Data science is something we’re hearing about more and more, typically concerning how it will change a few specific industries. For instance, we know that healthcare stands to improve dramatically as hospitals gain more ability to track and analyze patient data. And we know that data science is now driving modern marketing efforts, to the extent that we spend our days interacting with brands and advertisements specifically designed to cater to our taste. But the truth is that, thanks in large part to a push for education and innovation in the field, data science is now relevant far beyond a few select industries — and is increasingly being applied in construction.
As the importance of big data in modern society has become increasingly clear, more and more school programs have developed to train people specifically in related disciplines. Even beyond traditional schools in fact, online educational institutions tend to devote a lot of attention to subjects like this that are in some ways more career-oriented than some popular school majors and degrees. A look at data analytics careers at Maryville University emphasizes this idea, pointing to the popular data science avenues (like healthcare and marketing) but also highlighting the different types of jobs data scientists can do. And it’s when we look through these jobs — data analysis, project management, time management and logistics coordination, market research, and more — that we can begin to see potential in-roads in construction.
You can begin to glean just from those simple, general job descriptions how a data scientist might be put to use in the world off construction. But to further explore the idea, here are a few of the specific ways in which the construction industry stands to benefit from qualified people in this field.
For any construction project to be as successful (and profitable) as it has the potential to be, resource conservation needs to be a priority. And as is alluded to in this post ‘The IoT and its Impact on Construction and Design’, better resource management is one benefit of the increasingly widespread use of Telematics. This term essentially applies to the use of IoT sensors and systems to collect data — about machine fuel consumption, shipment locations, idle hours, and potentially much more. And the analysis of that data represents one of the most fundamental ways in which construction benefits from data scientists. Even highly trained skilled professionals doing exemplary work can fall prey to accidental lag and inefficiencies that may be more the fault of machinery, strategy or processes than any individual. These inefficiencies can be identified and addressed, however, through Telematics and data analysis.
Better Informed BIM
BIM is actually another topic that was touched on in the aforementioned piece about the IoT in construction. As explained then, BIM is a form of modeling that uses data (often gathered by the IoT) to determine what’s required of a new construction project. In its early days, BIM could use fairly basic data — say, about pedestrian traffic in an area — to inform decisions in architecture and building planning. But data science is now so expansive and capable that it can be used to feed more in-depth insights into BIM. This allows construction professionals essentially to deliver buildings that better serve their purposes and surrounding environments — almost as if using a more advanced form of market research based on available data out in the world.
Meeting New Needs
Somewhat related to the general concept of BIM is the notion that data science can also help the construction industry respond to broader societal needs. A recent news piece based on input from a professor of architecture at Columbia University presented an interesting example of what this might look like. Specifically, it pointed to the pandemic’s potential impact on city planning and construction, with the professor suggesting that “pandemics are a spatial problem.” This is presented as a very big idea, connected to the “interconnections between social, economic and environmental problems,” and it seems to be implying a drastic worldwide shift in how we plan buildings for health and sustainability purposes. Ignoring the vastness of this notion though, the professor is making a simpler point, which is that planners, architects, and construction managers have an opportunity to respond to problems with new designs aimed at greater health and safety, more sustainability, and more comfort. Any change of this nature, however, will be driven by massive amounts of data and thorough analysis.
Discussions on automation in the future of construction remain somewhat polarized. On the one hand, we know that craft professionals will always be vital to the success of good construction projects. This is not an industry in which we believe that automated processes and robotics will entirely supplant human professionals. On the other hand though, some degree of automation is not just inevitable, but needed. Wired’s call for a “robot revolution” in the industry sounds somewhat dramatic, but also points out that “the average big construction project is overdue and over budget,” and that automation can solve those problems. That’s a difficult assertion to argue with, and it points to why we will almost certainly be seeing more use of automation moving forward. But this won’t simply happen on its own. Automated projects will be conceived and carried out based on thorough data analysis regarding inefficiencies and solutions.
In these and more ways, data science is poised to turn construction into a more efficient, effective, and profitable industry. And much of this transformation is already underway.