, so again, maybe just to just try and re baseline that. Because there’s so much work happening, there’s so much to do, and we’re moving at such a great pace, we’re building stuff already, we’re designing, we’re constructing, and we’re ingesting data already, and we’re doing analytics, is The goalposts are always changing.

So you can’t just create a strategy and expect to get to that end state because the end state doesn’t exist. The end state is evolving all the time. So therefore you, we just need to try and think where’s the value. Okay, but let’s get that data and let’s create a geospatial data product to solve this business problem.

Okay. We know it’s tangible, but let’s stop trying to do everything at the same time. It’s a very difficult thing to try and manage. 

Adam Sroka: That’s hard enough for like young startups and small organizations that want, some of which we’ve worked with, like trying to manage a legacy code base or a PFC that people are using and getting value from and to do the new thing.

That’s difficult enough when it’s small. So I can imagine there’s a significant number of Fights and arguments and heated debates about technology choices, direction of travel and things like that. What would you say has changed the most over your 20 year plus career in GIS? I think, 

Ryan Ciesielski: Thinking back to what we described the military, as my first career.

I did 12 years there and very spoiled. So obviously the military domain is really mature in terms of. That area what’s changed since then. Okay. So like those sensors, the resolution of sensors, the availability of technology, the innovation that’s happened in the civilian sector, the business sector, the private sector, that’s what’s changed.

They’ve got, we’ve now got all of those data sources, of course the military, I don’t even know, I’m not in the military anymore, but I guarantee you they’ve got even better stuff than when I left and I would love to know what resolution stuff’s at now and how quickly they create. Digital twins and 3D models and stuff like that.

So basically just to wrap that back into that one is that the availability of high resolution, a temporally decent, refresh rates, capture rates that, that’s what’s available now. We can, there’s so much data. We’re in about the fourth industrial. Revolution type thing. IO ot, 5G, all that sort of stuff, which means there’s so much data out there and that’s what I’m impressed with.

However, , this is what I was leading to, is that I think that there needs to be, that we do, there’s always been these data sources at it, they’re all recognized and we’ve been talking about it for a long time, but it kinda and segue into like entrepreneurs and startups here is that, that I think there’s a huge opportunity.

Whereby everyone knows what the utility use cases are for stuff. We know, everyone knows how we run a network and what our strategic priorities are or objectives are. But I think there’s an opportunity here is what I’m trying to say. We need to think of faster ways to create reality models, BIM models.

at scale, at the network level, and I think that’s a huge opportunity. There’s so obviously there’s lots of data out there. We’re leveraging climate and climate risk scenarios, open source ones, and we’re doing analytics, but that’s not our core. So we find it quite difficult, if we have to put a lot of effort into it, but that’s the opportunity whereby National Grid and other utilities, respectfully, is that we do rely on that, that, that entrepreneurial, innovative approach.

A aspect of sort of UK small businesses, small to medium businesses, because there’s huge, there’s lots of problems to solve and just because someone’s done it already, if you can do it better, then do it, don’t hold back. 

Adam Sroka: Is it fair to say that you have a strategy of trying to adopt the best in class solutions as and when they arise and trying to adapt your flow to, to use what’s out there?

Ryan Ciesielski: Basically because there’s so many dependencies, like for instance, we at National Verde, we’ve got a five, five year business plan. So we’ve got like a five year strategy. And we have to tell our regulator, this is where we’re going to spend our money. This is, this is a rough idea of what that business plan looks like.

So we have to select highly trusted, highly interoperable out of the box technologies, but then when some innovative sort of product comes along. We, we don’t hold back. We’ve got for instance, our our national partners, part of the business should go out and work with entrepreneurs and startups, and they do an amazing job.

If they see someone and someone, a business and a new product that could solve something quicker, easier, and better, that aligns to us, they jump on it. And they need, they bring it in and we run a proof of concept. I’ve been working with a lot of, I’ve been doing a lot of proof of concepts for the last few years.

