While the construction industry may have struggled to achieve the same advancements in productivity from technology as other sectors, clearly there remains tremendous potential for change, writes Richard Harpham
As industry leaders, thinkers and technology providers come together for the 2023 NXT BLD and NXT DEV conferences in London, the intellectual effort and commitment to address the issues and opportunities across design, engineering and construction are still as strong as ever.
But, after a year of experiencing technological advancements such as OpenAI’s GPT, it can be disheartening to see the building production industry still struggling with issues such as delayed projects, budget overruns, and a continuing lack of integration between design and construction.
So, as we undoubtedly meet and beat ourselves up again, that the technology benefits experienced in manufacturing, aviation, and automotive, have not yet permeated the construction sector, I’d like to assert that it is unequivocally inevitable that these issues will be solved by technology.
The black art of construction management, that comes from decades of experience in making stuff work on the building site, is still more comparable to panel beaters in custom car shops than any modern automotive manufacturing environment
In this brief article, I want to look back, to look forward from my own experiences in companies like Bovis Construction, Infrasoft, Revit Technologies, Autodesk and Katerra, to share some thoughts on why we continue to stall in our attempts to radically improve building production outcomes.
Constructability and Prefabrication
As I’ve written previously, one of the core challenges lies in the disconnect between design and constructability, both in the processes and the software that supports them. Too often, design teams fail to consider the practical aspects of construction, leading to inefficiencies and delays. It’s not a huge surprise, as few architects are schooled in pre-construction, scheduling and project management.
My old building director at Bovis used to routinely greet me in the site hut with, “Have you brought another set of comics to review”, as I unrolled hours of painstaking drawing work on his desk. It was an unspoken truth that what I drew and what he built might not always match up.
The black art of construction management, that comes from decades of experience in making stuff work on the building site, is still more comparable to panel beaters in custom car shops than any modern automotive manufacturing environment. And we see that clearly in how numerous prefabrication companies, despite their potential, have faced obstacles in scaling their operations. As I’ve experienced, some of the most forward thinking ideas in prefabricated design solutions crash into onsite issues in fully leveraging their benefits on site.
Until industry stakeholders collaborate closely, ensuring that design better accounts for constructability, as well as embraces prefabrication, viable solutions to enhance efficiency and reduce project timelines might continue to evade us.
The reliance on memory and experience during pre-construction is a major roadblock to progress. During the last three years, it has become clear to me the construction industry must shift towards data-driven decision-making. And that data must be presented both as explicit instructions and implied opportunities to change actions at the time they can have the most impact.
Currently, the industry has had to rely on software that, at best, tells them what happened, not what is happening, and certainly not what is going to happen. If this were the banking or healthcare industry, it would be unthinkable not to leverage every data source in to as close to real-time as possible in order to find valuable answers or avoid catastrophic issues. In fact, even your car can now observe and consume data to make corrective actions to traffic, weather and obstacles in real-time.
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To catch up with other industries, software providers must develop the platforms that enable the capture, organisation, and utilisation of all data within and around a project. Then, by leveraging AI derived from continuous machine learning, contractors could make informed decisions, accurately estimate timelines and costs, and identify potential risks, thereby avoiding costly delays. Then, collaboration tools should more easily and ‘automagically’ facilitate seamless communication and coordination among project stakeholders, enhancing productivity and reducing delays. Surely this is no longer a debate, but rather a minimum requirement to advance construction productivity.
Collaboration for Success
One of the things I enjoy most about coming to conferences like NXT BLD is experiencing the collaborative attitude growing at the grass roots of our industry. This has not always been the case. Building a successful future for construction requires collaboration among all stakeholders, including architects, engineers, contractors, software providers, and regulatory bodies. By fostering this environment of open dialogue and knowledge sharing, we can collectively drive meaningful change.
Industry associations, trade organisations, and government entities increasingly promote collaboration and provide support for initiatives that drive innovation and productivity gains. This is one area of design and construction that we have improved and continue to get better at. Now we need to see the technology providers follow this lead and realise that success for the industry does not look like we all use the same brand of solutions, but rather that the solutions can both match our business needs and are capable of data integration across the whole construction ecosystem.
In conclusion, while the construction industry may have struggled to achieve the same advancements in productivity from technology as other sectors, clearly there remains tremendous potential for change. In recent years I have spent considerable time with tier-one general contractors looking deeply into data insight and collaboration challenges, to establish how machine learning and AI algorithmic technologies might address longstanding inefficiencies. The good news is that it is a target rich environment, with most data in firms still siloed across overly complex software stacks. But it’s not as simple as just adding AI tools to that stack. We must generate the right questions from emerging and new key metrics that are different from those we have relied on in the past.
The metrics that no matter will be found by constructability, leveraging data-driven decision-making, enhancing real-time visibility, and promoting collaboration. Software providers continue to have a crucial role in developing the solutions that leverage these metrics and help construction professionals transform processes.
Just as we were surprised when we first saw ChatGPT and GPT4, we’re probably going to be equally surprised by what we will achieve over the next few years, and I firmly believe we are just at the start of dramatic improvements in design and construction technology.