September 21, 2018
By Greg Gies, Director of Product Marketing, Dodge Data & Analytics
Over the past couple of years, much of the literature on the topic of AI (Artificial Intelligence) in the construction industry focuses on the impacts both AI and robotics have had, particularly in the areas of design, engineering and construction of buildings. Despite this insight, there has been less of a discussion about how AI is improving the actual “business” of construction.
One business area where AI is making inroads into construction is in regards to business development. This might come as a surprise, since the thought of a business development manager’s role typically conjures images of personal, face-to-face selling and relationship building – work that most of us don’t think of as at risk of being displaced by robots or computers any time soon. Despite these changes and while some AI technologies like chatbots are becoming more widely adopted in this capacity, we still haven’t quite reached a point where business development managers need to worry about losing their job to a computer, since the industry still relies on the relationships and trusted partnerships established and nurtured by business development professionals.
That said, there are currently many tasks that require industry professionals to focus their attention away from the human element of the job. In this sense, AI is changing the dynamic nature of the business and helping to foster greater collaboration and trust among owners, architects, contractors, tradespeople and manufacturers—an exciting proposition.
While it’s not as visible to outside observers, business development managers spend a significant portion of their time sifting through construction documents looking for opportunities that are a good fit for their product or firm. Unfortunately, this work is so time-consuming and costly that managers often rely upon imperfect rules of thumb and best guesses to decide whether or not to pursue a project instead of precisely evaluating the project by fit and profit potential. This often results in lost productivity or sub-optimal profitability, as best guesses are often wrong. With the severe shortage of skilled tradespeople, this problem is exacerbated, as already tight profit margins are squeezed even further by higher labor costs.
In order to combat these issues, industry leaders are turning to AI to serve as a kind of decision support system to uncover insights buried deep within complex, voluminous construction project plans, specs and addenda that all players in the industry analyze in order to make decisions in bidding and preconstruction—decisions that directly impact the profitability of projects with razor-thin profit margins.
Specifically, we’re seeing Natural Language Understanding (NLU) and Machine Learning (ML) technologies used to classify and extract data that historically required a human to locate. As these technologies are able to “read” these documents and uncover data previously “hidden” from the view of computer algorithms, it has become much easier to accurately identify profitable projects by drilling down through interactive data visualizations to sift through hundreds of projects in only minutes.
Through these capabilities, managers are primed to make better decisions about where to allocate resources, and are therefore able to maximize the profit from each project their firm undertakes. While marketing, sales and business development teams previously had to dig through project documents for hours, it will now take them only minutes with a few mouse clicks, increasing productivity and saving time, energy, resources, and cost while maximizing profit through better decision-making.
In the near future, we expect that manufacturers and contractors will be able to evaluate the profitability of future projects based on machine-generated estimates of the quantity of product or labor required for a project rather than relying on imperfect metrics such as total project value or total square footage, as is common today, that rarely correlate to the revenue and profitability potential for a specific manufacturer or contractor.
With the rise of cloud computing and mobile communications, the construction industry is embracing the use of information technology as never before. It’s critical for construction business leaders to understand how AI can be applied to their own businesses—otherwise they will find themselves left behind with either a large cost disadvantage or lagging innovation in terms of new value-added products and services.
About the Author
Greg Gies leads product and content marketing for the construction market intelligence firm, Dodge Data & Analytics. Prior to joining Dodge, Greg has held a variety of sales, product management and marketing roles at Boston-area technology firms where he has written and presented on a range of document management, data capture and machine-learning software technologies. He earned degrees in management and economics from the Olin Graduate School of Management at Babson College and Indiana University.