Welcome to the infrastructure podcast. My name is Anthony Oliver, and in today's podcast, we will be expanding our minds to hear the latest thinking on how the infrastructure sector is accelerating its journey towards digitization, embracing data and building infrastructure intelligence. The podcast is recorded in Singapore at the 2023 Bentley Systems Year in Infrastructure event at Marina Bay Sands Hotel. Singapore's 50-year infrastructure strategy makes it an inspiring place to discuss planning and delivering nationally significant investment, focusing on sustainable solutions that protect the environment and cut carbon emissions. The sector needs to use AI and data analysis to make better decisions. It's my pleasure to welcome Greg Bentley, CEO of Bentley Systems, who has been on a mission for over three decades to help the infrastructure sector go digital. Greg, welcome to the infrastructure podcast.
Anthony, thank you. Cheers.
We're back in Singapore for the Year in Infrastructure, which celebrates projects leading the way towards full digitization. You've said this is one of your annual highlights. What makes it so special?
It's special to be in Singapore after several years, due to both the quality of infrastructure and the quality of going digital here. My favorite part is the meet the finalists aspect, where I study most presentations and ask questions. Learning more always impresses me further by the projects, which is very stimulating and gratifying.
And they're from all around the world, of course, aren't they?
This year, out of 36 finalists, 19 are from Asia, seven from China. So the majority from Asia as we sit here in Southeast Asia outside China, which is really impressive.
Singapore has embraced BIM and data across the asset life cycle. Have they achieved it, and are they still leading the world?
When you use the qualifier across the asset life cycle, I think so. It depends on the appetite and ambition of owner operators, and only in Singapore do you have the time horizon, like the 50-year plan, to think about infrastructure across decades. Going digital, or infrastructure intelligence, to gain compounding value from engineering data is a difference here, and data works harder here than anywhere in the world.
Maybe one way it comes about is to bring people to Singapore to see the difference.
I've lost track of how many Year in Infrastructure events you've hosted, probably more than 10. Over those times, you've seen huge change, but it's not just about speeding up; it's about delivering value across the whole life cycle of assets. Is that really what's changed about digital engineering recently?
I think so. When we say infrastructure engineering isn't limited to capex, and stepping back, changes at Bentley Systems include introducing industry solutions, now eight total, all including monitoring, IoT, asset operations, and capex aspects. A solution requires an asset life cycle solution, with more focus on owner operators, who are 50% of our business. The value potential is for owner operators and their constituents, which is a welcome outcome.
I think so. All value occurs during operations and maintenance; capex is the cost.
Notwithstanding the need for efficiency and building to the right price to start, which is always a good place.
I don't want to fail to say that Singapore has reinvented capex too, but it's the ambition of owner operators. For example, the Tuas Water Reclamation Plant has won many Going Digital awards during project delivery. This year, submissions by contractors credit digital twins from the design process and 4D modeling, which has become the norm in Singapore. So Singapore has made great strides in capex, but opex progress is even more distinctive.
This year your keynote theme is around moving towards infrastructure intelligence. How are you defining this infrastructure intelligence?
The data working harder and generating compounding value. The reason it's top of mind is that everyone is marveling at generative AI, like language models, and understanding that existing data has a whole new dimension of potential value for training machine learning.
And that's true here as well. But you say that's another source of compounding value from infrastructure engineering data, and there are other strategies that even before generative AI potential compound the value, all infrastructure intelligence strategies.
So you call them the building blocks that you build on top of the data to access value. This year is groundbreaking for us in infrastructure intelligence. Data is the foundation, digital twins are the building blocks, and infrastructure intelligence describes the strategies to glean value from data through digital twins.
One of the other things you've said is the power of technology reducing costs across the life cycle and backfilling the growing shortage of skills. That's a key element of technology for you.
It is, and this is the first year where in our Going Digital awards we've asked submitters to quantify engineering savings. For finalists, it's a median of 18%, which is significant in helping cope with the engineering resource capacity gap, where for every 10 infrastructure engineering jobs there's a job opening.
So what are we going to do about that? Going digital and our finalists here have terrific digital advancements to advocate and learn from.
Well, and that includes engineering professionals. We have instances in Bentley Systems of using GitHub Copilot for software engineering, which has made engineers more productive and enjoying their jobs more, with less drudgery. We're confident we can achieve the same in infrastructure engineering, which can help attract future engineers and address the capacity gap.
But in order to do that, you have to embrace data centricity, which is leveraging digital capabilities to drive infrastructure intelligence. How would you describe data centricity?
Data centricity is a prerequisite. We have to open up dark data, or digital components, that can be reused, especially for machine learning, needing to be aligned, queryable, and semantically organized. Our Bentley infrastructure cloud can do that, and data centricity sets you up for compounding benefits from generative AI and other strategies.
I like the concept of dark data. It's the stuff which is really useful that you perhaps don't know about or can't access.
The dark data is all the work in modeling and simulation unless it's in our iTwin platform. For example, files delivered by engineers are used to open applications, but never after the project is finished, so that's dark data. Opening it up has much to gain over the asset life cycle. With generative AI, using digital components on other projects adds another dimension.
And if you ask me about my favorite project here in the Going Digital awards, it's the Hyundai project where they faced retirements in their plant structure designing group. They had 1,680 designs of big pipe rack structures, and never reused anything.
Right, imagine you were the junior engineer told to look through 1,680 designs. No one would stick around for that job, but machines don't care. At Hyundai, they used a supercomputer and a data scientist with three different kinds of AI to classify projects, generating 27 million potential cases, and when a new project comes, the AI recommends which existing designs can be reused, eliminating drudgery. This revealed data that was dark before.
The great thing about being here is getting up close with projects. I've just spent time with the guys from the new Everton stadium in Liverpool, which has embraced digital systems and data from day one to transform construction and maintenance. Is the use of modern tools for modern methods of construction success for going digital?
Modularization and design for manufacturing and off-site fabrication, on-site assembly, is a case in point of reuse of digital components. 4D modeling and construction simulation become essential. We need to further industrialize for project economics, and I commend Laing O'Rourke on the Everton project for their work on DFMA.
