Why You Need Digital as a Project Management Strategy

Rob Bryant:
Good morning, and welcome to the webinar today, brought to you by InEight and working in partnership today with the Australian Institute of Project Management. So very excited for today, we’ve had a few discussions in the lead-up to this and I think we’re in for a really interesting hour ahead of us on the topic of why you need to have digital as part of your project management strategy.
Rob Bryant:
So I ask all of you now to sit back with your coffee in hand and listen to what our panel have to say. But at the same time, we do want to hear from you. So please do make sure that you use the chat box on the right hand side of the screen to provide us with any questions that you might have. And give us feedback, really important for us to understand whether we’re doing a good job for you and meeting on your expectations of what you want to hear and what you want to listen to as we get through this conversation.
Rob Bryant:
So, I am here with a couple of seasoned experts from the industry in project management, and I’ll introduce Michael and Brad very shortly. Just before we do get into that, just to give you a bit of background. And the focus for today’s session is really around a recent blog that one of the AIPM members, developed and explored, which was around how the digital age is changed the way that we manage our projects today. And you can view that blog on the AIPM website.
Rob Bryant:
But the interesting points highlighted by those authors were really around how, in this digital age, already the roles and behaviors and expectations of project managers are changing, and particularly what we see in the construction industry. The construction industry itself is going through those life cycle changes, as any industry does, and there’s a lot of criticism often about the under-investment in digital technology from the construction sector. So the real question is how well is the sector keeping pace with change? And one of the first things we want to do is see what you all think to get you engaged in the early part of this session.
Rob Bryant:
So, the question for you in that is do you believe that the industry is keeping pace with change? Is the construction industry keeping pace with change in how it manages projects? And I’m seeing the polls coming through live here, and there’s some interesting opinions being voiced. So we’ll see how that settles down as we get through all of those votes in the next couple of minutes.
Rob Bryant:
The article then goes on to explore around how AI, big data and machine learning has a role to play in that. And there’s some really interesting themes, and we’ll touch on those. But also, one of the other things that I know we’re going to get into is what lessons there are to learn from other sectors and other industries. So we can see how we, as an industry and construction sector, can improve the way that projects are delivered through the application of digital technology.
Rob Bryant:
So, just as we get those answers settling in, I will ask our panel members to introduce themselves. So, first of all, I would like to introduce Michael Young. And Michael is the CEO of a consulting firm that manages and helps firms around the world to improve their operational efficiencies, and also a former chair and board member of the Australian Institute of Project Management. So Michael, welcome to you.
Michael Young:
Good day, Rob. Thanks, I’m really excited to be here today and to continue the discussions we’ve had before now. And in particular, keen to see what people out there have to think to say as well. So I’m looking forward to today.
Rob Bryant:
Excellent, thank you. Also joined by Brad, Brad Barth, coming to us from Omaha, Nebraska, part of InEight. And Brad has been involved in both the construction side of business and the technology side for a number of decades, and has been on the journey with InEight through its entire life cycle as a business and solution. So Brad, welcome to you.
Brad Barth:
Yeah, thank you Rob. Great to be here, good to be with you, Michael. Looking forward to the discussion today. Like you said, I’ve been at this construction technology thing for a long time, going on 30 years, really all my career. And grew up in the construction industry, so looking forward to hearing from the audience today and from both of you on some of the trends, and looking forward to the discussion. So, thanks for having me.
Rob Bryant:
You are welcome. Good to have you here. So, just to get us started, everyone’s put their votes through now. And 43% of those of you with us today say that no, the construction industry is not keeping pace with change. 37% of you aren’t sure, and so hopefully through the course of the next hour, we’ll be able to help you form a solid opinion on whether we are or whether we’re not. Without wanting to be too prescriptive or presumptive, I’m thinking there’s a lot of room for improvement. 20% of you say yes, we are keeping pace with change. So, very interested to hear from you as well on where you see things happening. And of course, there are some great things happening with a lot of very innovative and front line businesses out there, so I guess there’s signs of that change being implemented.
Rob Bryant:
So, going to open that question up as a starter now for Michael and Barth and ask you both, what do you feel about the industry? And I’ll start with Michael, your perspective from outside construction. How do you see the construction industry keeping pace?
Michael Young:
It’s a really interesting question, Rob. So I guess I’ve had the good fortune to work in a number of different sectors in a number of different countries, and particularly coming from that project management side of things, I see what works and what doesn’t work across a range of countries. And what’s really interesting is that when you look at the construction sector, and in particular at the question, we’ve seen a huge amount of change occur particularly over the last five to 10 years. You mentioned in the introduction things like big data and AI, and what we’ve seen is a range of technology tools being used across different sectors.
Michael Young:
Talking specifically about construction, what we’re seeing is the increased use of drones, for example. And some of the technology that’s on board on drones, there’s whole pile of calculations can be done on the fly and you can get a real good sense of actually what’s going on without having to put people onto the site. And so, you can use sensors like that to be able to really measure what’s going on. So, we’re seeing a range of other shifts as well, and I’ll talk a bit more about how that impacts on skills and how that impacts on projects more broadly.
