In Part I of this month's "Trailblazers" series, Jit Kee Chin, executive vice president and chief data officer, Suffolk Construction, shared her professional background, her thoughts on innovation in the industry, and how organizations can foster innovation in their own organizations.
In Part II, Chin discusses why emerging technologies such as artificial intelligence will play a key role at construction sites, including Suffolk's collaboration with Smartvid.io, a construction-specific AI company.
Oracle Construction and Engineering Innovation officer, Dr. Burcin Kaplanoglu, guides the conversation.
JKC: Different types of organizations foster innovation differently. At Suffolk, our people are generally entrepreneurial, so the challenge is primarily how to channel this innovative mindset and energy.
We follow a disciplined innovation process at Suffolk. We collect and monitor ideas in a classic pipeline model and use a stage gate process to review ideas, pilot solutions, and finally, determine whether we should scale enterprise-wide.
We listen closely to the field, understanding their needs and pain points, and innovate around that input. Business sponsorship is also important; we always require business sponsors. Finally, we measure the value returned, whether that’s through efficiencies, cost savings, better experiences, etc.
Changing employee hearts and minds in any organization can oftentimes require a cultural shift. Organizations must help change their culture and show people that innovation is something to be valued.
Leaders can reinforce this through role modeling, messaging, informational events, employee recognition, etc. This cultural shift must accompany a formal program for people to buy-in.
People are often more open to receiving new ideas if they have a basic level of understanding. Innovation isn’t just a mechanistic process for evaluating and scaling ideas that happens in an isolated department. Professionals can give pride to new ideas by merging different experiences and views.
JKC: There are some technologies that have lots of potential but are still early in the maturity curve. And then there’s technology that may be reasonably mature but the impact might be incremental at the moment.
One such technology is virtual design and construction (VDC) technologies, sometimes referred to as “digital twin” technologies, created to “build” buildings virtually before the first shovel hits the ground on the construction sites. These technologies are quite mature with an increasing number of use cases.
Augmented reality and virtual reality technologies also fall under this category. These technologies have transformed the way people experience building both tangibly and intangibly. AR and VR lead to more streamlined decision making.
Many people think the potential for AI and machine learning is quite large, even relative to the other technologies out there. However, the degree of maturity is relatively lower because we're just starting on that journey.
Among analyses techniques, computer vision is probably the most mature. There are still some real hurdles to overcome including data volumes, data sanitization, and resource requirements.
Prefabrication and modular construction are also becoming more popular. These delivery systems minimize onsite labor and produce buildings in more controlled environments that increase productivity, improve safety outcomes, and result in more efficient builds.
Some will say prefab and modular have been around for decades, but now may be their moment, given the significant advancements in 3D printing, material science, and BIM technologies.
Finally, there’s the link between the build and asset management using sensors and other information handovers. Historically, the break between the construction and asset operations side has been stark, at least in commercial construction.
JKC: AI and machine learning will have a significant impact on the use of predictive analysis to mitigate risk. Construction management is inherently about managing risk—time, cost, quality, and safety risk.
For example, early on I realized artificial intelligence can greatly assist us in closely monitoring various components of active construction sites. We partnered with Smartvid.io, a construction-specific AI company based in Cambridge, Massachusetts, with a specialty in computer vision and data analytics.
Suffolk and Smartvid.io researched and developed a solution that could combine more than 10 years of historical project data (700,000 images from 360 projects) with other existing data, such as weather. We applied a predictive algorithm to “teach” the system the risks and factors that could lead to an incident on a project site.
If our research continues to prove out, a future system could alert staff of heightened risk situations and potential safety incidents so teams could take immediate action and neutralize the risks before safety incidents even occur.
So far, the results have been encouraging. Our predictive analytics model has identified one of five accidents with 80% accuracy, with higher identification rates if more false positives are accepted.
This proof of concept demonstrates the key role artificial intelligence can play in safeguarding workers and construction sites.
Other such insights from AI and machine learning use cases are currently being developed. Over time, the net effect should be to mitigate and predict risk. I look forward to being part of that journey.
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