BIM and GIS for AECO Digital Twins

CLAY STARR: Thank you guys for coming this morning, 10:30. Of my favorite announcements that they make on airplanes these days-- and it only happens rarely, but it always makes me laugh-- is the doors are closed, and it's something along the lines of, hey, if you're not going to Dallas, you're on the wrong flight. So I'm going to give you a warning.

If you are here to see Ryan Reynolds, you are going to be disappointed. This is the extent of what you're going to see up on stage. But yeah, this morning, we are going to be talking about BIM and GIS collaboration, to support digital twins for the AECO industry.

So raise of hands. How many A's do we have in here? OK. E's? Got some engineers. Some C's?

There we go. Any O's? All right. We got a couple. All right. We're going to hit them all then.

We've got a light crowd, which is great and fine. We're meant to have a conversation. So I think there's a-- is there a hand held? If there were, need to be microphones.

Well, we'll get one to you. If you have a question anytime, raise your hand. Happy to interrupt and get your thoughts.

So who are we? Let's talk about why we're all here. First off, because I'm speaking, I'm going to go first. My name is Clay Starr.

I work for Esri. I'm part of our AEC team, and I lead our Architecture, Urban Design, and Planning group. I focus on Esri's key customers and working on building out business around architecture, urban planning, and design, et cetera.

Anybody not familiar with Esri or GIS in general? OK, good. So I don't need to tell you who we are. You guys know about Esri. If you want to know more, stop by our booth later. Happy to have that conversation with you.

But I do want to talk about how Esri views sustainability and how we talk about data and its use in support of some of the challenges that we face. And it's important from an Esri standpoint that you understand we view the world through these three very unique lenses. And we feel there's an overlap at any and all times between the social systems on this planet, the economic, and the environmental systems.

And when you talk about integrating data sets, when you talk about CAD, or BIM, or GIS, or sensor data, whatever that might look like, the analytics and the ways we understand that information is geospatial. It is, at its heart, a geospatial issue. And so when we talk today, we're going to try to hit as much as we can about these three lenses.

GIS as a software, as a technology platform is-- it's really just a system of record, a system of insights, and a system of collaboration for managing and applying what we're going to talk about today. And you can see there's lots of technical things up there, but happy to talk GIS. Happy to talk Esri with you guys later.

But I really want to get to our panel and give these guys and ladies an opportunity to introduce themselves. And we'll start-- Megan Stanley, GHD, who are you?

MEGAN STANLEY: Thank you. Yeah, great to be here today. From GHD, I manage our technical applications globally for the business. So I touch on Esri, Autodesk, and many other products across the business that do integrate and connect with workflows for our clients. So a great space to see the change that some of the shares that I'll talk about today in that lens of IS, GIS, but also what's happening in project space.

My three portfolios includes the automation and emerging technology space. We do look ahead about what's coming, what can be integrated in the business. We support the collaboration technologies and also with our partnerships as well.

For me, Yes, I actually have been in GIS a while. Since moving more into a technology leader role, I've been in GIS 18-plus years-- so really understand the workflows. And in particularly, came from an emergency services environment-- so fast-paced, standardization around symbologies, but getting information out to the field quickly to make decisions. And we've seen some big change in that industry as well. And a bit of a background in graphic design and art, so that's a bit of my personal flair that comes in that loves the geographic approach.

And just a bit about GHD-- we are a global firm. We are in three economic regions from our UK, Middle East part of the business, to our Americas, and also our APAC side. So we are quite broad. We've got about 12,000-plus people and centered around a lot of the markets around environment buildings. We've got sustainability, roads, transportation, and so on.

So there's lots of connects into the different aspects of supporting clients and projects. And some of our strategic pillars that we've been focusing on from what we're seeing around community resiliency is around that future of water, energy, and future community space. So a lot of our projects from a horizon perspective are looking at that forward-looking piece, but we are working in connecting globally on many projects in that spectrum. So thank you.

