The Year of Data: Why Data Is the New Currency of Construction in 2024

Robert Bryant:

Welcome everybody to this live webinar on the topic of why data is the new currency in construction in 2024. Very excited to be talking to you today, kicking off 2024 in terms of webinars with InEight with this topic, which just seems so appropriate, hence the title, talking about it in 2024 as the new currency.

My name is Robert Bryant, executive vice president for InEight Asia Pacific and it’s my pleasure to host today’s webinar and to introduce to you our panel and I will do that in just a moment. Before we do that, a couple of quick reminders for you. In terms of our housekeeping and running order, throughout the webinar, you are all muted as you may have discovered if you haven’t already, you are muted, but that’s not because we don’t want you to take part. We do want you to interact with us and we want to get some conversation going through the chat feature. So please do that. Put those questions on the Q&A section that you will see on the panel in front of you. If you’re having any issues, please use the chat feature and we’ll do our best to get you back online and get you participating and solve everything for you.

Just on InEight very briefly, for those of you that perhaps aren’t familiar with us, just to give you a quick rundown of who we are and really some understanding of why we’re so keen to explore this topic with the panel today. At InEight, we’re all about challenging just how well you can apply data to deliver better project outcomes for your infrastructure and engineering projects. And that means that it’s everything from the beginning all the way through to the operations of that asset. So it’s critical for us to understand just how well data can be applied, challenges that you face as businesses, organizations, and stakeholders on those projects. And I’m sure you’ll see today what we’re going to cover is entirely relevant to the challenges that you face and the ones that we help you solve.

In terms of the questions, we have got that Q&A section, so please do put those through and we’ll do our best to answer those as we get through the conversation today, and certainly towards the end, we’ll see if we can find some time, but I do anticipate we’re going to have a pretty packed session ahead of us. There will be some poll questions for you as we work through today’s webinar, so please do take the opportunity to take part in those. It’s going to help us guide the conversation and make sure it’s entirely relevant to all the topics that are top of mind for you, so please take a second to take part in those polls as they come through.

All right. So just to reinforce what we’re here to talk about today, 2024 really marks a tipping point for the construction industry. It’s the year in which data has become even more important than dollars. And the reason for that is because it informs decisions and is so critical to helping improve productivity and efficiency. It shapes the way that money is spent. And without good data, stakeholders are typically just working in the dark. And in an increasingly complex and demanding environment it’s not just frustrating, but it’s also dangerous and arguably that’s commercially irresponsible as well to not use the data points that you have to make better decisions.

Data literacy is critical and the people that we’ve got with you today are extremely literate in the topic of data amongst other things. And so I will introduce you to them now. We have with us today Cameron Mills, who’s the head of Project Controls Australia and APAC for Systech. Cam’s been a project controls expert or became an expert, I should say, with experience over the last 27 years across private and government projects. And I think that’s critical to having that broad perspective. Cam’s led multidisciplinary teams in very complex environments, managing assets across diverse sectors, everything from water, railroads, tunnels, oil and gas, buildings, retail, mining, heavy industrial and civil and mechanical and electrical infrastructure. Cam’s basically being across them all. Head of project controls for APAC at Systech International. Welcome, Cam.

Dr. Ajibade Aibinu, our associate professor in cost management and construction economics at Melbourne University. Real pleasure to get to know Ajibade over the last year or so since we’ve been at Melbourne Connect as our base for InEight in APAC. Ajibade is an associate professor in the faculty of architecture building planning at the University of Melbourne, and his passion lies in optimizing the built environment through data-driven exercises and the management of data to ensure value for money and good outcomes. Is a visionary entrepreneur and Ajibade is also the founder of ICM, which is a University of Melbourne-based startup that’s dedicated to revolutionizing management of projects in the construction industry. So you can see why it’s just so great to have Ajibade with us. Welcome.

Ajibade Aibinu:

Thank you.

Robert Bryant:

And the last member of our panel is Henry Okraglik from WSP. Henry is a futurist and innovator and a senior executive who defines and drives WSP’s ambitious goal in digital strategy. Some really exciting initiatives that Henry’s been able to share and tell us about over the last few years as we’ve got to know him. And he leads an award-winning team to create software and data solutions that help clients visualize projects and meet the compliance obligations they have and contribute to a sustainable future. He’s internationally recognized and his mindset sees him leader, diverse and innovative project set at WSP.

He’s currently focused on exploring that interplay between engineering and digital and how technology has the potential to disrupt that and really bring about positive change and improve society. And as well as his global role at WSP, he also leads practice hundred strong disciplinary experts in Australia and he is a member of the Smart Cities Advisory Board. So really appreciate you making time to join us today, Henry.

Henry Okraglik:

Thanks, Rob. Hi, everyone.

Robert Bryant:

So let’s get straight in. There’s so much to talk about. So let’s start with the first question that we’ve got for the panel. And I guess a good place for us to start is just how you might define data literacy in the context of the construction industry and why is it considered as crucial now as financial literacy. So I’ll start off with that question for Ajibade as he straddles that space between academia and commercial space. So Ajibade, from your perspective, how’s the perception of data’s importance changed and how does that work from a data literacy point of view? What’s your thoughts on that?

