Bird by Bird: Tackling Data Strategy One Step at a Time with ARKANCE

AI, digital twins and new technology can create real value for design-build teams but only when there’s a clear reason for using them.

In the second half of our conversation with Tobias Scheele, Executive Vice President, Americas, ARKANCE USA; Nick Miller, Pre-Sales Director, ARKANCE USA; and Brian Skripac, Director of Virtual Design and Construction at DBIA, we get into what organizations should understand before investing in AI or digital twins, how to tell a useful tool from the latest shiny object and what happens when project partners are working at very different levels of digital maturity. 

We also look at the people side of technology adoption, including why new systems can create frustration when teams don’t understand what they’re getting in return.

If you missed the first half of the conversation, listen to “Human in the Lead: Building a Better Data Strategy with ARKANCE.”

Access all our free design-build resources and learn more about Design-Build Done Right® at dbia.org.

DBIA members are shaping the future, one successful collaboration at a time. 

Transcript

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Erin Looney  0:08  
Digital twins, AI, new platforms, new tools, and a steady stream of promises about what technology can do for a project. But before anyone starts buying things, there's actually a much less exciting question that needs answered: What is it you're actually trying to accomplish? Why are you buying the robot? Why are you investing in the software? Why are you doing what you're doing? That's where we're going to start the second half of my conversation with Tobias Sheila and Nick Miller from Archons and Brian Skripak from our very own DBIA. I am your host, Aaron Looney, and this is the Design Build Delivers podcast, brought to you by Archons, an Autodesk Platinum Partner. A couple weeks ago, in Human in the Lead, building a better data strategy with Archons, we talked about the foundation, how organizations manage project information, and what has to be in place before that information can really start working for people and for teams, now we'll get into what happens when you try to put all of that into practice. When you try to start assembling the Legos, because AI and digital twins may be the things everybody's talking about, but they don't erase bad data or unclear processes, and they definitely don't replace a project team whose members are working at very different levels of digital maturity, and we'll also get into the very human problem underneath all of this-that people, actual people, have to use and be able to use the technology. A couple terms that get brought up ad nauseum: AI, digital twins. As someone outside the industry, you know I know AI in a very specific way to what I do, and Brian has patiently explained digital twins to me more than once. As much as we hear these terms, depending on your role in the project, you may or may not understand them in the same way as other project team members. So, Tobias, as an executive, what should you understand before you decide to invest in AI or digital twins or any of the big buzzy words out there?

Tobias Scheele  2:10  
This is one of the really great questions because there's no way you can escape that question these days. No way. So if you thought a while ago you can just ignore it and move on, the answer is no. And with all those big questions, first you need to demystify it and really go back to the source. What is it when people talk about digital twin? It's not just like a 3D representation of the asset. That's not a digital twin. Digital twin is more or less a representation of the reality in a digital format with all sorts of flavors, and we can talk long, long, long, long, long how deep this goes. Similar to AI, what is AI? AI will not do by a press of a button the design of an asset. Will not happen. Will not happen any time soon. But it will provide benefit and help for people who are working in the project, but this means as well from an executive perspective, I need to be very clear what do I want out of this. Because if I'm just saying, okay, I want AI, what am I doing? There's a zoo of people, and you can even use the most prominent chatbots and telling you what you should do. So then, everybody, please step one back. Those are not intelligent individuals. Those are not highly experienced employees who executed projects. These are models who are trained on information which are available and give their answer based on statistical evidence. Doesn't mean they have done this before. So, in other words, you need to be very clear. What do I want to achieve? So, and at which point do I want to achieve it? And this goes back into to the item. What is my data strategy? So, at the end of the day, all what you're doing with AI and digital twin is only as good as you have an understanding. What do I want to do with those data, and what data am I using? You are saying is one of those great examples everybody brings. I want to have efficiency gains in my design in using AI for great. Sounds good. How do you want to do it? First, you need to have an understanding. How good is my data quality of my existing projects? If you are still at the phase where everything is like in drawings in your cabinets outside. Good luck to get that digital. So maybe it's not worth the time. And don't try to explain to me that you just scan them and then an AI will make it all right. And then you say, yeah, sure, they can see the handwriting of whatever. They cannot even figure out my handwriting. So not thing. You need to have a certain data maturity before you're starting that conversation. So that data maturity goes back down to the basics. How good is your workflow documented? So what what is your core competency in this whole workflow? How well is it documented? How well is it structured? How much does it have a digital representation or data strategy, aka. A digital twin. How does it all works? Once you have that, you have a base. Then you can have a conversation. What does AI help here? What would I like to do? Then you need to look as well to who do I talk to because there's no yellow pages and there's these 10 companies who have an understanding of it. There is a 10 1000s of people are claiming they know what you're doing. Hence, you need to pick with whom do you want to work on those items, and you need to have an outcome-driven view. AI, by the sake of AI, will not solve all the problems. It will do great things. Don't get me wrong, but then you need to understand as well: is this the right thing I want? So first, get your base layer right, your strategy. So, in terms of your data, and then you ask the question, what do I want to achieve with AI? And then, seeing companies or self companies, you can do great things with it. But first, get the basics right. So it all goes down into the basics.