And so there’s huge scope there. So we’re always looking at, you’ve got the really big mature technologies that are, like, are, like, creating new features, and they’re using AI, and they’re using Gen AI, and they might do a little bit clever stuff with geospatial modeling, so that it does lots of stuff for you.

But that’s the strategic stuff for core systems. But then there’s like the point to point solutions. And I’ll give an example. We’re using like visualization and products that aren’t within the core system strategy, if you mean the core application portfolio strategy, but we’re using them because it’s easier to use them because it’s better 3d or visualization, for instance.

So like when something like that comes along, I am impressed like the agility that we’ve seen and the organization to say, no, hold on a minute, that is a great product. We, it would take us way too long to try and build something like that and using core systems, right? Let’s get our data in there and let’s get our engineers working.

Let’s try and make our engineers, daily work. Let’s help them achieve what they need to achieve quicker and easier without them stressing out about waiting for a core system to design a dashboard or a 3D model or a bin model. So yeah, leveraging those new sort of innovations and products.

Adam Sroka: Totally. It’s really refreshing to hear because so many large organizations do suffer from trying to do everything themselves. And I think really underestimate the level of investment to build something to a level of usability that’s going to make sense. So you’ve mentioned strategy quite a lot through this conversation.

Would you have any advice or guidance for people or organizations that are maybe just starting to think about their enterprise geospatial strategy? What are, like, the key components, the key drivers? 

Ryan Ciesielski: All my sort of advice would be, what is the problem you’re trying to solve? What is the problem you’re trying to solve?

What does it mean? What is the value in solving that problem first? National Grid, we adopted the SAFE Agile methodology, where it’s like product thinking, customer centric design. So think of what it is you’re trying to solve. And then, further down the line, think about what this, what this, first data, what data do you need to help support that.

But don’t think about technology until later, yeah, much later, if possible. But if you have to use technology sooner, don’t do it try not to do it at scale, don’t turn it into a blocker. So basically, what I’m trying to say there is just, don’t over strategize. Do things in small chunks with the greatest value.

What is the biggest value lever for me to do a piece of work? How much is it going to cost me and what am I going to get out of it? What’s ROI in terms of it? It’s too easy to get lost within like an enterprise data strategy, because like I said, the other one, the goalposts are always changing.

My view is that there is no end point. Because everything’s changing. The world is dynamic. And this is the thing about utilities, energy sector, the global environment is always changing. The assets that you put in the ground 40 years ago, the specifications, the design, the parameters, the surrounding environment, all of that data has changed.

We’re in a completely new environment. We’ve got climate change. That’s going to impact on what, the way we design assets and where we place them, strategies around that, the environmental constraints, the community constraints, community considerations. Don’t look way too far ahead. Short term, short goals.

Value value success. 

Adam Sroka: Shameless plug, but that’s almost exactly the messaging and the kind of education we try to give at Hypercube when we try to build projects for people. Like what’s the smallest, highest value step we can take that gets us to learn a bit and move a bit further forward and minimal risk and all that.

And it really plays out to be to build into big successes in my experience. 

Ryan Ciesielski: Yeah, absolutely. There’s so much out there and it’s not the fact that it’s easy to get distracted. It’s just There’s always another consideration, but that’s your, that’s scope creep, right? You don’t want that coming in.

You know what the problem is now. Again, I think that maybe this is a good opportunity just to elevate that to the previous question whereby the challenges at the sort of national grid level, across like country level footprints is that when you decide to do a piece of work, you decided to do a good thing.

But the time it takes you to come and do the work, again, it’s a good example. The landscape has moved or changed. You can’t then say, no, we’re not going to do that investment to solve that problem. You have to get on with it. And I think that’s difficult as well for customers or regulators or other third parties to look from the outside in to say, oh, why are you doing that now?