Ajibade Aibinu:

Yeah, thank you very much, Rob. So from my perspective, data literacy is basically the ability to work with data and particularly to understand that data, analyze, interpret, and also be able to communicate that data, whatever insight is coming from that data effectively towards making better decisions. And I guess in terms of how this has changed, the importance of that, I guess it’s all around better outcomes. And the outcome can be business outcome, it can be project outcome, it can be operational outcome. So it is a lot around outcome, either at project level, either at company level, and of course across the life cycle. I think that’s another thing I will emphasize as well, across the life cycle.

So if you are looking at the project right from the initial business case all the way to facility management and end of life when we’re building, the asset is disposed, so it must be across the life cycle. So I would say that is the literacy in my view and why it is crucial.

Robert Bryant:

Thanks. A lot of things that make absolute sense to me there. And, Henry, from your point of view, what do you see in terms of data literacy? What’s it mean to you? What have you seen it means as you’re engaging with clients out there in the market as well?

Henry Okraglik:

Yeah, I think we’re seeing a substantial change. If you think about engineering design and project controls for that matter, we used to generate a lot of drawings and a lot of designs that didn’t have a lot of data associated with them. Now it’s all about the data that’s generated by the designs and we’re increasingly finding customers want that data not just at the design stage but during construction and then during the operational phase, so data is becoming crucial. And of course one of the things that’s happened is we’re now producing huge amounts of data and creating the issue of how do you access it and get intelligence out of that data in the right timeframe to be able to make good use of it.

Robert Bryant:

True enough. Cameron, you’ve seen these challenges firsthand as well, data literacy and its importance. How do you see it shaping up as becoming parallel if not more important than financial literacy?

Cameron Mills:

Well, I mean assuming we’re able to take, as Henry says, the incredible amount of increases in data that’s being generated, as long as we can take that and turn it into information that can be used, that’s the underpinning of it actually having value. And when you’re comparing it to say financial literacy, if you look at, say there’s 10 or 11 functions on every typical mega project and finance and cost covers about two or three of those areas, but every single one of those 10 or 11 areas is generating vast amounts of data. So I think very, very quickly it’s come to the point that being able to harness that information and turn it into something that’s informative is really important, far more than just worrying about the cost and how finance is going.

Robert Bryant:

Love it, love the perspective there in terms of where the balance of information lies and data points. So we have put up our first poll question for you. So very keen to get your input on this, everybody. If you are looking at your screen, you can see the question in front of you. Please take the opportunity to answer that. How much does your organization value data in its daily operations? So if you are thinking about it, do you feel as if you are running on instinct as a business? Is it somewhat used to the way that you operate? Do you use it more? Are you on a progressive path towards using data more effectively or do you already live by it? Are you here because you’re a sold advocate? Please let us know your answer and we’ll come back to the answer in just a moment, see what you all think, see how that might guide our questions.

So back to the panel and keeping that whole theme moving, in terms of the accessibility of data, in terms of the key challenges that construction companies typically face when it comes to data literacy, how do you each see accessible data influencing project outcomes and what are the challenges that you see in terms of how data may or may not be structured and how it gets consolidated? Because to your point, Henry, there’s more of it than ever before. So perhaps starting with you, Henry, on that topic, what do you see being those challenges in terms of getting access to meaningful data and structuring it?

Henry Okraglik:

Yeah, if you think about the construction process, it happens in a very linear way. It’ll typically go if we take buildings as an example from an architect to a whole lot of engineering disciplines who will then flow it onto a contractor, who will flow it onto a whole bunch of subcontractors, who will flow it onto components, suppliers and manufacturers. And the vision has always been that that data will seamlessly flow through this value chain creating huge efficiencies in the industry. And what we find instead is that it’s broken at just about every intersecting point.

And so you produce a lot of data, but it really gets used in a way that actually contributes to productivity. And it’s no secret the construction industry is a huge laggard when it comes to productivity. And I think data is a major contributor to it is this chasm and somehow we need to find a way of breaching this chasm in this flow of data. We produce lots of data, but it very rarely makes its way through much of a value chain.

Robert Bryant:

Yeah, it is. It’s a great challenge to have of course, because it’s not a shortage of data, it’s just how well it flows and how well it’s shared, to your point. Cam, how have you seen that? I mean, you’ve been involved in so many projects across different sectors. I mean, do you see those same challenges? Is there anything that you’d add to that?

Cameron Mills:

Yeah, absolutely. Henry’s absolutely nailed it there. Look, it comes down to maturity level of an industry and organization as well. Some industries are more mature in the way they structure and work to process than other industries. I think that it doesn’t help that there’s no unified theory of project management and no typical standardization is the way we work in most of our industries. I mean, most organizations work in very disparate manners and most projects within those organizations work in very disparate manners. So I think trying to standardize the approach, but I think the biggest thing is through process.

I think process and training and development of people leads to technological innovation and adaptation. So I think where it’s worked significantly for me over the years is when you have very well-defined process of how you’re managing data and information throughout the life cycle of the project and you’re bringing all of those functions together, you’re bringing all the technology together in proper enterprise architectures and you’re getting the process to really drive how you want to operate. So I think there’s just a massive amount of work to be done in that maturity space.