Nick Miller  5:57  
Perfect example of that is an owner that was referred to us, and they had been convinced that digital twin was the right next step for them, and they were so excited to have the conversation. And so we jumped on to do some discovery to talk about, you know, where are you at? And my first question was like, what kind of models do you receive today? And their response was, oh, we we still receive CAD files. And I was like, okay, we have a lot of work to do, right? I think to Tobias's point, it's about understanding where are you today, what are you doing today, what's the outcome you're trying to achieve, and then how does that compare to like what is happening in the rest of the industry? Thankfully, with tools like AI, you can do lots of research and information finding before moving into a buying phase with a potential vendor. I think that really has bridged the gap for people to understand what's possible when they're asking for things. But understanding the impact of the things that you're trying to purchase, I think, is the most important thing. What problem are you trying to solve?

Brian Skripac  6:52  
They both said it, right? What problem are you trying to solve? What business challenge are you looking to improve? What process hurdles do you have? How can this technology make it better? Technology for technology's sake doesn't work, and we saw that in the early days with BIM. And I see that same kind of hype cycle occurring. I saw it with digital twins. We see it with AI. People are like, "Oh yeah, we got to get an AI system. Well, what are you trying to do? Well, we need it. What does that mean, right? Or an owner saying, "We need digital twin. Well, what information do you need? All of it. Well, how are you going to manage it? I don't know. How do you get that information now? Well, we don't. These are kind of the prep questions that are really important because just technology shouldn't be seen as a band aid. It's a process improvement. It's an enabler, and you got to know what you're trying to do with

Tobias Scheele  7:39  
it. I had to say it always as an executive. At the end of the day, what do I get in return? At the end of the day, you need to have a competitive advantage. So you need to have an ROI. How good can it be? How stretched can it be? All conversations, but there needs to be a return. To Brian's point, so you need to have more than an idea what you want to achieve because otherwise, if you're adding technology and technology and technology, at the end of the day, just let's face it, people are buying. It's true we are talking about. They want to have a building. They want to have a roof off the top. So it doesn't help if you have a nice digital representation of it. At the end of the day, it needs to be there, and it needs to be ideally in the price point you've agreed on before.

Erin Looney  8:24  
So not the concept of a building. Not the concept of the building. Nobody,

Tobias Scheele  8:28  
nobody can can find shelter if it is raining. Right. So it doesn't help.

Erin Looney  8:35  
So all of this sounds like it comes back to what we used to say, and we still say in media and communications, which is just because you can doesn't mean you should. There may be shiny new toys out there, but if you can't explain across every level of the project what that shiny new toy is actually doing for your goals, it's not necessarily going to be an added value situation, and that leads a little into tool fatigue, and we've skirted around that here just a little. Tobias, starting with the leadership, how how can you tell the difference between something that's a valuable investment, like we were just talking about, and something that is just a very sophisticated fish lure, essentially?