CLAY STARR: Yeah. Thanks, Megan. Just a quick question to get us all warmed up. When we talk digital twins-- we've heard this talked about obviously ad nauseam for a few years now-- talk a little bit about how your view-- and I mean maybe your specific or maybe even GHD's view-- how has the view of digital twin maybe changed just in the last 12 months?

MEGAN STANLEY: Oh, look, it's an ever-changing pathway. We've heard it quite a lot in industry in the last couple of years. But for me, I-- and it's something I resonated actually with what Andrew had said yesterday on main stage is that technology is moving at a fast pace. We've got a lot more data coming into our systems or consuming and creating from, which includes a lot of different technologies and integrated technologies. I'm seeing a lot of integration across technologies now as we move into the digital twin space where it's more of-- I see it as a modular connection into the outcomes you're trying to achieve for your clients.

So I think we're also seeing our clients are becoming more savvy. They're asking bigger questions around data. They're wanting to get into the mix of moving it around, and it's not just static anymore. It's actually, what does it mean to business aspects of the business or even the people side?

The human-centered approach I'm seeing come through as well. What does it mean to the people and the communities? What impact is that making? It's not just about the tech. And we've seen this for a long time, but we're really seeing that human-centered design come through, especially from GHD. There's a lot of focus on that space for client discovery of projects in that area.

And I think we're seeing the emergence of cloud. So that collaboration across regions is supporting what-- if we are building that digital ecosystem where people do need to connect in different regions, I'm seeing a lot of questions around cloud security, data flows, but then how do we connect and collaborate the skill sets across the globe to really get the outcomes that we need? So some of the key things that I'm seeing in regards to a morphing of what that means to digital twins.

CLAY STARR: Awesome. Thank you, Megan. Let's move on to Chris Harman, WSP.

CHRIS HARMAN: Morning, everyone. My name is Chris Harman, Technical Director of Digital Delivery and Innovation for the WSP Transportation and Infrastructure US Business. And that is a mouthful. I apologize.

I spend about half of my time working with internal clients or internal teams trying to change the way we work, instituting new strategies, new process, new workflows, building out technology. And then I spend about half of my time working with external-- so actually working on projects, working with clients, doing as much real work as I can get my hands on, which is unfortunately not a lot. So I still manage to be a BIM manager. I still manage to get my hands dirty enough to know what I'm talking about, but I make it up as I go along, as you'll see.

And WSP, I think-- I've been here two years now, so I feel like I'm starting to understand. If you follow the industry, we are now the largest AEC firm, and most of our work is design. And you get that through acquisition. And one of the things I really like about WSP is that they have just a really diverse set of clients, and deliveries, and sectors doing everything.

So if I ever need something, I can usually find it. But we don't like to say we're the biggest. We like to say we're leading. We want to lead.

And I think that that's something that we're really trying to lean into over the next few years. So it's an exciting time to be there because it doesn't feel so big. We're just trying to get stuff done.

CLAY STARR: And I'll ask you the same question I asked Megan around your thoughts around digital twins conceptually. How is that altered or changed over the last year

CHRIS HARMAN: I mean, if you're familiar with the Gartner Hype Cycle, like the rising expectations and everybody says it's going to be the next big thing, and then there's the trough of disillusionment when everybody's like, wow, this is just never going to happen. We did that with VR/AR. And then there's the-- it moves back up and becomes part of just day to day and stops being a thing we even talk about.

I'd say we're definitely in the trough of disillusionment. I don't know what the room feels, but I hear it from our clients a lot. They're just sick of it. And I'm going to be a broken record.

I'm going to go Jeff Goldblum, Jurassic Park. I'm not going to do a definition of digital twin, but I am going to say, we were so obsessed with what we could do, we never stopped to think about what we should do. We just let the dinosaurs loose, and everybody's mad at us.

And I think the problem is we never really did let the dinosaurs loose. We were just like, we could make dinosaurs. Do you want dinosaurs? And we'd be like, yeah, cool. And then we're like, well, actually, it doesn't work that well. And then we're left holding the bag.