Rob Bryant:
Yes, some interesting perspectives to take there, and Brad, what are your thoughts? From inside the industry, what are you seeing and how well do you think we’re keeping pace?
Brad Barth:
I would love to see the survey response if it was a year ago compared to today because I think we’ve seen an acceleration in the industry’s adoption of digital technology, especially over the last year or so as people have been forced to work in a virtual mode, and collaborate in ways that maybe they weren’t used to. So I think what you’re seeing is the transformation from this all-digital approach going from more of a… It used to be more of a differentiator, more of a kind of fall into the nice to have category, where it’s, I think over the last year it’s starting to cross that hump of it’s almost expected now, right? If you’re not adopting these technologies, you’re behind the curve now, right? As an industry, I think we’re getting over that hump.
Brad Barth:
And I think part of that is all the things Michael talked about, for sure. There’s a lot of new technologies out there that can do things that were, perhaps difficult for humans to do. For example, the drones doing inspections, they can do those things. Get into tight spaces, or challenging or dangerous spaces, perhaps much more efficiently than a human could. But also just the consumer-driven technologies. Mobile phones is a perfect example. That’s the expectation now. Younger folks coming into the industry aren’t going to put up with things like doing paper time sheets and sharing information over radios and over phone calls, right? That’s just not what they’re used to now, the mobile generation has kind of changed the industry quite a bit, I think, as well.
Rob Bryant:
Absolutely. It’s interesting you mentioned the consumer side of things, and I think there’s a lot of technology that is just ubiquitous, it’s part of all our daily lives now. And perhaps, with those respondents that have said yes, 20% feel that we are, I wonder how much of that is actually just in the day to day fabric of life. That technology is a default that’s applied to every aspect of our lives, and that includes, of course, the construction sector and work onsite and work in the office. But to push boundaries a little bit further, we think about where the opportunity and where’s the gap? What do each of you feel the gaps that are there now that should be filled and where technology should be applied to see efficiency and to see productivity improve? And again, to get your perspective, Michael, on the broader economic environment and broader industries, let’s start with you.
Michael Young:
Yeah, it’s been really interesting. So, if you look at technology change across a multitude of sectors, you mentioned the mobile phone and the things that we do on a mobile phone or a mobile device now that only two or three years ago was inconceivable. And so, you’re seeing people carrying their phones on the construction site, it automatically checks them into the site. If there’s any safety information that needs to be conveyed, it can be automatically pinged to people’s phones, and so on. So we’re seeing, as Brad mentioned before, that crossover into construction.
Michael Young:
Where I think there’s huge opportunities is with machine learning, AI and big data. And if you think about some of the key things from a project management perspective, often the things that project managers hate doing, that take a lot of time, are things like reporting. And where naturally machines, computerization and so on excels is around things like prediction and calculation. And so, if you think about developing projects, schedules or programs and also undertaking risk assessments, if we’ve got big data sources that we can basically leverage and machine learning and AI tools we can leverage, what it practically means in time is that we don’t need to actually undertake risk assessments anymore. We can actually feed certain parameters into a system and the risks will be identified and they’ll automatically be ranked and rated.
Michael Young:
Likewise, from a scheduling perspective and programming perspective, we can feed in basic parameters and the AI tools will automatically create the schedules that’s optimized based upon a range of factors. And so, likewise with reporting. No longer will we need to go to site to actually do site inspections and so on. We can use a network of data sources, that could be drone imagery, it could be a whole range of sensors, and so on, and we can capture that data and collate it and create a real-time picture or real-time dashboard as to where things are currently at or where they should be.
Michael Young:
And so, when it comes to the things that we all love to hate as project managers, reporting. Well, we won’t need to do that in time, that’ll happen automatically. Risk management and scheduling, that’ll be done automatically by computer systems that are far, far better at estimating and predicting than we are as humans.
Rob Bryant:
Yeah, that’s a really interesting idea, that we’re actually talking about an elevation at the role of project managers and the tasks that they’re performing, and freeing up some of that time. So Brad, in your time working in the industry and supporting the industry, what are you seeing on that front? Are you seeing that change in the roles within project teams and how they’re calling for technology to fill that gap?
Brad Barth:
Yeah, for sure. I think probably the biggest evolution is in the recognition that information by itself is not necessarily useful beyond the current project, or the current problem in front of us. We’ve got, typically in this industry, a lot of reliance on Excel spreadsheets, which doesn’t do a lot of enforcement around data fit, from project to project, or system to system or role to role. So I think one of the things that we hear quite often from customers and prospective customers who say we hear about the opportunities through machine learning, and even artificial intelligence, to help us work smarter but we know that we’ve got to feed that system with information and turn that information into knowledge. So there’s, I think, a recognition that all these Excel spreadsheets lying around are not really going to help us. Machine learning or otherwise, right? We can’t make a lot of sense out of that data.
Brad Barth:
So I think that’s probably the biggest trend that I think we’re seeing in terms of just being able to capture information in a way that it can be reused more effectively, and it can be shared more effectively, because I think this industry’s traditionally sort of blamed when projects don’t go well, the blame typically falls on the execution side of things. It’s the we didn’t work fast enough, we didn’t get the work done fast enough. And that’s kind of where the blame has been, but I think there’s a gradual recognition that it’s more about planning properly. We’re not creating the right expectations up front, and that’s what project management is all about, right? Setting expectations and managing the outcomes, and you hope they match.
