In Part I, Robert Shear, vice president of marketing and strategy, OpenSpace, shares how he’s always been at the intersection of digital workflows and the real world. He also talks about how to foster a culture of innovation in the workplace: “Make it relevant, take a portfolio view, and don’t get caught in the trap of just talking about the future.”
In Part II, Shear explores why he’s most excited about technologies that will help us track and quantify field activity and progress. “AI and machine learning help us connect patterns to the results,” Shear says. “And then our next job gets better than our previous job.”
Dr. Burcin Kaplanoglu, vice president, Oracle Industries Innovation Lab, led the discussion.
RS: I’m most excited about technologies that help us track and quantify field activity and progress, including drone or laser scanning solutions, and many others, including simply clicking on a photo on your phone. There are lots of ways to track progress objectively and quantitatively.
This is kind of like our industry's GPS moment. We've spent decades creating intricate, beautiful maps, and incredible BIM models, but we never knew where we were, and we never could say, "I'm here."
We're now at a point where we can know where we are objectively. I'd call this a GPS moment for us. And if you think about life before GPS, you had great maps, but you had to remember where you were, including looking at the street signs. It all worked out, but it was very different.
So, yes, it's a lot easier to know where you are and get places now. But the more interesting thing is the follow-on businesses that emerged once GPS was in place: Uber, Strava, Waze…you name it.
We’re at that moment where we're going to be able to quantify construction progress and connect the real-world situation explicitly to our plans and models. This means we’ll be able improve and get faster.
Imagine Strava for middle school renovations across the country. You can see how you compared to everyone else based on how many classrooms you built. You can imagine all these emerging things that start helping us close the loop in construction and start improving in leaps and bounds.
After being with Autodesk and helping build things that help people make these intricate, beautiful maps and visualize them, I’m really excited about finally connecting those maps to reality.
RS: Maybe take a step back and ask: "What's my definition of AI and machine learning?" The terms are often overused and misused. In my view, AI and ML are simply a pattern recognition and pattern matching technology.
You don't have to teach it the pattern, which means you don't have to codify the pattern ahead of time, you can let it learn the pattern. And oftentimes, AI learns patterns that you didn't even realize were there, so that's the power of it.
This is really pattern matching. The good news for us is that construction sites are full of patterns, from sets that are six inches on center to spreadsheets, specs, contracts—whatever—the patterns are everywhere.
If you think of an experienced super project manager, who just knows when a project is on or off track. How are they doing that? It's patterns, right? They're coming in, and they're seeing stuff they've seen before, they go, "Oh, let's watch out for this." Or, "Oh, good, I'm glad that was done."
There are going to be huge benefits of AI and machine learning in construction, largely because it’s such an unstructured data set. It’s the mother of all unstructured data sets. The more we're able to learn, define the patterns, and connect the patterns to the results, it's going to be the next level. It's almost like capturing reality is like the GPS.
AI and machine learning help us connect patterns to the results. And then our next job gets better than our previous job.
In the short term, we're going to go through the hype cycle; everyone's going to claim it, and there will be some cool quick wins. Long term, it’s going to transform the industry, probably as much—or more—than any other industry.
If you think about other industries that have grown up around digital information from the start, they've sort of built structure into how they do it. That's the only way you could this stuff. You started with a structure and then you build out.
Construction is like the real world; it's messy, it's complicated, and there's no way to retrofit these patterns or structures onto it. You learn from the process. In the near term, we're going to see the ability to search for things in a job site that you never knew you wanted to search for before.
You don't have to say, "Look, the seven things I want to search for are generators, porta-potties, and stacks of drywall”. Instead, you can go in and teach the system quickly how to find things. That’s going to be short-term.
In the long term, you're going to be able to quantify and optimize projects across a portfolio and projects over time. We're going to see “Strava for construction”. We’re also going to see certain trades be really recognized for their excellence and get paid more.
Contractors will share the books with their owners and be able to go much deeper into a collaboration because it's going be more objective. You don't have to hide or worry about getting sued as much because you can provide more transparency and quantify your excellence. Therefore, you can focus on getting better.
See innovation in action at the Oracle Industries Innovation Lab.
Read more Trailblazers articles here.
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Corie Cheeseman is a senior content marketing manager for Oracle Construction and Engineering.