Earlier this month in my Global Technology Director role for a client I was interviewed by BIM+ magazine about my views on the importance of data science in the transformation of the architecture, engineering and construction (AEC) industry. This blog post is based on that interview. The original can be viewed here.
What are the AEC industry’s big challenges with digital transformation?
The fourth industrial revolution is the first one in which the pace of technological change is outstripping business change and what society is able to cope with. In previous industrial revolutions society had decades to adjust to the pace of change.
The biggest challenges in this are the human, behavioural and cultural ones, and the need to bring people along on the journey. It’s about painting a view of what a changed world might look like to inspire them to participate. You cannot make people transform, they have to want it and understand the reasons why.
For example, many companies just roll out new software tools and three years later their people have reverted to their old ways of working because it’s more comfortable and familiar to do so. I really want to focus on questions like: What are we trying to transform? How does it work for us as a company? How do we respect cultural differences around the world? Only then should we map the technology into it.
What do you hope to achieve in your Global Technology Director role?
Digital transformation is something I’m very passionate about. To me it’s all about using emerging and innovative technology to create human and business outcomes previously considered impossible or, more excitingly still, never before conceived. A lot of people approach digital transformation from the direction of technology, but to me the technology is just an enabler of these outcomes.
I’m currently helping to spearhead a digital workplace initiative that will change the way the company manages knowledge so that it becomes a single global learning organisation. That means freeing up knowledge trapped in people’s heads to create a rich collective resource of wisdom. Another aspect of this is transforming ways of working to ensure the company’s employees can collaborate richly with anyone, anywhere, anytime and on any device.
My interest in this field dates back to my early career in software engineering and software architecture. Back then I was envious of engineers and architects who were designing things in the real world that you could touch and that might be around for hundreds of years. The software I developed might have been used by a million people but it probably wouldn’t be around ten years later, and certainly wouldn’t be remembered in history books. When I joined the AEC industry I wanted to combine my software engineering experience in user-centred design with real-world engineering to create the best of both worlds.
What are your views on the future of BIM (Building Information Modelling)?
I admit I am not fundamentally a BIM specialist, but BIM is about data and data is close to my heart. At both company and industry levels we need to move our mental focus beyond the design and construction phases to take in the whole-life piece and consider why that’s important. This is all about data science.
We might be creating some of the best buildings in the world, but that’s not all BIM is for. With new build, we need to think through factors such as the sensors we need in a building, the data we can consume and who is going to benefit from the consumption of that data. The majority of today’s buildings and infrastructure is still going to be around in 2050 and beyond, so that’s a huge data opportunity for us too.
Is client interest and awareness of BIM greater now than two or three years ago?
It’s better than two years ago. The interesting question is who the client is and are they one that cares? There’s a cost to BIM modelling and designing for the whole-life piece and the needs of building operators and building occupiers. My sense is that our industry and adjacent ones need to come together to paint a better picture of this longer-term view and not be so siloed in our thinking, which includes clients.
Which are the most promising computational and data technologies coming through?
In design, construction and operation the one constant is data and we therefore need to be developing a stronger capability around data science, machine learning and AI. There’s a pretty easy business case to make here. I’m very keen about ideation-based engagements with data-rich clients to find new innovative digital opportunities they might not even know are available.
In my experience in the AEC industry there are data scientists who are very aligned to particular sectors, whether that’s rail, water, energy, smart buildings or whatever, and other more domain agnostic data scientists who just love data and gaining new insights regardless of the use case. For an engineering consultancy, I believe the real opportunity is in bringing these two worlds together to create a cross-company capability that can really leverage and support everything it is doing across all of its disciplines and sectors to unlock these data opportunities for its clients.
What key efficiencies can machine learning bring to the built environment?
The health and safety use cases are very clear, for example using machine vision to ensure that people are following the correct behaviour on site. Another use case is using machine learning to optimise building space, where analytics can enable us to overlay a model with things like crowd data and environmental data to optimise the performance of a space.
When you make the step from smart buildings to smart campuses and smart cities, there’s a lot that can be done with machine learning and real-time data to improve vehicle flows, people flows and other movements to reduce congestion, for example, in ways that previous technology just didn’t allow.
Does that remove a burden from designers?
The ability to automate some of the more repetitive tasks can free up designers to be far more creative. My definition of digital is about human outcomes, so automation can unlock some of these opportunities. We have reached a point now where we can almost assume that the technology, whether it’s AI or VR or BIM, is going to be able to deliver whatever we dream up, so now we can focus on the outcomes, which is a very exciting prospect.
What is the importance of digital twins?
Scenario modelling is the most exciting part of this, as you can try things out on a digital twin that you could never do to the physical asset, yet still gain the same insights and apply them to the real-world asset.
What is the role of digital technology when designing responses to the climate crisis?
In technological terms we need to link everything we do back to positive outcomes that address the climate emergency. This comes back to a large extent to data: you cannot accurately measure the impact we’re having on the planet, or the damage that’s been done that we have to mitigate against, without data. Putting sensors into existing infrastructure is a key element, as well as going back to first principles and assessing whether the materials and processes that have been in our industry for decades are appropriate for tomorrow’s world.
This is also about educating clients. Some might want a new building when in fact they would be better off repurposing existing assets to improve sustainability. There’s no simple answer to the climate emergency, but it should now be a big driver behind all of our work.
There’s a lot more to do in responding to the climate crisis. I’m incredibly excited to be using digital technology, techniques and transformation to help clients play their part on this journey.
Tony Scott is the co-founder and director of Scott Communications. He is also co-founder and CEO of artificial intelligence and data science specialists NeuralRays AI and a founding member of ACE‘s Digital Transformation Group.