Brad Barth:
But to do a better job of planning… Like Michael was saying, right? A lot of the new technologies can help us. We capture the data the right way from all of our previous projects, humans and technology can both kind of leverage that information, get smarter and be more predictive so that some of that more grunt work, or tedious work, can be set aside and focus on more strategic things.
Michael Young:
Right, and I guess that one of the things we see is that there’s things that we innately do really well as a human being, but there’s also a whole pile of things that, as a human being, we’re not particularly great at. And you only need to look at some of the psychology literature to identify that we have whole pile of biases. We have and optimism bias, and so when it comes to predicting or estimating how long things are going to take, we naturally assume that it’s going to go swimmingly well, there’s not going to be any issues. We tend to underestimate the duration and effort things take, or it will take to deliver a particular project, and so on. And so, innately, the human brain’s not great at doing a lot of that predictive work, but we’ve got machine tools, AI, machine learning, and so on. That’s what they do really, really well and they learn, and they can do it far better than even the best human can do it.
Rob Bryant:
Yeah, it’s interesting, isn’t it? There’s probably nothing more resilient than a project planner in the construction sector in terms of optimism as an attribute, right? So that’s making it a little bit easier today. Michael, keen to understand from your broader experience how you’re seeing project management in construction evolve against other sectors. I mean, is there a bar across sectors where you’re seeing the tasks and things being performed by project managers falling under what you see in other sectors?
Michael Young:
Yeah, it’s really interesting. And when you get a look at what’s happening in the project management space around the world, obviously different countries and different economies are at different stages of growth and development, and I’ve had the good fortune to work with experts around the world developing international project management standards. And so, you get into the real nitty-gritty as to what we do, how we do it, and so on. The great thing about it is that you’re looking at the way projects are planned, scheduled, managed, et cetera, across different industries but also across different countries and different cultures. And so, you get a real sort of, I guess, snapshot of what’s going on when you’re so involved with.
Michael Young:
What’s interesting is that there’s elements around different sectors that are great, but I think that where a lot of the innovation really comes from is when we start to look across sectors and look at what different industries are doing. And so, whilst it’s probably a generalization, a lot of the construction type scheduling approach, for example, is largely predicated on that sort of waterfall or more of that engineering style of model, where we do all the requirement specifications, we do all our design work, and then we do a layout at build, not necessarily in a linear kind of fashion but it tends to be more along those lines. Part of the challenge, of course, is that particularly given the contracting models that are used, where we’re being asked by clients to sign off to some sort of fixed price, or firm price top model, that sort of locks us in to a particular way of delivery as well. And so, we’ve got a few factors that come into play.
Michael Young:
When we look in different sectors, and whilst it’s not all directly applicable to construction, we’re seeing a lot more iterative and agile kind of models being used. And whilst that’s not necessarily going to work in a lot of that high construction kind of scenarios, there are plenty of examples where a more agile or iterative model could actually be applied in a construction sense.
Rob Bryant:
Okay, and that is interesting, the thought that the industry could be shaken up a bit by some different approaches. If we think about the evolution of the construction industry and the challenges its facing, I think one of those very distinct challenges right now is the scale of projects. We’re seeing bigger projects than ever coming through, and we’re talking here about not just the volume of work but the scale of it. So, we’ve got projects that are potentially 10 years, or certainly five, between five and 10 years in duration, and multi-billion dollar projects. We’re talking about 15, 20, $25 billion as programs of work.
Rob Bryant:
So what do you think that does to call for that transformation, and what needs does that bring in addition to just us catching up as an industry? And Brad, with your exposure, what are your thoughts around that?
Brad Barth:
Yeah, I think the increase in size of the projects just raises the game in terms of managing the risk, right? Because the larger the dollar value of the projects, those risks turn into ripple effects that can be quite large. So, from the owner’s perspective, if you’re funding the project not only are you counting on the success of that project, but if that project goes off the rails you’ve got a ripple effect of we’ve got to, perhaps, pull funding from other projects in order to get this one back on track, or we might need to descope the project in order to stay on budget if it’s a budget issue, or get it done sooner if it’s a schedule issue. And that turns into, it cuts into the return on investment we’re getting as the owner of that asset that’s being constructed.
Brad Barth:
So I think the bigger projects create more opportunity to let risk get away from you and have that sort of downstream effect if you’re not careful because in this industry, as we talked about kind of getting going, there’s a history of coming in over budget and coming in behind schedule. In fact, there’s studies that have been done that have shown there’s a $1.6 trillion opportunity in the construction industry globally to fix that problem.