So I'm going to touch on themes of that throughout, but that has been what I've been coming to. And not that I'm not still bullish on it, but I'm starting to say, I don't care if you think what I'm describing should is not necessarily a twin or what you're describing could be like-- I don't care. Let's just talk about who's paying for what and how we're going to give them that.

CLAY STARR: I thought your Jeff Goldblum quote was going to be more of the positive, like life--

CHRIS HARMAN: Finds a way.

CLAY STARR: --finds a way.

CHRIS HARMAN: Digital twins find a way. I'll do that next time. I hadn't thought about that, yeah. I could probably string together a set of GIFs for this, yeah.

CLAY STARR: All right. Mark Mutter with Arcadis.

MARK MUTTER: Thanks for having me, Clay. I got no dinosaurs. Sorry about that. But we'll get on. So Mark Mutter, work for Arcadis as the Director of Digital Twins. My time is across three areas. One is working with clients to solve their problems.

So how does a digital twin help them solve something? A second is building our products or solutions that we can take to clients, a standardized offering. And the third one is similar to what you were saying-- building out capacity capability, playing around with a couple of proofs of concepts, seeing what technology can enable us to do.

Probably a little bit on Arcadis on the next ones. For those that aren't familiar, we are a Dutch firm, about 150 years old, 36,000 people across 70 countries. Again, if you've got a question about some topic, we've got a ton of experts, which is always really helpful to be able to delve into, across a couple of areas-- so places. So this is the built environment-- so buildings, mobility, helping people move through cities and between cities.

And resilience is really picking up on the sustainability and climate change resilience. And recently, we've added a fourth one-- so intelligence, helping our clients. I mean, it's a complex topic, this one. And it's not a surprise that there's help needed on our client side as well. And how do we adopt this? What do we do with all of this new information and new capabilities that are coming our way? So that's the fourth area.

CLAY STARR: And I know, Mark, you've been the Director of Digital Twin now for several years. Full disclosure-- I worked for Arcadis until about two years ago, so I go way back with Mark. How has your view of this topic change just in the last year or so?

MARK MUTTER: I really like the trough of disillusionment example is there are so many definitions of digital twins. You ask 10 people, you'll get 11 answers about what a twin is. So I read them, and they make sense to me. I understand the words that are in there and how they come together, but I don't think it helps anyone really understand why do we want one. What are we going to do with it? So I think a similar vein is focus on the outcome. What benefit is it going to achieve?

So we're starting to move it to something much more simple. So what's the use case? What's the problem you're trying to solve? And that will define a lot of what you put in place around a digital twin, what you talk about. So for me, the understanding has moved.

It's a data model about something in the real world. And it's got an ability to bring in data about something, and that's it's secret super power. And how you do that and how you define it it's really going to depend on the problem you're trying to solve.

CLAY STARR: And I want to remind our audience. You guys ask questions any time. You've got a panel of experts up here who live and breathe this topic. So raise your hand, interrupt me.

It's not a big deal. But I do have some prepared questions. And it's interesting. You all three talked less about technology and more about the job to be done, right? These outcomes you're trying to achieve.

And when we talk about digital twin, I mean, just in general, we generally maybe don't agree on the actual definition. I don't know that we need a unified definition.

But I think what we agree on is that it's the future. And ultimately determining what that future looks like is really the question that I have for you guys. And that is why are digital twins? Why is this acclamation and amalgamation of all of these data sources-- why are they necessary to achieve the kind of outcomes and goals your clients are wanting? Maybe I'll just start with Chris here in the middle.

CHRIS HARMAN: Yeah, I mean, I think to what I said earlier, the outcome is what it is. I'm not going to do a case study, but we did it at Geo-- Geodesign Summit, this year, present a big case study on a digital twin in New Zealand that was basically an asset management optimization platform. And I really have been pushing us to just call it an asset management optimization platform, not call it a digital twin, because that's the outcome.

That's what we sold. That's what they asked for. That's what they got. And when we call it a digital twin, the expectations grow, and the outcomes could be anything. And we usually get judged poorly not on the quality of our work, but on how well we met the expectations we set at the outset, right?