As in, oh, why are you doing it that way? But no, that’s going to unlock value. You might not be able to see it, but we already agreed. That was a business outcome that we agreed on. So you don’t, but it’s difficult because there’s so many different viewpoints. Everyone sees strategy and delivery differently, but the reality is that if you chose, if you made the right decision and said, there’s true value in doing this piece of work, carry it through because otherwise you’ll be wasted time and effort, cost money by pivoting to do something else.

And then before you know it, it could be an infinite loop whereby you keep going, it’s unhidden. Without delivering. 

Adam Sroka: I think totally, yeah. If they’re not threaded together, you do end up in that quagmire of Things that don’t progress and people become disenfranchised or the work’s not seeing it through or they’re getting dragged into all these meetings that don’t really have an outcome and things like that.

So to change gears a little bit, what would you say you’re most excited about, like trends in upcoming geospatial technology, like where the industry is headed and how it applies to the energy sector? 

Ryan Ciesielski: I’ve got like an aspirational answer, but then I’ve got the real world answers. The aspirational would be the, I’m a big fan of.

Space technology, satellites, high orbit, low orbit. I would like to see higher resolution sensors. I’d like to see faster refresh rates, the temporal collection rates. And also the different sort of data sensors that are available. If there’s a, an amazing scientist out there that can design one that penetrates the ground, like ground penetrating radar from space at scale to a good depth, that’d be amazing, please.

But in the real world In the real world, I think i’m excited that I have seen a massive trend in a, entrepreneurs, startups, UK. There’s been a really big push in terms of those, the types of organizations, the catapults the Location Data Scotlands, the data labs, I’m loving that.

There is geospatial has always been like a niche sort of area, right? I totally accept that. It’s it wasn’t a black box. It was just, Oh, that’s difficult. Let’s get someone specialist or a specialist company to deliver just it. Just fix that problem that I think we’ve got. But now I think that the thing I’m really excited about genuinely is that geospatial is coming to the forefront.

I want to see geospatial being taught more in schools. I want everyone to understand that it impacts every part of our daily life and that there is, there’s an infinite number of problems to be solved. And you can use geospatial data and tech or geospatial data analytics and technology to help solve those.

So well done a big shout out to startups and entrepreneurs out there. Keep pushing and don’t ever be afraid if you see something similar to what you’re trying to create, because yours might be different and better. The other one is. So this is my last answer to this kind of question. The other one would be let’s talk about the real big stuff.

Is that, yeah, GeoAI, I’ve been tracking some cool stuff that’s happening in the U. S. There’s a geospatial institute in the U. S. that’s bought one of the most powerful computers in the world. And they’re basically rolling out community led geospatial artificial intelligence programs. A and B. Proof of concept on data, that’s so cool.

Eh, because I do know that there’s an infinite, there’s, that is going to be a game changer. Especially for climate analysis, instead of taking three months to process, climatic models, for high temperature, low temperature, lightning strikes, all that good stuff, flooding.

It’ll happen in minutes. So we can always be up to date. It’s really cool. No, it is really cool. The other one that I’ve seen is I really like the fact that there’s more turnkey geospatial data product solutions. The value is because there’s so much amazing talent in the world who are really good at stuff.

And if they’re putting into a geospatial data product type approach that can plug into enterprise solutions. That’s amazing value. So like an example is not naming the company, but there’s lots of other companies doing it. That’s why I’m saying that it’s like having turnkey 3d models, turnkey sort of bin models, like we’re going to be doing stuff a lot more intelligently so that we don’t need to focus on stuff that’s not our core business.

We can focus on the stuff that’s really important to our customer. There is huge opportunities. There’s lots of other cool stuff too, right? I love I love machine learning. I love that sort of computer vision approach, walk around a substation, automatically creates the lineage between the real world and the asset management world.

We’ve got like that, that cool robot, the, the four legged sort of robot that cuts around in place. That’s cool. That’s not ours. So that’s not like owned by National Good, but we, it’s an innovation thing that we’re, we’re part of, but really excited to see what kind of sensors we can put on that.