Robert Bryant:

So at the moment, Cam, I guess what I’m hearing from you is that you’re seeing there’s still a lot of room for growth in terms of how well different stakeholders are valuing that data or that shared value that might exist between stakeholders on projects?

Cameron Mills:

Yeah, I think that executive stakeholders are looking to be informed more and more now, and a lot of the problem is they don’t really know what they want to see and how they want to see it. And at the lower levels, everything’s been generated more than you can imagine to the point that’s probably not adding a lot of value. So I think for me there is a lot more work to be done in the space of what data can do. I think we’ve gone through quite a few years now of just generating so much information to be able to actually get that to be valuable has been really difficult.

And I think what I’m certainly trying to do now is scale back on that, the old less is more theory. So you’re trying to identify exactly what is required and answer those elements rather than trying to just kill people by information overload. But look, in other industries, certainly other industries I say are more advanced in process and in technology than civil infrastructure at times. I think definitely oil and gas and mining have got a few years ahead of us at this stage and we could certainly learn some lessons from the way they’re managing data and information in their projects.

Robert Bryant:

Yeah, I think that’s an interesting area in terms of the broader engineering construction industry is why those sectors do. And I had suggest it’s perhaps because there’s a very critical understanding of the need for productivity by the owners of those assets as they move through the construction phase. So they always have that end in mind as they’re working through construction rather than perhaps just the delivery of the asset and then walking away. Do you think that’s fair?

Cameron Mills:

Yeah, I think it’s true. I think that there is a definite difference in certain industries that are much more driven by where the clients are private industry clients compared to where it’s say a government client who’s building civil infrastructure for instance. So there’s definitely a distinction between the way these two things operate and work. There’s much more focus on productivity, profitability, those sort of drivers in those private industries than there are more in government. Not that it’s not important, it’s just that it’s more about much more focused on those bottom line.

Robert Bryant:

So I guess it depends what the objectives are and it comes back to knowing what you want to understand as you then think about the data that’s in front of you. Henry, I know that you’ve been driving data literacy programs at WSP for the last 12 months. Can you share with us a bit about why that came about and what you’ve learned in terms of the objectives and the benefits of that program?

Henry Okraglik:

Sure. Well, one of the things I began to observe was that we had a lot of very talented digital engineers who were really adept at producing designs and models and producing huge amounts of data. And then another part of the organization who are predominantly project managers, project directors, and executives who really didn’t understand anything about digital engineering are very, very little. And so you’ve got this sort of chasm of the nerds versus the executive and it often played out in fairly adversarial ways and often to the detriment of the project and the customers and the financial performance of those projects.

So I started delving into this a lot deeper. I ran about 30 workshops last year with every cohort in the organization from our ELT right down to our digital engineering graduates to try and work out what was going on. And part of it is a generational shift, part of it is young people coming through universities now are very adept at using technology. They’re digital natives, they expect to do everything digitally. A lot of the people who are in senior executive roles and project managers don’t really get it and have never really kept up to speed.

So this year’s initiative is about training and education and that means from our most senior executives all the way down to our digital engineers. And of course you’ve got this other issue that the major product vendors that we use in engineering design, so that’s Autodesk and Bentley primarily, they each spend around a billion dollars a year in R&D. So the technology’s advancing a pace, we have to get our digital engineering people to keep up with that and then we need everybody else in the organization to understand the benefits of it and how to use it effectively. So that’s kind of the program at the moment. So it’s been an interesting journey exploring this and very challenging for a lot of our people.

Robert Bryant:

I’m sure it has, I’m sure. Okay, so we’ve put that question out. I’m keen to see what the results of our first poll are. So we’ll bring those up in just a second and see here, well, this is encouraging. And it seems that we’ve got people on board here because they already know there’s some value in this topic and certainly the majority are making their way along that journey using data more day-to-day than they did two years ago and a good number living by it. So we might explore in a little bit just how you’re using data, what sort of things you are applying it to. So get ready for the next poll question coming up in a short while. But that’s really good, so thank you very much for everyone that’s participating in that.

Ajibade back on screen. Welcome back.

Ajibade Aibinu:

Thank you.

Robert Bryant:

Could you give us some insight perhaps from your perspective on the journey that construction companies are taking towards data literacy and perhaps talk a little bit about how it needs to become integral to their organizational culture? Henry was giving us some insights there about some of the generational challenges and different perspectives, which is one aspect of it. What’s been your observation in the work you’ve done to drive change through the organizational cultures that you see?

Ajibade Aibinu:

Yeah. Look, that’s a very good question and a very critical one as well because in our work that we have done working with companies not only in Australia but in Finland and Netherlands and UK, what we have seen is that you got these younger generation coming out of the university who are very passionate about technology. In fact, sometimes I speak to a lot of my students who have graduated and they’re very frustrated. They get frustrated, they tell me, “Ajibade, in your class you show us how to use this technology. We did a lot to our subject, but when we graduated and working, get to the workplace, we’re very surprised why we’re using spreadsheet for that and this?”