Tobias Scheele  9:17  
Well, you you have actually two items, and always saying two items from an executive perspective. So first, what is the value proposition and the added value for my business, for my people, for my customers? That's the first gate which needs to be passed. So what is it really? And then the other item is: this is again, what do you want to be? Do you want to be the trailblazer, the first of its kind. Do you want to be a follower? So this is his work coming to your company. What is your risk appetite? There are people who are super highly innovative and say, "Look, this is our whole business purpose. We are the ones at the forefront. We are super innovative. Yeah, if we made three times the wrong decision, we take deep breath because we." Deep pockets. We can do it the fourth time, but then we are gone. So now the companies are saying, you know what? I want to be on the front, but I don't want to be the last one. It's really like first, what type of company are you? What is your appetite to take innovation? Then on the other item is what's your underlying culture? If you, as a company executive, say, you know what? I want to be the absolute leader, and and doing first innovation in your whole culture and organization is extremely risk reverse. I mean, this one might work. You need to find the right balance. This is like corporate executive one on one. So I like to say, okay, what do I want as a company, and then is do I have the right culture here. How do I embed it from a executive perspective? Right now, these are exciting times because, as I told you, you cannot escape this. So this is happening. This will happening, in my view, over the next one to three years. It will come to a point where it will be stabilized in the new normal. So then there were a lot of people who will get a wake up and wondering why am I late? What happened? Why I'm not there at all? And others who are wondering, wow, I did something really right. What was it? What was right? I'm sure there will be a lot of books written on this. So, and there are a lot of books written already who are claiming they know how it goes and will say, well, tell me who knows exactly how this ends. So, which I have my doubts here. So, this is a time to find the right balance between how innovative do you want to be, can be, how good is your organization in adopting it. And again, at the end of the day, everybody has to realize what does a customer want. Can have the greatest shiny toy, the greatest idea, the greatest whatsoever, if there's nobody out who wants this and want to buy for it, then you have a problem. Never ever forget this. This is what I'm telling executives. Never ever forget this when you're making those decisions. Isn't there someone who wants that? And if not immediately, that's fine. I mean, you can market analyze to death, and then sometimes you don't get any out of it. So, but you need to find that balance. So therefore, you always need to stay in touch with the end customer.

Brian Skripac  12:07  
I think that also creates this kind of technology fatigue. Also creates frustration from an adoption standpoint. If you're on the innovation side, on the technology side, and you're just shoving software down your team's throat, and they don't see what the value is. What are they getting out of it? Like Tobias said, even aside from the executive level, the boots on the ground doing something, saying, "Hey, you need to do this, do this, do this, and they're like, "I don't see what value this has for me. That creates some corporate tension, right? They're going to be less likely to want to adopt something, because they don't understand. Hey, I have to take my time away from my task to do this thing that you're you're telling me is going to save me time, but I don't see it saving me time when I'm trying to do it, and that makes the next thing even that that much harder. And I think that's where, when we do these implementations and talk about innovation, we need to meet people where they're at and ensuring that we're solving their challenges.

Tobias Scheele  13:03  
This is a very good point. There are people who are doing this, and they need to understand what is in for me. So sometimes you need to push them, sometimes you need to pull them. The best solutions are where people say, "You know what? I really got it. I want to do it. Those are the easy ones. But on the other hand, we need to understand them. And technology-wise, we are there's not one day where you're not opening the newspaper and something next greatest groundbreaking is happening. If you want a construction site, you're getting there, and again, pile of dirt up to the point where it's very somewhat five years or one year, five years or even longer on certain infrastructure projects. You need to bridge that gap. You cannot come to them every month with the new latest and greatest. That hey, I'm still excavating here, so I don't know what you're talking about. And on this technology innovation life cycle, don't fall into the formal trap that you're thinking, oh my goodness, I left out because I haven't moved yet, and I have to move. Don't go back to the point. Where are you really good apps. When you're looking on the design and construction company, there's a lot of good things. There's a lot of track record, and again, that will not disappear. There's no reason for formal. It's just like, okay, what am I doing right here? So where do I pick it up, and what do I pick up? The

Erin Looney  14:15  
Design Build Delivers podcast is brought to you by Archons, your technology optimization partner, helping design-build teams, streamline workflows with Autodesk solutions, expert support, and real-world training. Ready to work smarter and faster? Get tools, insights, and schedule your AI readiness check at archons.us/dbia. Tools and platforms are one thing, and and I do have to say, while you were talking about that, Tobias, I was thinking of being a kid, and you know the gaming systems were developing almost every year. They were a little bit better than the one the year before and the year before, and we got a Nintendo, and my dad was like, "You're getting a Nintendo till you run the wheels." Off of it, I don't care what comes out in you know next year. All my friends are getting all the other stuff, and we could still play games. So it just it's the adult workplace version of. But I really want the next one up, the next one

Brian Skripac  15:15  
out. So

Erin Looney  15:16  
these are much more sophisticated tools and platforms than that old Nintendo that you blew on the cartridge. Fun as it was, but also skills and experience come into this as well. And you mentioned Tobias affirms culture, and this comes up all the time in talking about design-build projects. Brian, you may be able to speak to this to set the stage. Design-build teams in this conversation we're having can be at very different levels of digital maturity. You might have people who have all the shiny things, and then you might have people who are like paperwork's just fine, or I just draw in the dirt. Let's hope not, but you just never know. When you run into a situation like that where people are working on the same project and that digital maturity is not the same. What do you need to establish early in a design-build project to make sure that doesn't become a problem?