So sure, we can do anything. It can be anything. And so the outcomes is everything. And digital twins is a great way to wrap it up. It's a great way to describe the process that we did in delivering the asset management optimization platform.

And that is a digital twin in a sense. But we don't call it that. We call it what it is. And that's the outcome we're trying to achieve.

I think that another thing I'll talk more about in a minute is the difference between an endpoint solution for a client, an asset management optimization platform that works for one client in one place. You start with a data set, and you combine it with some stuff and move up. That's that is one thing. It would be much more convenient to have built across several sectors a single platform that would do it in multiple locations.

And then it would be much easier to describe it as a digital twin because it can be applied to multiple places in different ways. But when we go straight up to that end solution to that outcome, it makes it hard to then just say, oh, it's a digital twin, and it does everything because, really, we've built it for that. And that outcome is important, and it's actually very valuable. So let's just focus on that.

CLAY STARR: Megan, you mentioned a minute ago the increasing maturity and the savviness of clients. And I'll put the same question to you. Why is this concept-- why is it necessary to drive the kind of outcomes that they're hoping to achieve?

MEGAN STANLEY: Oh, and I think I'll actually touch on the concept that I raised around that connectivity piece. From what I'm seeing with our clients, we are continually needing to connect the right skill sets across our business and clients to the resources and opportunities around technology, but also data. So I feel like there's a connectivity piece here to achieve those outcomes and to get the benefit of, yeah, the skill sets globally and also leveraging technology across borders.

So I think the connected data ecosystem really sings true when you're thinking about outcomes. And I think the storytelling that we're sharing today, but also, we see it in industry as well, how are each of us connecting the dots on how we apply digital twins to an outcome? Whether it's an environmental outcome, or if it's a regulatory outcome, or if it's an asset management outcome, it's great to hear the stories around how we're all attacking that problem and sharing that knowledge from each other. So again, a connected ecosystem of stories, but also, when we're trying to achieve that, I think that's also an important piece.

And especially as we've got some pretty challenging problems globally that we are all want to achieve, whether it's resiliency through climate, or it's connecting communities on large pieces to support community living and things like that and, also, the energy space. There's some big topics out there and I think connecting us. And how we can better connect technologies is a big piece.

CLAY STARR: Mark, are Arcadis's clients-- are they asking specifically for these digital twins? Or are they asking for something different? And speak to maybe the necessity of what that difference means to them.

MARK MUTTER: Yeah. So we're seeing more and more RFPs or opportunities coming out describing digital twins specifically. But I think similar story is you describe, we're going to come with a digital twin. There's a glazed look across the client's face, and there's a bit of "this sounds expensive." And you try and bring along, team members in your own business.

And it's like, digital twin sounds way too complex for what we need. So I think one of the things that we've been trying to refocus for the space of digital twins is to talk about the outcome. What's it there? What's it going to deliver? It's going to increase resilience.

It's going to make more cars go through this intersection. It's going to make something safer. And you may be using a digital twin for it. No one's describing we're going to make you an Excel solution.

You're describing the solution. In a similar way, you've got to just let the tool be in the background. That's what we're able to bring and offer. And focus on the outcome. And I think that's where some of the trough of disillusionment or the adoption is isn't quite there because it's been a technology-first perspective before, where we're putting a digital twin in place, and we're not focusing on the outcomes.

So it's not delivering a good benefit. So people haven't had a good track record of seeing the digital twin was implemented and, wow, look at what we got for it. It wasn't focused on the outcome enough. So I think, yeah, being able to reshift it.

There is something about digital twins is I'm a massive believer that they are necessary for solving clients' problems, or sustainability problems, or Insert anything there. It's a technology that offers something that isn't there otherwise. It's able to bring in data and plug the missing data gaps that you need to solve the problems. It's got loads of really strong things that are just getting missed, I think, a little bit.