Brad Barth:
And so, that gets back to that better planning, right? So, a part of the challenge we have in the industry is learning from past projects. So, to your point, these projects are quite large, they take a long time to do, so any individual person… You’re not doing 10, or 20, or 50 projects a year. You might do, you’ll do a big project once every five years. And so, it’s really critical to capture the experience on that project, and those lessons learned, so that other people in the organization can benefit from that knowledge so that the risks and scenarios and assumptions that we hopefully validated on that project can be leveraged by everybody else who didn’t go through that project, they were on other projects. So that collective knowledge and collective experience, I think, is critical the bigger the projects get, right? Because the risk gets larger.
Rob Bryant:
Absolutely.
Michael Young:
And I think it’s certainly an area that, collectively, we’re not great at that lessons learned piece. I tend to talk about it as lessons learned… Rather than lessons learned, it’s lessons identified and often lessons forgotten and then relearned. I saw a really quite funny thing scrolling through Facebook the other day and it was sort of almost like the Dilbert cartoon, the three panes. And the first one was department of lessons learned. The next door was department of lessons learned, forgotten, and then relearned. And the last one was the department of come on guys, can’t we get this right? And I thought it was so true.
Michael Young:
I think the challenge we’re seeing comes back to that sort of volatile, uncertain, complex and ambiguous world we’re living in. And so, the rate of change we’re seeing has accelerated exponentially and what it means from a construction perspective and a project perspective, more generally, is that… As you said, Rob, the projects are getting larger, they’re getting longer in duration, and there’s been this sort of expectation creep, also, by clients. And as the projects get larger, just simple technology change, we see a rapid amount of technology change and what you start with at the design or requirements phase could be well outdated when it comes to build time.
Michael Young:
There’s some classic case studies, one of the great examples in Australia here was our existing submarine fleet, and they specify technology in the actual submarine itself. These were built about 15, 20 years ago. And the particular technology they specified was superseded by four generations by the time they actually came to do the build. And they found themselves having to constantly go back and update and change all of their requirements and specs because the technology kept changing all the time. And so, you ended up with this sort of chasing your tail kind of scenario.
Michael Young:
Where it becomes really interesting is that we’re seeing all sorts of technology being built into buildings. Everyone’s been talking about BIM now for ages, but we’re also seeing a lot of smart buildings, and so we’re using a range of sensors to do everything from vent buildings to activate and tune air conditioning, a range of different things. And so, as we start to see a lot of this automation technology come online and being used more widely, that just adds to the complexity no end. And so, this is where we probably need to look at different contracting models but also look at different, more iterative models.
Michael Young:
Just on that, what’s been really interesting in where the expectation change has come from, it comes back to the good old phones. We see the way that software companies churn out an app for the phone now, it’s put out in the market very, very quickly and the focus is really around getting it to market. In the construction sector, we don’t quite see that necessarily. Definitely, there’s a push and a drive to get things done quickly, but we still tend to be doing things the way we’ve done it for a long time. We need innovation.
Rob Bryant:
That’s a really good point, actually, as you mention it because we… For all the value that comes from lessons learned in previous projects, actually looking at a different way of doing something is critical. And there’s another interesting challenge the industry faces right now, which is a labor shortage, and a skilled labor shortage, because we have that many projects particularly in this part of the world going on right now. So, what are some of the solutions and things that we can think about there to take lessons from other industries and to think about how people coming across and transferring skills from other sectors might be able to influence the construction sector and project management. Michael, what’s been your experience across that challenge, and that sort of issue?
Michael Young:
I think we need to think outside the box. I know it’s a cliché and is often spoken about, but what you tend to find is that reality is that we’ve all worked in a particular sector and we tend to move from one client, or one organization, or one employer to the next. And so, whilst every organization’s got their way of doing things, we tend to see only very small incremental change. And we try and do it just a little bit better, or we refine a little bit, and we don’t get that truly innovative step when we go looking at our competitors.
Michael Young:
So, a great a story I read about a little while ago was Southwest Airlines in the US. And typical airline, they fly people around, usual sort of scenario. Well, the problem was they were effectively, they had almost become bankrupt and the only way that they could turn around the company was they had to keep the planes flying. They needed more planes because the way the airline makes money is they’ve got to have aircraft in the air with bums in seats. And if they’re flying people, they’re not making money. If the planes are sitting on the ground, they’re not making money. So they looked at purchasing and leasing additional aircraft. Well, that was off the table because their balance sheet wasn’t looking real good.
Michael Young:
So the only option they really found was they had to turn the aircraft around more quickly. So when it lands, turns up to the airport, they need to basically get everyone off, refit the aircraft, clean it, do all the things that they need to do, get the people onto the aircraft in a really swift manner. That way it spends less time on the ground, and obviously more time in the air. Well, what a lot of companies would do in that scenario is they’d go and look at their airline competitors and they’d go, “Oh well, maybe we can do what these guys do, or what those guys do.”
Michael Young:
Well, someone actually was really thinking outside the box and they actually went and did a benchmarking exercise. And the benchmarking exercise is not the sort of thing that you would naturally jump to. And if you think about what things, sport, situation requires and absolutely super, super fast turnaround. Well, it’s actually a Formula One pit crew, right? They can fill up the car, they can change four tires in about 2.1 seconds, right? So that’s a really good pit stop. And so, what Southwest Airlines did is they went to, I think it was Ferrari, and actually studied the way that their pit crew operated. They also looked at the way that, and hospitals have done the same thing with operating theaters. They’ve actually studied the way that pit crews work, and what they’ve identified is everyone has a very specific role.