Brian Skripac  16:09  
Well, I think that's one of the things that that gets teased out immediately in kickoff meetings and having the right people there from the outset. And you know, go back to the VDC project leader. That individual needs to be there to curate those conversations. Right, the owner has a goal. The design-build team has a plan to get there. The VDC project leader has to help facilitate how technology, data, all these systems are going to deliver on those outcomes, and part of that is understanding what tools are being used, how interoperable they are, what common data environment is going to be used to provide that transparency and trust of knowledge and information that's being shared, and where the gaps are, and that that's a big opportunity for design build teams, and that's got to happen at the outset. And there are opportunities for collaboration. There might be third party participants that need to come into the project to help somebody who is not able to deliver internally what they need. They can design a system, they can create the shop drawings, but they might also need to do it three dimensionally, and they might not have somebody to do that. Let's bring a partner in to do that, and that individual-that's a project leader who has the opportunity to engage with the team and make sure that everybody can deliver on those standards. I think one of the other things that that VDC project leader has the opportunity to do is break down everybody's corporate standards and be able to mash those up for project standards because you're in a different boat now. And even going back to what Nick said, you know, I'm delivering my stuff and here it is, and you have to figure out how I set it up and why it was there. We're in a different boat now. How do we collectively define those goals and make sure that we're able to get that information from point A to point B to point C and and further down the road? And I think that's a huge opportunity. That's where this project-focused team environment comes into play in design-build and really is an opportunity for success and you know mitigates the siloed corporate structures that don't enable that collaboration and continuity of data.

Nick Miller  18:25  
Part of that too comes from just being transparent with where you're at. I think those ecosystems tend to be pretty supportive, and if you're working with someone who also suffers from like, hey, we don't do the 3D modeling internally, they're more than happy to share a partner of choice, or who they've had success with, or how they've gotten that work done in the past, and it really becomes kind of a community-driven effort to bring all boats up to meet whatever the project requirements are. But it starts with being a little bit, you know, I'm going to use the word vulnerable, right? But transparent is probably the right word. Certainly, everyone has the desire to quote-unquote fake it till they make it, but fundamentally, once you make it, you got to also figure out what you're going to do, and that's where the partnerships can become super valuable in terms of leaning into the other people in your ecosystem and how you leverage them to maybe meet project requirements that are dynamic or different than what you're used to internally.

Erin Looney  19:15  
I have never thought about fake it till you make it past the fake it part. I really, what happens when you do make it? Do you you can't fake it anymore, Nick? Let's get a good example from you of a project, an organization, a situation where all of these things we've talked about this data management problems, the risk, the fear that it could happen, people with a bunch of different tools. Give us an example of where somebody did it well, where they managed project information well, connected it together, and it was as smooth as it can be.

Nick Miller  19:49  
This could be its own podcast, maybe. As I started to think through this, it's it's such a big topic. But I think about one client that we worked with for quite a long time. They've got 50 plus projects. Active at any given time, they're building things across the country. Their active subcontractor and GC clientele and interactive partners are in the 10 to 15,000 range on any given period, and they've got 30 to 40,000 in their ecosystem that they work with as projects activate, come online, and go offline. One of the things I thought that they did. What was really interesting is they, you know, poses a challenge. How do we ensure that the quality of information that we receive is the same across every project and every sub that we work with? And so, working with them to develop an actual KPI quantitative approach to evaluating data that they receive, scoring it, giving it metrics, and then giving the ability to present dashboards to a team that show how you're performing against all of your peers in a defined set of metrics as it relates to how we name and submit things via the submittal process. What RFIs need to be submitted, how they're named, and then what kind of data we need to capture relative to the project that we're on, and then how fast are people responding to them, and really building up a pretty robust and healthy understanding of the requirements that they would like to see, building playbooks that define that for the end users, deploying that out to them, and then creating a monthly cadence where they actually talk about performance, and I think that really is one of the most interesting things that I've seen in terms of taking this massive set of information they're receiving and turning it into a reusable database that drives the longer-term outcomes that they're looking to achieve. Obviously, that's a big project; it's a huge undertaking. But taking that many people and getting them to operate in a single kind of confined ecosystem approach with a common understanding of what the expectation is, it's like if we can do that for that type of a client at that scale, it definitely can be done on a client over client basis, project over project basis. When you've got a dozen or so players in the ecosystem, it just requires some forward-looking planning and some thoughtful diligence in terms of what are we trying to do at the end of this thing to make sure that that's written into the contract language and the program documentation that you're putting forward in the project overall.

Erin Looney  22:14  
Tobias, react to that. What do you see in what Nick was just talking about and in your own experience that is a good example of all of these things we've talked about going right.

