On-Site Magazine

How IoT, machine learning and artificial intelligence will drive better decision making in construction

By David Bowcott   

Risk Management Software

The greater availability of construction data and improved methods for analyzing it are expected to improve outcomes for contractors. PHOTO: Adobe Stock/Pinkeyes

We have now had several years to assess how technology will change construction. We’ve seen a technological onslaught with thousands of solutions being brought to market claiming to make the industry safer, more productive and less risky. Like any explosion of technology, the dust does eventually settle, and you begin to gain clarity around what is and isn’t working. Within the construction technology space, it really does seem like the puzzle pieces are starting to fall into place in terms of what solutions will deliver the greatest impacts and which will be left behind.

At Aon, we’ve been doing our best to keep up. In 2017 we established a Technology Assessment Panel to help our clients better understand which technologies appeared to have a strong chance of impacting the real risks facing their business. Nearly every week we would look at a new technology that claimed to impact risks in the design, construction and operations phase of a built asset’s life. Over time we started to see how these technologies could be categorized and how they were beginning to interact with each other to create some potentially profound improvements in construction risk management and productivity. After almost five years of running our assessment panel, there are clearly two categories of technology that appear to be separating themselves from the pack. Those technologies are Internet of Things devices (IoT) and machine learning/artificial intelligence technologies (ML/AI).

To understand why increasing the speed at which you can make better decisions represents a profound technological impact, it’s a good idea to take a brief look at the research on decision making. If you haven’t already, you should have a read of Thinking Fast and Slow by Daniel Kahneman. Kahneman is a psychologist, economist and Nobel Prize winner who extensively studied the psychology of judgement and decision-making. The book represents an excellent summation of his and his collaborator Amos Tversky’s work in this area. Kahneman has basically uncovered that human beings do not appear to be the best decision makers because of a desire and/or animalistic need for rapid decisions. His findings indicate human beings have two systems for decision-making. System 1 is a human’s fast, intuitive and unconscious thought decision making, sometimes called “gut” decision-making. System 2 is slow and requires conscious effort. Humans seem to have an aversion to quantitatively analyzing all the data before making our decisions, as his research also indicates we strongly favour the use of System 1 decisions.

Now, I’m sure we can all appreciate why we tend to utilize our System 1 decision making more often than System 2. Who wants to spend all that time crunching numbers and racking your brain to find the perfect decision, when you can quickly go with a decision that just “feels right?” Even the brightest minds of our time sometimes favour quick decisions, but when things go wrong, we often regret not taking the time to comprehensively analyze our decisions. 


In today’s world, we are beginning to witness the emergence of System 1 decision-making times done with System 2 analysis. Think about it, how often do you simply tap into your smartphone to augment your decision-making, thinking: “Maybe the internet has some information on this decision I’m about to make,” and very often you quickly find something that provides a better analytical framework for your decision. I can’t tell you how many YouTube videos I’ve watched to help me fix stuff around my house, return my computer to a normal state, and help me understand complex tax filing requirements. What previously would have taken hours to research now takes minutes as there seems to be a YouTube video for almost any problem that needs fixing.  

Now, imagine that rapid analytical input making its way onto your construction site. Imagine knowing almost everything that is happening on your project before making a crucial decision. Further, imagine having analytically driven cyber-advisory telling you the ideal decision derived from analysis of vast amounts of data generated on your job site. Well, that’s beginning to happen right now. We are seeing IoT devices provide almost full visibility into your job site’s risks, all reportable via your mobile device. With all of this data being co-mingled, and combined with data from hundreds or thousands of other job sites, we are further seeing the emergence of the predictive job site as machine learning and artificial intelligence algorithms get applied to both IoT and other sources of data to help you make your best decision. 

The future job site is emerging now via project IoT backbones, data aggregation technologies and associated ML/AI algorithms. These job sites will provide key decision makers the ability to make System 2 decisions at the speed of System 1 decisions. The result will be a material reduction in risk and thus a material improvement in productivity and profitability. Construction is an industry of managing the unknown unknowns and the acceleration of strong decision-making will make this often-unpredictable business more predictable.


In case you missed it, dive deeper into technology’s role in construction risk management by listening in on a panel discussion hosted by On-Site last month. David Bowcott; as well as Chris Gower, COO, of PCL Construction’s Buildings division; and Neil Banerjee, the senior vice-president of Operations at Matheson Constructors walk through the considerable opportunities construction firms can take advantage of.

David Bowcott is Global Director – Growth, Innovation & Insight, Global Construction and Infrastructure Group at Aon Risk Solutions, as well as a member of the Canadian Construction Association’s (CCA) board of directors.

This article first appeared in the June 2021 edition of On-Site. To read through the whole issue, click here.


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