CLAY STARR: I feel like I should retroactively retitle this session demystifying digital twins because everyone has this very unique approach to it, which is not let's define it, and then let's build toward it, and then let's sell it-- although all those things are possible-- but really focusing, it sounds like, on those kind of outcomes and really-- I don't know-- almost translating what the market, and the industry, and even Esri and others are saying about digital twins. And when you put boots on the ground, what are we really trying to accomplish? And with that, obviously you guys know this, I'm sure, that the problems of digital innovations and transformations largely are not technological, right?

Technology isn't the barrier that it once was. Oh, well, it's a file format issue, or it's a VPN, or whatever. The problems we face are largely cultural or even structural inside of our organizations.

But we understand that the need to bring these data sets together is increasing. So I guess, my question-- let's start with Megan this time. I'm just curious on your thoughts on this question in terms of-- and I use GIS and BIM because those are the two big data sets, this horizontal data set and these vertical data sets that have existed for decades. But why those? Why is GHD bringing those together?

MEGAN STANLEY: Yeah, look, and I love that being in the GIS world for so long that we're really seeing the connection here, both from a skill set perspective, but workflows and how we are delivering projects with that integration of both location data and the LEGO blocks of the important asset information around the BIM side. So yeah, I've been fascinated to-- I've been talking to a lot of our colleagues across GHD. And I wouldn't say I'm the sole expert of BIM and GIS connection.

We've got heaps of a lot of different leaders and technical leaders across the business that are looking at different ways of integrating this. And I think we said it earlier. GIS brings location to the project. It brings context to faster decision making. You're not going backwards and forwards with file formats to try and get a location-based question answered that actually might move you faster through that asset life cycle of the project.

One particular example-- and I did bring it up mid this year at the Esri conference. We had some great work that I'm seeing both from a skill set level, but the power that it's having to the client. We're working with a port client in our APAC business. And we are looking at integrating workflows with our auditors construction cloud and the GBIM space.

So we're starting to build this stakeholder opportunity essentially for visualizing data and having some governance workflows around particular parts of the workflow that will help the decision making on that port. And we're seeing some real evidence of that being quite a success. And I love that there's one particular person that's working on that project that is really harnessing the GIS and the design side and pivoting what used to be quite a big gap between it's just a GIS map, or you do your design.

We're actually starting to see these integrated workflows that you're actually starting to see the benefits to the client side in the stakeholder piece. So yeah, I think that working through ecosystems and sharing stories in that world, I think, will be really impactful. And that's just an example of what we're seeing at GHD.

CLAY STARR: Yeah. Working for a digital mapping company, I hear location. And I hear you say it's very important, and this is why I want to georeference my [? CAD ?] and my BIM. But Mark and I have had some interesting conversations where maybe you take a different approach-- I'm curious-- on-- because when we talked about BIM and GIS, you said, yeah, but what about all these other non-BIM or non-GIS data sets? So talk about what Arcadis is doing and how you're leveraging data and why you're bringing it together.

MARK MUTTER: Yeah, so Esri and Autodesk, you guys are making it easy to bring these things together. It's been the launches that you guys have gone through this year. So we can bring these two things together, and that's great. I think the thing for me is it brings context to everything else. Much of it's focused on the asset and the asset health.

So How's the asset performing? Is something broken? Is something worn, et cetera? How much energy has something used? It misses some of the what's the asset there for? What's the process or the thing that it's supporting? The roads there or the bridge is there to move vehicles. And how well is it doing that? Your building-- it's got some objectives like a conference center.

How well are people moving through it? So I think being able to bring these two things together and the GIS element means the context to it is allowing much more-- not just a focus which the AEC industry tends to take about the physical asset itself, how that's performing, but how it performs in enabling what it's there to be doing in the first place. So I think the GIS contextual element just makes that even more applicable.

CLAY STARR: And, Chris, I know we've talked about the idea of-- when we talk digital twins, I know you and I talked specifically about how location was foundational. Maybe talk a little bit, like, what does that mean to you in that place we talked about?

CHRIS HARMAN: Yeah, I mean why are we bringing GIS and BIM together? Because we want to know where it is. Next question.