Michael Young:
Now, in this instance, they changed the turnaround time from something like an hour and a half down to about 26 minutes. So, massive, massive improvement, and they couldn’t get it less than 26 minutes because it physically takes an amount of time to get people on and off an aircraft. But they looked at the sequencing of all the different parts, who does what, and how it’ll work. And so, they were able to turn around the organization from benchmarking with a Formula One crew.
Michael Young:
And so, yeah, often you’ve really got to think outside your industry and your sector and think about, “Well, where is the best of breed in that particular function?”
Rob Bryant:
I love it, I love it. Just imagine, I think I can see quite a few construction crews and machinery being managed with jumpsuits and crash helmets and stopwatches. I think that could be a thing.
Michael Young:
Absolutely.
Rob Bryant:
Yeah, love it, love it. Awesome. Well, we’ve got a couple of questions come through, so thank you very much to those of you posting those. I want to tackle those for the audience. One of those, I think, comes back to what we were talking about before around scale. But the question is, as most software and digitization is implemented we’re seeing more delay, or projects that are being flagged with delays. So, is there a correlation there or is that just a coincidence? What are your thoughts around that? Are we slowing things up by trying to get too smart with technology?
Brad Barth:
I’ll jump in on that one. I think you’re going to have… The first project, you might suffer some delays as you’re implementing new technologies, getting used to it, rolling it out. Like anything else, you got to get that institutionalized and get through that process. You might have some bumps in the road but typically, what we see as customers are rolling out whether it’s software technology that’s going to help you work more productively and plan better, or even technologies like we were talking about to help you execute better. Once you get it down to the point where it becomes rote, that’s the next time, and the next time and every time after that, you’re going to see those improvements.
Brad Barth:
So that’s part of the challenge, I think, that the industry has had is taking that time and knowing that that first project, or maybe even the first two, are going to be more challenging as you get that new technology under your belt. So, it starts with the owners, right? The owners of these projects that are spending money often have been the ones that have driven the change because the contractors are going to do what the owners contract with them to do. So, it comes down to commitment to making that change, and doing it the right way, and getting over that hump in order to get all the benefits from that.
Michael Young:
Yeah, and certainly, just picking up on a couple of the comments and questions along the same kinds of themes here, what we’re often seeing is the way that a project manager currently manages a schedule is that often it’s highly subjective. And so, one thing we’ll see as a change is that often the project manager will go, “Well, I reported 60% last week, or last month. I’ve got to show some progress so we’re going to report 65% this month.” Now, the reality may be that there’s actually been no progress at all, but we can’t show the same figures as last month because it shows we’re not doing any work.
Michael Young:
And so, when you’re actually getting data feeds from calculated tools or from live data, AI or machine learning tools or whatever it is, what you’ll actually see is the real scenario, not what the subjective view is. And so, yes, you may see some so-called delays, but the reality is that we’re always there, it’s just possibly the project manager or the whatever was reporting optimistically, or reported to show that, “Yes, I’ve made some progress,” and so on.
Michael Young:
It’s one of my sort of bug bears. I say a lot when I’m doing project reviews, and particularly been asked to come in and turn around projects that have fallen over. Often what you find is that when you track back through all of the reporting, you find yes, there’s been progress made but there’s no connection whatsoever between what you see on the ground and what’s actually being reported. It’s almost like they’re two disconnected things. And so, I think what will happen is… It’s a bit like when you’re driving around and you’ve got the GPS set in the car. If you try and second-guess it and go, “Oh yeah, I know where to go,” and of course, you drive where you think you need to go, you often will find yourself getting lost. If you trust the technology, it’s going to give you the real data, the real this is where we currently are right now. And it’ll give you the truth whether you like it or not. Sometimes the answers you get aren’t going to be overly nice or palatable, but it is what it is.
Rob Bryant:
It’s telling you that the way you’ve been going for the last five years is actually 10 minutes slower than the way that I’m going to navigate you now.
Michael Young:
Correct.
Rob Bryant:
Yeah, yeah. Well, I guess related to that . Sorry Brad, I was going to say related to that… I’ll let you respond to that one too, but I think a related question on this is around how reliable is AI, and what faith should we place in the integrity and quality of that data? So, Brad…
Brad Barth:
Yeah, and just tying that back to the earlier discussion, I think that we work with a lot of owners that are for these projects, and for them it’s less about the number itself, whether we’re talking about the duration or the cost, and more about the transparency and avoiding those surprises we were talking about that have those ripple effects way beyond just this particular project. So, it all gets back to that, like we were talking about, get more realistic plans in place. So then it gets back to, well, what is really a delay? Is it a delay against a unrealistic expectation in the first place?
Brad Barth:
It’s all about setting those expectations, so if you’ve got those contingencies and risks and previous lessons baked into the plans… Because one of the things in this industry, particularly when you’re dealing with physical assets that you’re trying to construct it’s, to Michael’s point, there is that tendency to report with optimism, let’s say. We’re making great progress, great progress, great progress. We get to the last 10%, let’s say, and then realize that we’ve got 50% of the schedule left in front of us still even though we thought we were 90% done.