Tobias Scheele  22:24  
I was just listening to Nick and then say, you know, this is actually when, and I like that phrase always: the rubber hits the roads. And what does good looks like? Because there is the point. So you have your vision, you have your statement, you have your PowerPoint, you have these ideas. Where does it hit reality from an executive perspective? So yes, everybody would like to have these find one good project, all KPIs green. Reality is when you're in the middle of that change. That's not happening. Change, and everybody needs to understand change in an organization never feels comfortable. So you need to get an understanding what change management does to the people, so to the boots on the ground. So what does it mean for them? It doesn't mean you need to have communication for everybody, so but you need to have an appreciation what's happening there. When you're in the moment of change, you cannot overcome the cable. So people really want want to know this, but at the end of the day, outcome counts. So the outcome driven. So you want to do good things. You want to talk about that. So you want to take that very good project, that team who did this very successful, that ecosystem, that partner, really help you to work this. Expose them. Talk about what was it? What really worked well. Do a post mortem. Do not just walk on. So this is really about what does good looks like, and how do you benchmark against it? What is needed to make the best next project equally or even better, always a bit better. Going back to your one of your earlier points when you said, "Oh my goodness, people still have their their paper in the drawer or the drawing in the sand, and then when you're thinking back, some of the greatest architectural marvels in human history have been drawn in Santa at the time because there was nothing else. But this means there is a deep, deep, deep understanding. There is a deep, deep knowledge in the whole community how to do projects and things. You don't need to completely reinvent this. Just like okay, what are the elements which you need to touch, and then go from there. And when there is a success, expose it, talk about it, prove it, show it. Then this creates peer pressure, peer interest. You always want to be showing success. So success breeds success. This has to be a success-driven initiative. It's not an initiative I'm doing because executive asks for it. That's never a good idea.

Erin Looney  24:52  
So I'm going to end with a really basic question. I'd like to take all of these some abstract, some concrete ideas we've talked. And create this useful package for everyone listening. For all three of you, where do you think an organization should begin when it knows it has fragmented project data? What is step one from your point of view?

Tobias Scheele  25:16  
Do an assessment of the SS, then obtain where would you like to be? What are the steps to get there? And don't do it in one jump. It's not happening. Don't have like if I don't reach that end goal, I'm just screw everybody. No, no, no, no, no. Have steps, and each step needs to be celebrated.

Nick Miller  25:36  
If this were easy, everyone would have done it already. Find a partner that you trust, right? Find someone that you feel like you can work with, that you think has relative experience to what you're trying to accomplish, and bring a partner into the mix to be a third-party arbiter in the process. We find a ton of success with that simply because we become kind of numb to our own pain in some capacity. We don't recognize that maybe things are being done in a way that is not the easiest, most predictable, best outcome possible. That's where a third-party lens can be helpful to assessing what else might be possible, or give you the opportunity to at least benchmark you against your peers in the industry.

Brian Skripac  26:14  
I think back to Tobias's point, right? You can't eat the elephant hole. You can't take all of your data. Everyone's data is fragmented. The bigger the firm, the the more fragmentation that you have. I've worked in mid-sized firms and extremely large firms, and it's scalable. It gets the fragmentation gets worse the bigger you get. But find out where the easy win is. You have all this data. Where are you suffering the most? What's the biggest pain point? The biggest challenge that you have? What's going to provide the biggest ROI? And look for that as your initial establishment. Then move on to the next thing. I think it's very true. You can't can't do it all at once. You got to take small wins, but you have to understand what your challenges are and where your pain points are, and solve those individually. Make that list, and then chip away at it over the course of time.

Erin Looney  27:04  
Bird by bird. Yes, as a matter of fact, I did just say bird by bird. Hey, it worked for Ann Lamott. It worked for Ted Lasso. And after Nick brought up all the boats, Tobias put the rubber on the road, and Brian tried to eat an elephant hole. I think one bird at a time is a perfectly reasonable place to land. So pick your metaphor. Just don't try to boil the ocean while you're at it. Or, said more clearly, you don't have to solve every data problem at once. Thanks again to Nick, Tobias, and Brian for joining me in this two-part conversation. And if you haven't heard the first half yet, go back and take a listen. Human in the lead, building a better data strategy with Archons is available wherever you're listening to this podcast. That conversation puts all the things in place for a lot of what we talk about here, from data strategy and project information to the role people still have to play, no matter how sophisticated the technology gets. Thanks for listening to the Design Build Delivers podcast, brought to you by Archons, an Autodesk Platinum Partner. Learn more at archons.us/dbia.

Transcribed by https://otter.ai