Measuring, predicting, and preventing safety incidents with AI

In our latest Trailblazers interview, we speak with founder and CEO of Newmetrix, Josh Kanner. Kanner shares his career background, his recommendations for cultivating innovation in construction, and why he sees so much potential in AI and machine learning.

Dr. Burcin Kaplanoglu, vice president, Oracle Industries Innovation Lab, led the discussion.

What is your current role and how has your career evolved since you started in the industry?

I am currently founder and CEO of Newmetrix. We’re a software company focused on bringing AI to the global AEC Industry to predict risk on all kinds of projects.

I've been in construction technology since the end of 2004. My career has evolved a lot. In 2005, I co-founded a company with Adam Omansky called Vela Systems to bring mobile technology to construction.

All that we had back then were computers called tablet PCs; the iPad hadn't even been invented yet. Back in those days, there really wasn't much construction technology going on in the field.

There was a wasteland of opportunity in construction where very few processes had been digitized. The thought of bringing technology to the field was regarded as crazy.

Now, there's more technology than ever, and a ton of opportunities for driving value in our global industry. As an industry I believe we’re still just getting started, however.

What’s your view of the state of innovation in the industry in general?

We’re in a golden age for construction technology. There’s more technology available than ever before, whether it's in the field or in the office—and whether it's in the design, build or operate stage of the value chain.

More investment in the industry is also creating more opportunities for construction firms of all sizes and types to innovate, create value, and differentiate themselves for their customers.

What are the biggest challenges to innovation?

It really depends on company size. For larger firms that are looking to be innovative, in some ways, there is too much going on.

A big challenge to innovation for larger firms is trying to figure out and prioritize where to focus attention, including preventing “app fatigue” in the field.

At the smaller end of the spectrum, numerous companies still have paper-based safety and other processes. Or maybe if they are doing digital processes, they have “digital filing cabinets”, where the data is collected and stuck.

There’s also a question of prioritization at the smaller to mid-sized contractors; it's the same challenges that we've had forever. The main competition is Excel or paper and there must be movement from either paper or paper-like processes to unlock value.

How would you recommend an organization foster a culture of innovation?

This is an area that I've spent a lot of time on over my career. The culture, process, and the people part of implementing any technology is critical.

It's not just the tech, it's asking: “What is the culture, and how do you reinforce it?”

There are some straightforward recommendations I would make. First, you need to know where there are certain technologies that are adding value.

You want to highlight and promote them within the organization. Consider this as “internal marketing”.

The way you create a culture is by driving it. It doesn't have to be to the use of the technology itself, but the technology’s outcomes should be tied to compensation.

There should either be a bonus or another way to celebrate a success. These are “incentives”.

Last, but not least, you must make sure you're not looking at technology in a silo. You need to prioritize where you're focusing your attention, whether it's coming from the top down based on certain processes that you want to drive across the company, or from the field going up. This is “executive sponsorship”.

For example, let’s say you want to introduce centralized reporting and analysis of safety. This would include streamlining the creation of safety with weekly safety reports that help drive engagement opportunities.

Leadership must celebrate a success, ensure the right incentives are in place, and make sure you're prioritizing attention from the management team.

What emerging technology do you see presenting the best opportunities for the industry? 

That’s why we started Newmetrix. Our concept focuses on how we can take the increasingly digitized data that our industry has and combine it in new and interesting ways to create insights that weren't there before.

You see that data coming from a whole bunch of places, including both back-end systems that we've had in some cases for years, like scheduling systems. Some new technologies are gathering data that was never there before, including 360 image capture, site cameras or data coming from IoT sensors in the field.

I see huge opportunities in the data we're analyzing. This includes breaking down the silos between those different pieces of data, bringing them together, and using the data to get insight into key areas of project risk, whether it's safety, quality, cost, or schedule.

The availability of the data, and the technologies that combines, analyze, and make predictions based off this data, are bringing the construction industry into the next phase of its overall value creation. Using the same kinds of techniques that manufacturing firms, retail, and consumer companies use is key to understanding and predicting risk and project outcomes.

Let’s go deeper into AI and machine learning. Can you walk us through certain use cases and their benefits?

We see a ton of potential around the analysis of safety data, in accessing what’s already collected by companies, combining it, and unlocking insights through a combination of analytics approaches.

For example, the number of safety observations that are completed in a week can be combined with payroll data as well as unstructured data like job site progress photos and other imagery.

At Newmetrix, we’ve built 100 ways to look at safety risk from the imagery that's coming from your 360 photos and job site photos. We combine that imagery in our predictive model to analyze structured data, like how many observations are done.

We also pull data to understand manpower on-site—whether it’s from your daily logs or from your payroll data.

"Using the same kinds of techniques that manufacturing firms, retail, and consumer companies use is key to understanding and predicting risk and project outcomes."

-Josh Kanner, CEO, Newmetrix

Predicting outcomes

Then we can predict outcomes on top of that data using our predictive analytics.

The net result: a safety manager or an operations executive can know on a Monday morning which 20 percent of their projects that week are going to have 80 percent of the safety risk. In the short-term, that's an opportunity available today for companies to reduce risk and save time by knowing which projects they should focus on from a risk standpoint.

Longer term includes combining that information with other project risk factors to create a concept of what a good or bad job is; combining safety, quality, cost, schedule, and understanding how those all interact—not just each as its own discipline.

Preventing risks

Risk prediction helps companies get insights across data silos (digital filing cabinets). The implications are huge for not just project delivery, but for the cost of project delivery, particularly in risk management and insurance.

Each of those areas of construction risk fall out into a major line of insurance. Based on which broker or a carrier you talk to, the cost of insurance in aggregate on a job can be anywhere from four to nine percent.

If you predict risk and manage your job with that predictive data, just like you can manage how you drive and get a safe driver discount, we see our customers starting to get safe construction discounts from their carriers. Their brokers understand how to use that information to better communicate the risk of the insured.

Doing a better job of identifying risk enables you to reduce your insurance and other costs on the project, but most importantly, to protect human life in what is, despite all the technology we have, one of the most dangerous industries in the world. That’s a problem we all need to keep working on.

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