CLAY STARR: [LAUGHS]

CHRIS HARMAN: No, I'm just kidding. I don't ever do anything that fast. I'm just kidding.

No, I was getting off the airplane. And a guy behind me decided to push past, which is totally wrong, by the way. You're not allowed to do that.

And it annoyed me. And so then I pulled my suitcase out and wasn't paying attention and smashed myself in the face and broke my glasses a little bit. They're all bent. This is a real story. I'm going somewhere with this.

CLAY STARR: [LAUGHS] You're just complaining.

CHRIS HARMAN: So I went to the glasses website where these came from. And I searched for certified authorized repair places in Las Vegas. And it gave me a table.

Ugh. I had to copy and paste that into Google Maps. That's the worst.

Nobody wants to work that way. That's not how we think about things. I don't know one client that's like, yeah, could you just give me a table? And then we'll just figure it out.

Yeah, it's fine. They're not like that. That's not the world we live in.

And I think one of the issues we have is that geolocation should be relatively agnostic. We should all be able to include where a thing is. If we're building things that are important, then we should know where they are. And that should be translatable across different platforms and software vendors.

And so Esri gets credit here because they've been just like us with this very disparate data sets coming in at them. And they're just like, well, just put in a table and tell us where it is, and we'll put it all together in one place. And I think that's what our clients want.

I think the other answer to this is because GIS systems are prevalent across all of our clients, especially in transportation space. They operate huge assets across thousands of miles even-- state departments of transportation, port authorities. And I can't do that in Revit. They can't, right? It's not possible. So it's really important that we include that.

And to answer your original question, I've started just being like, if you're not including geolocation information, I don't want to spend effort on it. Figure out a way to put this in the world, and then we'll talk. And I think that's maybe not the best approach because there's lots of problems we could solve without worrying about that.

But I like the way you put it. And one of the things we try to do in the asset management space is plan projects better, so we don't go fix one thing and then, a month later, go fix something else right next to it. If you don't know where it is and you're basing your decisions on condition, those are the kinds of decisions you make. And that's not how we should be operating.

CLAY STARR: Yeah, that's great. Yeah. We say in Esri, everything is somewhere.

And then there are impacts to the things that exist that maybe aren't related to it exclusively existing. But there are environmental, and ecological, and other factors at play. You're not going to design a house meant for Florida and stick it in Las Vegas.

I heard someone say this recently. He said, they did that-- I don't know who they is-- they did that. And year 1, they were an architectural record. Year 2, they were in court. So the location is something that's critical to how we make these decisions.

OK, yeah, so let's talk. We brought this data together there. And I'll go back to Mark here. We brought it together, right? So let's talk. I want I want to hear the good and the bad or the good or the bad.

Let's talk about some improvements or maybe even some challenges or barriers that have emerged when it comes to, how do I integrate these data? These are sometimes rather large data sets. Arcadis is a big company. You've got all these regional issues and cloud. What are some of the things that you've experienced in that integration?

MARK MUTTER: I mean, just data integration is always going to be massively difficult. And so just when you think you've got it worked out, there's a different situation. Every client, every location's got some different data that's going to require you to do something else. I think that's one of the largest challenges is being flexible enough to be able to manage what might come at you in a different way.

I think that, going back to the user interface-wise, maps are a really natural language, natural way of engaging with the data and the information. It's brilliant. So bringing extra context but adding data to that, it's good. The challenge is, so what? So what does that mean?

Now what? We've brought the data together and fill out the blank. There's got to be something off the back of it. And I think it's harder to find what's the reason.

I want to go and get my glasses fixed. What's the closest one? This is something natural in much of our lives. But when we come to these big schemes or big plans, we forget some of that.

CLAY STARR: And, Chris, what about you? I heard what you said a minute ago, and I just want to-- I'd like to focus on the challenges you guys have seen in order to achieve this. But if there's some positive, I'm sure there's some--

CHRIS HARMAN: Yeah, I'm going to try to be positive. I feel I've been real negative. Maybe it was that guy. I just need to let it go. It was definitely my fault, but it's nice to blame somebody.