Many of them tell me they get frustrated with the inefficiency they see because they feel something can be done at the click of a button and they wonder why. So again, put that together with some of the work we have done with a company, having a vision, having an overall strategy we find is very important for a company, a kind of overall strategy of how data is going to be used and kind of initiative, putting resources for that as well. So some of the company that we have seen in Europe who are very successful, they put a lot of money budget every year into these innovation technology adoption where they have champions in every department.

They have a structure for it. It’s not just waiting that is going to happen. There’s a structure, there is a kind of leadership support. We’ve done a lot of work around the role of leadership support. And what we found very interesting is that the leadership doesn’t mean people who understand technology. We’ve seen companies with very enterprising leaders who are not interested in technology, they don’t know how to use them, but they just believe there is a future for it and they put a lot of resources into it, they support it, and they’re doing it very well.

Even though the CEO or the managers are not digital literate, but it’s just that they can see the future, that vision. We believe having a overall strategy is very important and that then affects training, it affects having objective for it, how the company want to use it, identifying what problem they want to solve depending on the risks that they help clients manage. So we see that management support, that vision strategy very clear as very important because if it is not clear, it’s very hard to track and people get frustrated as well. People get frustrated in the end.

Robert Bryant:

Yes. Okay. But it’s encouraging though. It’s encouraging that even if there isn’t an immediate understanding or comfort level at the executive level, there’s an appreciation that you are seeing that it needs to become part of the fabric and the daily operation of organizations. So I think that’s a positive.

Well, we’ll pose another question for our poll in just a moment because I’m keen to get your inputs on some of that too and understand what else you think about data and how it can be used. We’ll dive into a topic here that I’m sure is going to open up a lot of interest as I add the two little letters, AI. So a lot of buzz around that and as we talk about it in the context of data and good data and data literacy as a foundation for how you leverage it and there’s a great buzz about it, of course. All computers feed on data.

Question for the panel, how well do you believe that relationship is understood by businesses? We just heard from Ajibade about executives knowing or appreciating the value of data and how it may be applied to their business, but how well are you observing stakeholders that you’re engaging with understanding that good data is a foundation for the application of technology and particularly anything associated with AI? Henry, what’s been your experience as you’ve engaged with clients and organizations through WSP?

Henry Okraglik:

Yeah, I think you’re right. There’s a huge interest in AI and if only it was just as simple as opening up ChatGPT and typing in whatever pops in your head, but certainly the projects we’ve been doing would indicate that there’s actually a fair bit to wrap your mind around how AI actually works and how it can benefit your business. So we’ve looked at it really from two points of view, and this is only internal of WSP. For me, it’s important that we understand what it does, how it works before we let it loose on our customers. So we’ve got a couple of projects running internally so that we can learn ourselves exactly what the benefits are and how it works so we can give the best advice to our customers.

So I divide that into two areas. There’s what I’d call productivity improvements and efficiency. So doing things like, let’s imagine for a moment I’m bidding for a project controls project and I want to look at, show me all of the people who have worked with InEight for greater than three years on a rail related project in New South Wales. Now, to answer that question, doing it manually, you would have to go sift through 7,000 CVs in the case of WSP in Australia or have a very good structured data set with a lot of metadata than they do to search on that, which I’m willing to bet most places don’t. We certainly don’t.

So we’ve got a project with AI where you can actually pose that question in OpenAI and it’ll retrieve those results in a matter of minutes. Saving our bid team many, many hours of work, probably weeks and months of work if I totaled it all up. So that’s one example. The other one, and I think this one is more like the holy grail, at least from an engineering perspective, is how do we make some of our engineering design modeling tools more accessible to more people, particularly our younger graduates, and how do we get that to actually help them learn the ropes with things like structural engineering or MEP?

And we’ve got a project going on that we’re doing in collaboration with Microsoft in the US and Canada. So we’ve got a collaborative project working on engineering design, which was very, very exciting and from my point of view, a potential game changer.

Robert Bryant:

Interesting stuff. Yeah, I think it starts to open it up. Your point there about those efficiencies and productivity gains that you can make gets me thinking about this parallel with financial literacy because we can often operate in a business and on a project and believe everything is going swimmingly, but it’s the costs or the behaviors and the patterns that we don’t see that can be doing damage long term. And we get this slow divergence in terms of things costing money each day and suddenly adding up. And the same applies with data. You do things thinking, “Well, it’s just as quick to go and ask the question and have people collect it manually,” but there’s hidden costs to all of that and applying technology in the right way makes the difference. It’s a big problem.

We’ve got another set of poll questions and then I’ll get the panel to add some more commentary to this. So our next question for you as an audience is along those same lines within your organization, how are you utilizing data and AI today? What are the things that you are doing in your business with data? And we heard before that a lot of you are already using data more than you did two years ago, so what are you doing? What are the things that data’s being used to assess and analyze and bring about improvement? So please take a second to answer that as we move across the panel and ask the same question, really just framing that up.

So for Cam, from your perspective, what is it that you are seeing in terms of how AI can be applied, how data can be applied, what are the real gains that we’re starting to see?