Because it’s a robot, the accuracy and the precision of the path that it’s recording data, very cool. That means it increases the data integrity, that we know the asset’s in the right place. We can do all the spatial analytics, like if that asset fails, is there a domino effect? If a non electrical piece of equipment, like a foundation, is corroding.

That’s really important because connected to it from a network modeling perspective and physically in the real world, it could be a really expensive asset that could cause an outage at the substation, which could cause an outage for our customers. So yeah, there’s no, there isn’t, look, there’s so much amazing stuff happening out there.

But I do think geospatial data and analytics is really getting the attention 

Adam Sroka: that it deserves. It’s a really exciting space because it’s the intersection of like hardware, physical space, data you mentioned the Datalab and Michael should shout out, sitting on the board of the Datalab, they’re running a geospatial fringe event to their DataFest throughout August.

I know you’re getting involved. I’ll be hosting a couple of the events, but you’re getting involved, aren’t you? 

Ryan Ciesielski: I know yeah, super excited and your location here in Scotland. I’m part of the AGI, member of the AGI. I’m used to be given insights. I’ll be given insights into real world use cases of geospatial data technology, how it’s being used, what it really means and what it looks like.

And because that might spark again, I’m always, I don’t know why, right? But I’m a firm believer, if you tell people how you’re doing stuff and what it means, that it will spark innovation amongst those startups and entrepreneurs, if because there’s, like I said earlier on, so much amazing talent out there, but also we need more talent.

We need more people with the right skills in geospatial thinking, analysis, understanding geospatial data and what it means. So yes I’m purposely trying to do more of that stuff because I want to get on top of people and say, look. I’ll be able to help you in terms of, this is, these are problems we’ve done before, this is how we use the data, this was the value.

These were the challenges, think about this stuff, but then obviously to try and inspire folks that there is. Infinite ways to use geospatial data and analytics to solve real world problems. 

Adam Sroka: One thing we like to do just before we let anyone leave is ask if there’s a way for people to get in touch with you or if there’s anything you’d like to plug or promote.

Now’s the opportunity. If people want to find out more about you or the work you do, where should we send them? 

Ryan Ciesielski: If you’re not already on my LinkedIn, connect, follow. I’ve been a little bit quiet on there recently because I’ve been busy building out that capability in my new role. But also not completely promo National Grid, but there’s a, there’s a lot of harmonies across the whole of the UK and the energy and utility sector.

There’s a lot of big work happening out there. There’s lots of amazing materials for instance, on the National Grid website. Go on there and you’ll see all of the big work that’s planned across the UK. Of course, the transmission distribution businesses in Scotland, we’re all working in harmony, we’re doing that whole system, thinking, design, it’s really interesting space, but if you go on there, the reason why I’m saying that is the numbers and the stuff that we’re trying to do, it’s just transcribed Unbelievable.

It’s just crazy. And yeah, like I said, look me up on LinkedIn. If you’re not going to the event in Edinburgh, yeah, jump onto LinkedIn and have a look for it. If not, message me and I’ll send you the link. Yeah. We could see that. 

Adam Sroka: Ryan, it’s been an absolute pleasure and I’m keen to catch up with you over the next few weeks through the events.

All the best at National Grid and thanks again for joining us on the show. 

Ryan Ciesielski: Excellent. Thanks for having me. It was great to talk to you.

Outro: And that’s it for this episode of the Hypercube podcast. Thanks for tuning in today.

If you have any questions about the topics we covered, you can reach out to us on LinkedIn or check out our website at  wearehypercube.com. You can also join Beyond Energy, our Slack community of data leaders from the sector. There’s a link to sign up in the episode description. We’re just getting this show off the ground, so if you like today’s episode, please leave us a rating, review, or subscribe wherever you get your podcasts.

It all really helps. See you next time.