Brad Barth:
So, that last mile effect, I think, is something that the industry is getting better at and some of these technologies help a great deal, providing that transparency, helping to surface risk, perhaps, that the humans are either not looking for or maybe kind of, “I don’t really want to .Don’t tell me about that right now, we’re making good progress, let’s just keep going.”
Rob Bryant:
Yeah. Yeah, for sure.
Michael Young:
And it’s interesting if you look at, once again, different sectors there’s been a number of cases only in the last couple of years where they’ve done test cases in the legal industry. And what they’ve done is they’ve used real lawyers, human beings, to go and arrange different cases and effectively put forward and prosecute cases based upon historical data, and precedent, and so on. And effectively, the lawyers had to come up with a particular premise or proposition, or the way they were going to propose to argue the case.
Michael Young:
Well, they then pitted that team of lawyers against basically machine tools, computers, AI, and so on. And they found that humans were about 40% accurate and the current technology, which was a couple of years ago now, was approaching 90% accurate. And so, twice as accurate as the average human, and that’s not introducing any other kind of bias or optimism, or any of that sorts of things. It’s just that there’s things that technology is fantastic at, particularly if you’re collecting data directly from sensors. And so, it’s not like someone’s plugging in data, therefore you’ve got data quality problems. It’s actually some sort of sensing that’s going on. Could be repeated photographs of a particular location site, and so you can physically see the change and measure the change. And so, when you’re getting data like that, there’s no data quality problem. Often it comes back to that, we were just talking about the reporting quality problem.
Rob Bryant:
Yeah, reporting’s a really interesting one because, as you said, that’s traditionally taken up so much of the project manager’s time in collating, gathering and holding everyone accountable for providing that information to then forward as an update. So, coming back to your point… I want to come back to that point you raised earlier of the changing role of project managers and what technology does to change that role, to enable a broader range of skills to be brought into play. What are you seeing there, Michael? What do you see as either things that have happened in other sectors or opportunities that you’re seeing emerge in the construction sector on that front?
Michael Young:
I guess what I’m seeing around the world, and very strongly happening in Australia in particular, is there’s been this resurgent focus on project leadership. And so, if you think about the full range of skills the project manager needs to have… If where we, in the future, move towards automated scheduling, automated risk identification management and automated reporting, a lot of this technical or harder skills that the project managers have traditionally learned, that’s all taken care of now by these systems.
Michael Young:
And so, what we’re seeing is a real shift in a focus on leading the project team sale, leadership focus, stakeholder engagement, communication, and in particular a lot more focus around change management. And so, typically around the world what we’re seeing is a shift towards a greater focus on the benefits that the project delivers and an increased focus on ensuring sustainable outcomes. And so, in a technology sense, building a system is not good enough, you need to actually have people using the system efficiently. And so it’s a shift from your sort of on-time, on-scope, on-budget, to-spec kind of scenario more towards does it deliver the outcome we want?
Michael Young:
And we’re seeing, particularly in government over the years, shifting their focus, too, even in construction. It’s not just about building the building, it’s about is it being used and is it actually improving… In any case, let’s say a hospital. Is it actually improving healthcare outcomes? And so, their focus is shifting very much towards the outcome and, of course, a project manager needs to adapt because just building the building and doing that traditional hardcore time, scope, quality kind of project management doesn’t cut it anymore. It’s the focus on the outcomes, change management, and in particular engagement in leadership.
Rob Bryant:
This is less transactional and far more ingrained in the full life of the project, the life cycle of the asset in that respect. So, by adopting technology, project management’s actually becoming part of the solution and then employing that and opening up the adoption as well, and then ultimately the improvement of the outcome.
Michael Young:
That’s right, yep.
Rob Bryant:
That’s fantastic, and Brad I know there’s some areas here that you’d be keen to provide some commentary on, particularly around that life cycle. But can’t this concept that project management is no longer limited to a transactional stage of construction, but that we’re actually talking about the full life cycle of the asset and how technology assists from the beginning through to the, effectively to the decommissioning of that asset?
Brad Barth:
Yeah, that’s right. And you see trends like digital twins, right? Where we want to, as an owner we want to create not only a more efficient process as we’re going through the design and construction of that asset, or even, back to your point, back to the conception of that asset and start to track all of the… Both the planning side and the outcome side of that whole equation, both of those metrics inside the model itself. So if you take a 3D model, what makes it a digital twin is not just the 3D representation of it, it’s capturing all of the assumptions that went into the construction of that thing, capturing all of the as-built results, outcomes, if you will that resulted from that construction process, and that’s going to help you manage that asset more effectively for the rest of its life, right? Because if you look at the cost of the asset, the engineering and construction stage is a little bit like this and the other 30, 40, 50 years is continued cost relative to operating and maintaining that asset.
Brad Barth:
So, starting on a good foundation and coming out of the end of construction with good information that can be not only leveraged for the life of that asset, but then leveraged on other assets that are similar or have similar characteristics. That’s where that whole digital twin, and it doesn’t have to be a digital twin, just the digital approach of capturing that information in a reusable way, in a systematized way, just becomes so valuable.