Cameron Mills:

I see very similar to what Ajibade and Henry said, a lot of the young ones are coming out of university and they’re very keen to start applying AI everywhere they possibly can and obviously jumping into the technology and so on. So I think some of the biggest advantages in construction we’ve seen are more predictive analysis on things like schedule. So innate schedule as a product itself where we’ve got the ability to feed in almost reference cast, forecast-style programs into a software suite that then predicts potential outcomes based on a bunch of scenarios. So that sort of predictive forecasting is certainly something that I think that even in cost of reference class forecasting, I think that that will be very beneficial in the future for what they intend to use that for as well.

So look, it’s going to take time. There’s no doubt. It’s like with all these new fads that come on, I remember when digital engineering came through and then all of a sudden BIM came through and everyone’s running around saying they’re going to be doing everything by this all the way through. So I think it’s about just cautioning the advantages and the benefits against not losing the fundamental principles that we still need to adhere to. So yeah, I think there’s definitely, everybody wants to be informed, everyone wants information. I don’t think there’s ever a question in an organization that people don’t want to be well-informed.

And I think as Henry said, being a little bit cautious about the AI and where it’s going to take us and what we’re actually getting them to do. One of my biggest fears that technology’s going to essentially dumb down the practitioners and take them away from the basic fundamentals. I’ve been saying this for years. I know universities and industry work closely together, but they’ve got to work even closer together now because I’ve had goodness knows how many graduates over the last few years have come out. And whilst they’re really technology heavy, they’re very at times lacking in the fundamental principles of project management and project controls.

So I think that combination of maintaining that core understanding of estimating cost control, risk, quality time, and coupling that and supporting that with technology and incorporating the technology advancements is important. It is a big fear of mine. As I said, we’re just going to race down a path that people think that technology and software’s the answer and it’s part of the solution, but it’s not the sole solution. So that’s my piece. I think we are all wanting to utilize data, we’re all wanting to utilize and we’re all excited by AI. It’s just making sure that we manage it well.

Robert Bryant:

Yeah. Great point, Cam. Ajibade’s going to be itching to answer some of that because and add something to it because it’s exactly where you’ve the perfect position there, Ajibade, around that. We had a question from the audience that I think ties into this nicely as well, which is there a concern that by the time you train people on the environment and how to use technology, that it’s so dynamic that things have moved on or are there fundamentals, as Cam’s talking about, that we can make sure people are understanding and applying technology to answer those fundamental points? What are you seeing in terms of how that balance of fundamental project challenges versus the application technology are being managed?

Ajibade Aibinu:

Yeah. Look, I think that’s a very important part of the whole technology adoption process. So one of the things that we have done in the past since 2013 is that we have followed about 19 companies in Europe and Australia following them to see the journey, technology adoption trajectory. And one of the, maybe I won’t say conclusion, but one of the things we have seen is that technology adoption is not a journey from point A to B. It’s becoming apparent that it’s adaptation to change because what we’ve seen from this company, by the time you finish, I mean learning or mastering how to adopt them, drones, technologies already how they are, AR/VR is already coming to the market. So we have seen that success is going to rely on how dynamic companies have to adapt quickly, but also thinking about the value, the business value because technology will not solve everything. It’s just a support. It’s just a tool.

Being able to identify what business problem that your company want to use, the data and technology to address things that create value or bring value to your client and to your business. I think that’s very, very critical. And in terms of training, I think it is a dilemma for the industry because you got to continue to just train your people and also what we are seeing is a company, what they complain is they train people and then a year later the people are leaving, they go into another company and then they have to start all over again. I don’t have an answer to that. They also don’t have an answer. It is what it is.

Until the whole industry start to move in the direction of then we have a good full of people who can use this technology in the market. Until then, I think it’s going to be a bit of a challenge too in terms of training, in terms of new things coming to the market, in terms of losing people and having to retrain them all over. Another new set all over again. And again, it goes back to how do you keep your people as well, even as a company, if you train them, if they’re working on your pilot projects, they’re learning how to use data and technology, how do you create an environment where you can keep them?

Unfortunately, we are living in a time where Gen Z doesn’t want to be in a company for 10 years. They’re not like you and me who can be in a company for 20, 40 years and we are very loyal, it doesn’t matter what is happening, we just stick to it. For them, every eight months, one year or two years, they want to change and do something new. So again, I think it’s a challenge which we need to continue to figure out how do we adapt.

Robert Bryant:

As you say, Ajibade, that is a reflection of our current state in that transition. And the fact that everyone in the industry being aware helps rising tide, lifts all ships, and it’s that idea of investing in the industry as much as you’re investing in your company, but of course seeking to retain talent is always got to be a good objective for any organization. So it’s a bit of a mix there.

We’ve got a poll question back out there, so we’ve got a good level of response. We’ll just give you another few seconds just to put your submissions in and then we’ll take a look and see what your thoughts are. Here we go. Okay, very good. So we’ve got, let me see here, just zooming in on my screen. So we have 36% saying reporting as a key function of AI and data and technology, nearly 30%, 27% to guide decisions. Interesting to see a lower number using it or considering moment that they use it to improve efficiency or to identify risk both at 18%, just under the 20% market. So that’s interesting.

Panel, what do you make of that in terms of how organizations, does that fit in with what you would expect and what you see? Henry, how does that line up with your experience of what you are seeing in the industry?