So I think challenges are data schema, right? And we spend so much time trying to relate x to y, and this apple is that orange. And it's this never-ending process. I think an improvement that I'm seeing right now-- and I don't have a proof point for it yet, but we all know it's there. We just won a contract with a large DOT to provide digital delivery and a roadmap for them.

And one of the first-- well, they want to do a proof of concept because they wanted to check scour data, flooding, overtopping for all their culverts and bridges. And this data exists in reports. And we were like, OK, well, let's go through and find out what those things are, and then figure out a way to build a table out of that, and then put that into your GIS system.

So that way, now you're not having to scroll through a 100-page report for each crossing, but you can just go to that crossing and click on it and get the data that you want. And they were like, oh, that's fantastic. You're going to revolutionize everything. And we're like, great.

So now we'll just start figuring out how to build these tables and we should call things. And we were chasing this last year. And I mean, as everybody-- we haven't said it yet, I don't know how we made it this far. But I was like, what if we just took all those reports and put them in a bucket and set a large language model on that?

CLAY STARR: Yeah, I was just thinking.

CHRIS HARMAN: Right? Like, why-- our problem has been for so long that challenge of building these data sets and making them talk to each other, and pulling what we need out of it, and figuring out how to dictionary this to that. And we spend so much time doing that. And I'm like, well, what I have is a big bucket of unstructured data.

And then suddenly-- and it has not gone through a trough of disillusionment, by the way, because artificial intelligence, those large language models, they went straight up, straight down, and then now they're just a thing. Before we could ever come to grips with it, we're now suddenly just like, oh, I guess GPT can just do everything. It's just become this thing.

And so the improvement-- but I don't have a proof point for it yet, but we're trying it on this project-- is that I don't have to structure all this data. I don't have to do this anymore. I don't have to spend all my time arguing with the client about what they call things and begging them to define this stuff because the language model will pull it out. And this is where I see a lot of advantage for us in this space because we've been real negative about how it's difficult to put these things together, but now we're into this new era where the more junk we can put in the bucket, the more value we'll pull out of it, which has been a complete opposite up until now.

CLAY STARR: Yeah, the "garbage in, garbage out" mentality over the last couple of decades has been turned on its head because now you just can chuck it all in there and ask interesting questions. Megan, what about you? What is GHD seeing in terms of challenges or improvements to integrations?

MEGAN STANLEY: Look, I think, from-- I think there's a people side to this as well that I'll touch on as well as the technical that we're seeing a lot more thinking beyond teams. So if you're in a team, it's about team of teams. It's beyond the silo of where you sit. So if it's a GIS team working with a design team, and the planning team, and the whole-- what is the broader ecosystem of the data sets that you need to work on?

So you're bringing teams together. So I'm seeing an opportunity there. And I mentioned one before where we are looking-- we're doing some great between-team type workshops. And they're being led by some young professionals too, which have some really great ideas.

So and they're sitting with this cross skill of both design and GIS. So they understand both worlds, and they're coming up with these integration workflows between these technology integrations that are now becoming available. So yeah, I think that's been a great thing to see from an improvement over time and just harnessing that across the business.

Something else as well that I'm seeing-- I mean, my role, I work very much within the enterprise. I've had previous roles where I worked client-facing delivery through GIS and building the teams and strategy. But now, having more of an enterprise approach, we're looking at ways of-- it's interesting. We're looking at how things are-- and this is for any client organization-- how you structure your taxonomy on what you call certain even data sets within your business.

So what does that taxonomy structure look like? And that sets up the foundations for future efficiencies, and governance, and automation workflows between teams, as I mentioned. So I think that's been a challenge and an improvement across the business. But I think a big piece here from an integration side is there's a people aspect to this that I will talk about a bit later on.

But it's about connecting the people, mindsets. We've got a cultural focus point at the moment at GHD. We call them the ways.