Michael Young:
And I guess the other thing, too, is that obviously we’re different people involved with value engineering and various practices around that. I guess what I’m talking about is it is way, way beyond that. It’s not just to do with the actual building itself or what it’s designed to. This is all around the organizational change to make sure people adopt the practices and the organization achieves the strategic and commercial outcomes that they’re chasing. So we’re talking more strategic and more, I guess, change-focused rather than necessarily focused on the input.
Brad Barth:
Yeah, and that’s quite a challenge in this industry, right? Because at the first sight of schedule overrun or cost overrun, the tendency is to descope the project, which then cuts into those economic benefits or whatever the perceived benefits were of that asset. You start to cut those down in order to stay on budget or stay on schedule, and ultimately that’s… From the owner’s perspective, achieving the scope that you, when you got approval to fund that project there was an economic business case that you had to make to get the funding for that. And often times, that gets whittled away as you go through the construction process, so our job in the industry is to not let that happen, right?
Rob Bryant:
Right, to keep that front and center through the full duration. Another question we’ve had come through, which ties back to a topic we touched on before, is the contracting methodologies and the relationship that has in terms of project management. And again, technology. How do we implement more effective, arguably more effective contracting and smart contracting through technology? And the role that that has and the role that project management has through that as well. Thoughts on that? Michael, perhaps starting with you on that topic of contracting.
Michael Young:
Yeah, I touched on it earlier. One of the challenges we see with contracting is that a lot of the contracting models are, I guess, predicated on this getting 100% clarity on requirements or scope, and that’s what’s then articulated through a specification or the contract terms and conditions. So what it effectively means is that we need to have everything 100% clear right up front because a lot of clients like to work to either fixed price milestones or that kind of fixed price kind of model. And so, where that becomes a problem is that we don’t often exactly what’s going to happen or exactly how long it’s going to take until the day after the project is finished. And so, we only know because, when we look in the rearview mirror we’ve seen how long it’s taken. But we’re being asked to effectively estimate or guess right at the front. And so we learn a lot as we go through the project.
Michael Young:
And so, we find that a lot of the contracting models are quite flawed in their underlying premise because the assumption they make is that we need to have everything 100% estimated correctly, completely and fully known right at the start. The reality is that many of the projects we’re now doing, even in the construction sector, a lot of them are almost research and development activities. Yes, the way we assemble a building probably hasn’t changed largely, but we’re seeing new materials, we’re seeing new ways of assembling those materials or new technology that’s being introduced. And so, there’s a lot of research and development goes on, and those sort of contracting models don’t take into account for that.
Michael Young:
So we probably need to see either more iterative type arrangements, more agile type of contracting models. We see a little bit in the design construct kind of models but we need to work in a more collaborative model between owner and constructor so that we actually work collaboratively to develop an outcome that works best rather than effectively trying to get a bunch of terms and conditions and stitch up the builder or the construction company right at the start. That model’s really not quite working when we’re living in a world that rapidly changes all the time.
Rob Bryant:
Yes, and I think we’ve started to see that. I know at InEight, Brad, we’ve seen some of that go through to the requirements from contractors as much as we have from owners. What are you seeing there in terms of how that’s changing the role of the project manager, potentially?
Brad Barth:
Yeah, for sure. The owners, I think, invariably want to work more collaboratively with their contractor partners, right? So it’s, to Michael’s earlier point, you’re seeing less and less, especially with the big projects, less and less of the, “Hey, let’s go through a year of design and engineering and then go into construction for three years.” Things are just moving too fast now, technology has changed so that kind of waterfall approach kind of fell by the wayside a long time ago in our world, in technology, as we’re creating software. But you’re starting to see that kind of start to get whittled away in construction as well. More iterative, and even more shared risk models, right? Where the owner and the contractor are sharing the risk in different ways, which is kind of putting some pressure on the legal support system for the industry that has to change the way they think about contracts in general.
Brad Barth:
But I think the, back to how is that changing the role of project manager, I think there’s always going to be, tying this back to the AI… I see some of the comments there. AI is going to help, certainly as we capture and validate the assumptions that went into project X and project Y and project Z, leveraging that on future projects. So it’ll make more of that information available in the conception stage so when projects are being conceived and those initial budgets being developed and the schedules being developed, they can set proper expectations for those things in the first place.
Brad Barth:
But it’s always going to take… That can’t completely go to a machine approach. Humans are always going to have to interpret that information. I’ve never been particularly with the term artificial intelligence because it’s kind of… It’s artificial, that came out of nowhere, right? But machine learning, particularly at InEight, we’re very much interested in how we can leverage machine learning to take all that information that a project manager in today’s world has to sort through and make some sense out of, how can the technology do that for him or her? And surface things that you just don’t have time to do, find patterns in the information that if you spent all day long doing that you might find those patterns, but nobody has time to do that.