Henry Okraglik:

I think this is such an interesting area working on a project on the Melbourne Arts Precinct where we’re doing a unified sort of de-model of six different construction sites all being done by different contractors, different engineers, different architects. So you can imagine what that’s like. But what’s been really interesting when we go to the asset owners and ask them what they need in order to manage their asset, it’s like chalk and cheese. We get totally different answers and yet most of the data, the justification for it is that the asset owner will need it in order to efficiently manage that asset into the future.

So what we found is that we’ve been able to simplify the data requirements enormously by simply talking to the people that actually will end up using the data. Because I think there is a tendency to over-engineer, over-specify thinking that more data is better. And of course, once you simplify the need for the data and strip it down to what someone actually needs and is likely to use, the structuring of that data becomes much, much simpler and much, much easier. Structuring lots and lots of complicated data without knowing who’s going to use it and why and when is kind of foolish when you think about it.

Robert Bryant:

Yeah, it’s a great topic. It ties in so nicely with this result because in terms of perhaps a line of thinking, it’s like financial statements and documentation too. It’s easy for us all to become overwhelmed by a number of different financial statements, but there’s key ratios and there’s things that matter that really should guide decisions. And to your point, it doesn’t mean you’ve got to become an expert across all aspects of accounting to understand key financial data. And the same applies to any other data point here. Is that fair, Henry, in terms of what we’re talking about?

Henry Okraglik:

I think that’s actually a really good analogy and I think if you look at the financial sector and the area, you are talking about management accounting, very few senior executives are certified accountants, yet we trust them to run a business on a number of pretty small metrics in a way. And arguably, a lot of them do it very well. And really we need to move to a similar type of perspective in the way we’re looking at construction projects and start approaching it from what’s going to be useful, what do we actually need to make decisions? And not just collecting data because we can.

Robert Bryant:

Right. Cam, I know this is a hot button for you. You and I have spoken about this a number of times, the idea that reporting just gets blown out because we can do it as opposed to what do we need?

Cameron Mills:

Absolutely. I mean, this is fascinating results and I wonder how many of the people who answered the poll are frustrated with the responses they had to put in. So I mean, I’ve been on mega projects before where you’re generating 130 dashboards for your monthly reporting. I’ve been on them generating 50, 60, 70, and there’s no way in the world that these can be informative and used. So I personally think in five years time if we ran the same poll, if there was a maturity learning curve, you’d see changes in this that the reporting to stakeholders, which is just a BAU thing, but it’s certainly there and to guide decisions is a good thing.

But things like administrative efficiencies and streamlining operational processes, identifying risk and understanding behaviors, that’s signs of maturity, of a mature organization using information to really understand what’s going on within a project or an organization, not just to generate reports that may or may not be useful or guide decisions with an overwhelming amount of data to support that. So I would love to see this in about five years time and certainly I’d like to think that it would change.

Robert Bryant:

Yes, likewise. So maybe we’ve got lots of people in the audience there who are all sort of animated and agreeing with us, I would imagine.

Ajibade Aibinu:

Yeah. Can I make a comment here please?

Robert Bryant:

Of course, Ajibade. Yeah, I can’t see you on screen, but-

Ajibade Aibinu:

I think this is a very important point around we must always not forget, never forget that the issue of data and technology, if we really want to gain efficiency and productivity and better outcome is always around having the right data to the right person at the right time to make the right decision that they need to make. We don’t want to overload them, so we don’t want to have a matching dashboard with everything. We just, for this particular person, he’s a project manager, he’s what he does every day, he manages safety. All you want to know at the moment on today is what are the safety, how to avoid safety incidences, or how to understand what is it trained in safety.

I think even facility management as well, you can collect so much and it just becomes so massive and not clear, what is that? So I think it goes back to what is it exactly that decision that you need to make? What is the high value decision that you need to make by different people and how do they want to receive that information? When do they need it? And I think this is very important if we really want to gain efficiency and better outcome using data. And like you said, in terms of facility management, I feel that is where the value of data lies during the operation’s phase.

So if you spend a lot of money and effort creating the data during design, during construction, yes you get some gain, which is good, contractor can get some gain, different consultant gain their own gain. But in terms of the real value for the society I feel is really the facility management when you are managing the operations or use of the asset and being able to define that during business case and design stage is very crucial. That is why you will need people who have experience in running asset, in managing asset to be involved in that stage to be able to clearly define what exactly do we need to be collecting across the life cycle to help us understand what did we do and what was the outcome of what we did? So that next time we can do things better to get better outcome.

Robert Bryant:

Yes. It seems to come down to some real fundamentals that just sounds so simple when we talk about it like this, but it’s beginning with the end in mind. So in terms of your data points, and we hear it a bit when we’re having conversations around some of our solutions be that completion solution and the fact that you’ve got scheduling that’s related to completions, but oftentimes completion structures aren’t considered till the end when in fact they should be considered right at the beginning in terms of the handover of data that you need and how that’s structured all the way through the asset. So those data points become so critical.