But there's one particular one which I'm quite passionate on is about data, the data way. And it's linking about what are we trying to achieve from our client's point of view, our future orientation of where we're going with data, but also how we scaling and making things more efficient. So keeping that top-of-mind approach when we are talking cross boundaries is being quite important cultural shift that the business and for us supporting clients on as well around integration.

CLAY STARR: Yeah. We mentioned earlier about these cultural barriers that have existed. We've been talking about breaking down silos for a couple of decades now. And those silos, we thought, were just between the A and the E, right?

Or the C and the E. Those are the silos we had initially imagined. But really, I think what we're talking about is silos that exist inside of our own organizations, where the inability-- not even the desire is there, but it's the inability to understand that it's even possible to make those connections internally, to create those more efficient workflows.

And we are finding-- and I'm seeing in the customers that I work with the desire, the vernacular, it exists. It's just now giving them the tools to understand how to go about doing it because you said, technology is isn't the issue, right? It's getting into your people.

And, Mark, I want to ask you about-- with that in mind, we talked a little bit about how your view on digital twins has maybe evolved or changed over the last several months. But let's talk about your overall adoption strategy. How has your digital twin adoption changed? Or how is your overall strategy around them? What differences are you are you seeing just from maybe a more cultural business-driven sense?

MARK MUTTER: Your question at the beginning, how has your opinion or thinking of twins changed in the past 12 months. And I'm thinking now that probably the next 12 months is going to be way different compared to the last two or three years. I think there was another buzzword just to introduce-- so artificial intelligence, or machine learning, or something else. I think one of the core capabilities of a digital twin is providing the data for AI to burn is, in many cases, you don't have the data sets required for machine learning or all these clever analytics tools to be able to really benefit you. And so twins is a good way to standardize, automate, structure, or bring in unstructured data to be able to do that.

So I think we're shifting to try and find what the right data is to gather. I think 40 petabytes of data was mentioned yesterday. It's like, what can you mine from that? And there's still going to be big gaps that you needed that you wish you had. And that's where twins, I think, on an AI strategy can really add some fuel to the fire. You can't get that going unless you pour some data fuel in there.

And the other part is just, I think, the impact on resilience and sustainability. Twins, for our industry, it's going to be a big opportunity area to be able to understand how something is performing in not exactly real time, but at least be able to know what's happened for my portfolio or my specific assets. I think it's just a huge opportunity. That's somewhere that we're refocusing us on.

CLAY STARR: And, Megan, since you did bring it up, I want to come to you and get your answer to this as well. Are there other things that have changed from a corporate standpoint around how you guys are adopting your digital twin, how your strategies toward them? How are they shifting?

MEGAN STANLEY: Yeah. I mean, I, again, mentioned earlier at the start we're seeing a lot more savviness from our clients around working with data and understanding what that means. And I think, for us, we're quite conscious of-- when we're talking about a digital twin, there's a spectrum that gets you into a real autonomous or future vision scenario planning environment. But to get there, you need to be visualizing or just connected.

And to get to that spectrum, there is a pathway. And I think we've been quite conscious of understanding our clients' maturity levels of maybe it's about building that data strategy to set up that foundation and to actually share and set them up for what that vision could be in the future. Some are even more advanced.

So it's being aware of that spectrum. And I think that's matured the thinking. I think it's changed, but I think it's matured. And I agree. I think AI is going to play a big role in changing workflows again and how we connect and also what new ideas get generated for our connected teams around that space.

CLAY STARR: And, Chris, because you started the AI conversation, I want to come to you on this question, but I want to ask the audience first. Being in the design-and-build space where you guys sit, how many of you right now are thinking of your data as an actual asset? This idea of time, and materials, and producing production, PDF documents effectively excising 95% of all intrinsic data so that it can be emailed via PDF-- if you're not thinking in terms of data as an asset, if you're not thinking about how you're changing your approach to not only how you're delivering but what you're delivering-- I think that's the challenge that I want to put on you to start thinking about, well, what impact do these technologies, and these new requirements, and the savviness of our clients as they increase?