Brad Barth:
A great example is, more from an estimator’s perspective than a project manager’s perspective, but you’re seeing… It used to be estimators, a big part of their job would be to do quantity takeoff, quantity survey. So they’d roll out the plans and start doing the dimensional takeoffs. Well, all that information now is in the 3D model, or most of it, I should say. So the skillset of an estimator is evolving more towards you need to know how to interrogate 3D models. You need to know how to manage data because you jump into that 3D model and you can get overwhelmed with millions and millions of data fields and information you have to sort out. So that’s an example, kind of that transformation that’s happening, whether it’s estimators, project managers, field engineers, whoever.
Rob Bryant:
Yep, yep. No, that does make sense. Now we could probably keep expanding on some of these topics and keep rolling for the rest of the afternoon, but just as we start to think about wrapping things up, what are some of the roles that the people listening might be able to play in this digital transformation? We saw that there’s 20% of our audience at the beginning who felt that the industry was keeping up. The rest either weren’t sure or didn’t think they were. But across all of those perspectives, what can people do… What can project managers do to become transformational pioneers around digital adoption? So, Michael…
Michael Young:
Yeah, so there’s probably… A couple of things come to mind. Often what you find is, whilst every organization’s got their way of working, their way of doing things, and so on, often you find, and certainly all of the projects I’ve managed, large projects, often you find that as the project manager or program manager you’ve got pretty much a huge amount of say as to what you do on that next project. And so it comes down to why you coordinate it, plan it, and so on. And so, certainly what you could do is start using or applying some of those tools in some of those projects.
Michael Young:
But for firms more broadly, I think it’s a case of do some proofs of concept, do some prototyping or testing, and so on. Now it’s obviously going to take a few different parts of the business or the organization. Obviously, you’re going to need the IT folk to assist, but you also need to think about data sources and get the various people on the project and engineering sides involved as well. And so, the easy step is to do a prototype or a proof of concept or some sort of test. One thing, different organizations I work with, I advocate that what they should be doing is spending a percentage of their project budget on that sort of sandbox kind of setup, so you’re doing prototyping, testing, proofs of concept or a range of different things and you’re running those projects all the time in that organization, because otherwise you just keep doing what you’ve always done and you don’t have a vehicle or a mechanism to actually innovate and change.
Michael Young:
Different firms have what they call skunk works. When you look at the way that the Googles of the world operate, what they do is they have these little groups, little think tanks, skunk work, sandboxes, where people basically test and prototype and do all of those sorts of things. And then if it looks like it’s going to be viable and workable for that organization, it’s then implemented as part of the why the organization works moving forward. And so, it can be applied at those two levels. One’s the project level, but also at that organizational strategy perspective’s important as well.
Rob Bryant:
Okay. Brad, your closing thoughts on that.
Brad Barth:
I think my advice would be, sometimes when we talk about terms like digital, or innovation, artificial intelligence, machine learning, these things sounds kind of daunting, like they’re major changes. And I think, set all that aside, the essence of it in the opportunities for improvement I think, in our industry, is mainly around getting better at modeling expectations. Where we talked about it at the beginning, setting the right expectations and the budgets and the schedules, and too often I think we do a great job breaking the work down into manageable chunks and coming up with costs and schedules and execution plans for each bit of scope, and we manage the outcome but what we forget to do is validate the assumptions that went into that. So we thought it was going to take this long and cost so much, it cost something different and took longer. So we know that. We kind of have to know that to do our job, but we don’t capture the why’s, right? We don’t capture the assumptions that went into why was it different so that we can improve that model.
Brad Barth:
It’s kind of like weather forecasting. I liken it to weather forecasting. Forecasting, which is really what estimating, or budgeting or scheduling is, right? It’s a forecast. But you can’t just predict what the weather’s going to be like on Friday and then just record what it was. You got to have models that continually get better by validating the assumptions. What went wrong in that model? Let’s make sure we don’t let history repeat itself the next time. And digital helps you do that, right? Digital helps you do that faster, it helps you work more flexibly, it helps you share the information easier. So digital’s just sort of a means to an end, right? But it’s still, fundamentally it’s all about creating those expectations and tracking, validating the assumptions.
Rob Bryant:
Fantastic. Well, we’re just about up on the hour. It sounds like the future is bright for project managers in terms of the opportunity to adopt technology and perhaps increase the value of project management even further by drawing from the past, presenting the data to help inform decisions, and elevate the role as well, Michael. I think that’s one of the most exciting aspects of it from a PM point of view for all those practitioners is to see how their role could actually be elevated significantly by the adoption of digital technology.
Rob Bryant:
So, wonderful to have you both with us today. I think there’s more in this that we could explore at another date, so we might look at setting up a time and broadening the panel and continuing the debate and discussion. Some fantastic questions from our delegates today, so thank you all for those. It’s been a great hour of exploration and discussion. I hope you’ve all got something out of it and some things to take away, and look forward to seeing you all again next time.
Rob Bryant:
So Brad, Michael, thank you.
Michael Young:
Thanks Rob, thanks Brad, and if you want to continue the conversation hit me up on LinkedIn and I’ve written a couple of articles on a similar kind of topic, so check me out on LinkedIn and I’ll… Happy to chat.
Rob Bryant:
Fantastic. Thank you very much. All right.