For the panel, I want to open it up and we’ve got another 10 minutes or so of conversation to have. I’d like to get your thoughts on where you see the industry going? If we project ourselves forward five or let’s make it more exciting and say 10 years. So 10 years from now perhaps we’re all sitting on a beach somewhere, let’s hope. But what’s the industry going to be doing? How are they going to be operating on a daily basis? What sort of people and skill sets I should say are going to be prevalent in the industry in terms of daily operations? Is it going to look dramatically different from today governed by how data is going to influence it or would you expect it to fundamentally remain the same?

What do you think is going to change? And, Ajibade, perhaps I’ll start that question with yourself, given again that bridge of academia where you are guiding graduates that will be part of that scene and then we’ll see what the rest of the panel think too.

Ajibade Aibinu:

Yeah, that’s a very good question, Rob. I guess in the future, in the next 10 years, we’ll continue to see more and more of demand for real time data, real time rather than historic data, real time data to manage assets, especially from a sustainability and environmental perspective. We’re likely going to see a lot more of that. So how do we manage energy? How do we understand energy consumption and how that is impacting the environment in terms of carbon emissions and all that stuff? I think that is going to continue to grow as well as cyber physical systems, digital twin, but where the physical is responding to the digital and digital is responding to the physical as well.

So that connection between the physical and the digital I think is going to be important because that will enable us to see if something is happening within my office at the moment, my model can pick it up that something is happening and can let me forecast what is going to happen next and vice versa. If I change anything in digital, how will my office respond, the environment in my office will respond to that? So those cyber physical systems, I think we’re going to see a lot more of that, demand for that.

Robert Bryant:

Fantastic. Cam, what’s your take on it? Where do you think we’ll be? What will the industry be doing?

Cameron Mills:

I think it’s already started. So if you think of a standard for me, a project controls team, we’ve got cost engineers, planner, schedulers, quality advisors, risk advisors, estimators, dot control, those fundamental functions, change managers, and so on. So those seven or eight functions, we’ve now added an additional function to that for the last few years we’ve been hiring data analysts, data scientists, which is something we’ve never done before. So in 28 years it’s only been the last couple of years that we’ve been starting to employ these complete different skill sets.

And I’m actually working closely with my colleague, David [inaudible 00:47:41], in the UK where he’s out there in the market looking for data analysts, data scientists. So it’s already started. It’s got to the point that standard reporting coming out of standard technology and run by the normal functions or some specialist engineers has now been replaced by these data qualified, degree qualified and trained individuals. So it’s something that I’ve absolutely bought into.

They are now part of a project controls team in any implementation, so they help advise on the technology solutions that you intend to go in and to generate. Also, the way data is managed throughout the lifecycle of the project and obviously reporting a massive big part, reporting piece. So I think it’s changing already.

And what we’re also doing in the next few years and happening now that’s going to change the next few years is we’re training everybody in our team in data analytics. So we’re putting people through Power BI training, Tableau training, we’re putting people through short courses on data management and so on. So it’s actually already happening. So that’s exciting to see.

Robert Bryant:

Fantastic. Yeah, that is encouraging. That is like you say, it’s already here. So often we talk about what’s coming, but of course we’ve got to understand that we need to start that journey today or yesterday in order to be there. Henry, what’s your take on this? I know this is right up your alley. I mean, you’re a futurist.

Henry Okraglik:

Yeah, I’m going to pick up the AI thread on this one I think because I think from what I’m seeing, AI offers the potential to democratize the way we interact with what was complex specialist software and enables people who are relatively untrained and unskilled to be able to safely interrogate and question data and get results. And the reason I think that’ll happen is because of the sort of things Cam’s talking about, these data analysts, data scientists, machine learning specialists will be able to construct the data and the parameters that drive that data in a way that enables people to interrogate it and get solid results out of it. And you really need those data scientists.

And I mean, WSP’s employ hundreds of them at the moment for the same sort of reasons. But I think we will evolve to the point where you’ll be able to use natural language to ask questions that you just couldn’t do today. And I think that’s going to happen much, much faster than people actually think.

Robert Bryant:

That’s exciting. Looking forward to it. So we’ve got a few minutes left and I wanted to make sure we give time to each of you to give a summary, but in doing so to offer some perhaps advice from your perspective from each of you for those listening, for those on the session today, what advice do you offer to prepare them for having an organization that is better able to leverage data and that has improved data literacy as they move forward towards the landscape that we were just describing? So sticking with you, Henry, first of all, what’s your advice?

Henry Okraglik:

I think my advice is to firstly recognize that we’re in a period of flux. This is a very odd period. We’re in between an old analog way of doing things and rapidly advances in technology that are driving huge amounts of data. Often we’re not sure what to do with it. So I think firstly is just acknowledge where we are at this point in time. Undoubtedly in 10 years, 20 years time, it will be completely different to what it is now. So we are at a moment in history of great change, I think. And I think you’ve just got to acknowledge that because acknowledging that means you also recognize that we will make mistakes along the way as we go through this.

And I think having an appetite to learn, an appetite to train, a tolerance for making mistakes as we learn and readjusting as we all get better at this and sharing knowledge I think is going to be critical to advancing the industry. I’m really optimistic about all of this by the way. So I’m not in the least bit pessimistic about it. And I think sometimes people are very critical of technology, but I think in this case we need to embrace it and learn. And I think one of the things I’m starting to fall back on is the need for more training. Training seems to have vanished from most organizations’ vocabulary and out of their expenditure.

And I’m starting to advocate a lot more for moving back to spending a lot more money on training at all levels of the company or we will not use the technology effectively. So my thing is look at training, look at who needs what training and skill them up and do it quickly.

Robert Bryant:

I like it. Ajibade, I’m sure that’s music to your ears in terms of the opportunity it provides. And what’s your thoughts in terms of, again, that advice and perhaps following on from Henry’s comments?

Ajibade Aibinu:

Yes. Look, it’s really a massive opportunity for the society and for companies as well. And I think just flowing from what Henry just said, I would say companies need to know that this is not going to be a sudden flight, is going to be a learning process and it’s not going to be something one day you jump on and you just arrive. It’s going to be a journey you will need to learn, start now, give time to learn. That means have pilot of project, give time to your staff to do it because if they never do it, they never know it. They never understand how it works. And so I would say give time, learn. It’s not a sudden flight. You’re going to go through a process. So do start now.

Robert Bryant:

Fantastic. And, Cam, what’s your take on all of this? Where are we going to be, but more importantly, how do people get there? What are the things that they need to start doing today?

Cameron Mills:

Look, for the older generation, I would recommend be open-minded, be open to change, be dynamic and agile and look for, as Henry says, look for the opportunities and the benefits. For what I would consider myself the middle generation, be cognizant of what’s above you and below you and being able to strategically get everybody where they need to be. And for the younger generation, my advice would be be patient, be patient with where you want to be and how long it’ll take to get there and making sure that everybody’s brought along the journey.

Robert Bryant:

Fantastic. I think you’ve all brought some brilliant perspective for this discussion. I think it’s just starting to open up as these things always do. And I wonder as we’re thinking about that advice and what the vision might be, once we’ve got a couple of minutes, if there’s any questions people would like to ask, please put them through and I’ll pose them to the panel while we have those two minutes or so left.

But as we wait for those questions to come, I might just ask you all, what’s your take on how the construction industry might apply lessons from other sectors? So I’m thinking for each of you, have you seen other sectors be that manufacturing or retail or other spaces where they’ve moved further along the investment journey and the data journey and what might be applied as lessons for construction? Ajibade, what have you seen in the working with colleagues and across different industries within the university space and commercial?

Ajibade Aibinu:

Yeah, I think from what I’ve seen both in Australia and in Finland in particular and Netherlands, a lot of collaboration. Collaboration is very critical across industry. So if you go to Finland, they got a lot of initiative where different industry work together to talk about technology, how it’s deployed and drawing from lessons from companies, from industries that are already advanced. So I think my summary is collaboration is going to be key with the university in particular because we need a lot of research to see how success in other industry can be adapted to our industry because we are a very unique industry. We have short community when it comes to project, we work in silo, we’ve got a lot of these differences in context. So we need a lot of research to experiment to try. So I think collaboration among companies and with the university in particular for research is very critical.

Robert Bryant:

Great. Henry, your thoughts on that?

Henry Okraglik:

Yeah, I’m working on a modern methods of construction project for a large number of public facilities and one of the members of our consortium comes from the automotive manufacturing area. And as he says to me, cars have what, three and a half thousand parts roughly that can produce a car on a production line every one and a half to two minutes. It takes us years to build a large public building. And he’s sort of sitting there going, “You guys, how could you have ended up like this?”

So we have some very, very interesting discussions and it’s obviously buildings and cars are very, very different things for all sorts of reasons, but there are things we’ve learned from him and the automotive manufacturing sector that are 100% worthwhile. So I think learning from other sectors, it’s been invaluable really getting that other perspective.

Robert Bryant:

Yeah, as an accelerator it’s great, isn’t it? And Cam, disclosing on your thoughts around this, what can we learn?

Cameron Mills:

Look, I agree. I think learning from other industries is imperative. I just don’t think we’re very good at it. I think lessons learned and learning from this experience and projects in civil infrastructure isn’t done well and there are some pockets of good practice to be done. And for us, we repeat the same mistakes continuously. We do need to improve. And then once you get that level of maturity, you can then look to learning from other industries, but definitely it’s something we need to get better at.

Robert Bryant:

Fantastic. Well, thank you all so much. Really enjoyed this conversation and look forward to having conversations with each of you. We’ll look for another opportunity to bring you together, but for today, thank you for your participation. Really enjoyed it. Thank you, Henry. Thank you, Cam. And thank you, Ajibade.

Ajibade Aibinu:

Thank you, Rob.

Robert Bryant:

Thank you all for joining us too. It’s been great. I hope you’ve enjoyed the last hour. Please feel free to follow up with more questions if you have them. And if you’d like to find out about our course you can visit ineight.com. We’ve got lots of content there where you can see the blog posts from some of our industry specialists as well as links to other webinars and look out for the series that we’ve got coming up where we try and bring more people like the panel today together to gain insights and help share some really interesting discussion that just challenges how well we can deliver projects.

So thank you all very much. Please don’t forget to complete this survey that pops up as we end today’s webinar. Your feedback’s important, helps us understand what you like and what we can do to deliver value for your time as well. So thank you all, looking forward to more discussions and a bright future for the industry. Thank you all. Bye for now.