Why the IIoT Demands More Flexibility from the WorkforceWhy the IIoT Demands More Flexibility from the Workforce
When it comes to preparing for the workplace of the future, you should learn as much as you can about as many things as possible.
January 26, 2017
“When I speak with government agencies, the first question I hear is usually: ‘how should I train people?’” says Richard Soley, Ph.D., executive director of the Industrial Internet Consortium (IIC). “I can say with absolute certainty: ‘I have no freaking idea.’”
That degree of candor is refreshing, giving all of competing theories about the job-creating and job-destroying potential of technology in general, and the Internet of Things in particular. But the fact that no one knows what will happen with jobs in the 21st century is itself instructive: It requires workers to train to be more flexible. (Note: At present, the IIC does not have an official position on training.)
Given our quickly-changing technological landscape, it is easy to find training that is quickly out-of-date. For instance, most universities’ computer science departments teach students Java because it is the most popular programming language. But who knows what will be the top programming language tomorrow? “Even 35 years ago when I went to MIT, they refused to teach you programming languages,” Soley explains. “They said: ‘We are going to teach you what programming is about, how to think about abstraction, and how to solve problems, and how to integrate things together. Once you have that, learning the programming language is the easy part.’”
The Biggest Challenge
Preparing the workforce for the needs of the Industrial Internet will place new demands on information technology and operations staff as well as the engineers who build machines. It also will require that those groups collaborate in new ways. The integration of IT and OT—informational and operational technology—is a struggle, but it’s not the biggest one. “Data analytics is going to be the biggest need in computer science for the next at least five years,” Soley says.
“I was talking to a senior executive at General Electric the other day, and he said our diesel/electric locomotives generate nine million points of data every second,” he recounts. “No single person is going to read that.”
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While professionals and most modern data-analysis tools struggle to tap the potential of such huge volumes of streaming data, progress is being made. “I will tell you that in all 27 test bed projects that are running at the Industrial Internet Consortium today, there is lots of data being generated, and many cases where we are delivering decision support to real people: doctors, people managing electric grids, and so forth.”
As the Industrial Internet gains strength, elements of Silicon Valley ethos are beginning to mesh with the culture of many industrial companies. “One of the reasons that Silicon Valley culture has thrived is that it recognizes the value of failure,” Soley says. “People understand that failure doesn’t mean that you are no good; it means you have learned a valuable lesson. If you build a bridge and it stands, you learn nothing. But if it falls, you learn not to use that design with those materials.”
Learning from the Past
People working in the Industrial Internet field must also find new ways to approach systems integration—essentially breaking a big problem, into parts, assigning those parts to teams, and then integrating the resulting solutions together. The Industrial Internet multiplies the complexity of this, adding connectivity to the mix of traditional engineering disciplines.
To figure out how to address the ever growing complexity of integration, engineers can draw inspiration by studying past systems integration examples, Soley says.
“My favorite example comes from a book titled ‘Twenty-First-Century Jet’ from Karl Sabbagh,” Soley says. The book relates a story about integrating engineers working on the 777 in the early 1990s. The project was running late and Boeing’s management hoped to cut the number of unnecessary meetings by removing a directory of the engineers working on the project.
There was also a learning curve when designing the aircraft because it was the first that was designed entirely online. “Everyday, you would work on the parts going into the airplane, and every night, the computer would build a simulation of the entire aircraft and find things that overlapped, and send an email to the people with overlapped parts and say: ‘you’ve got to solve this problem,’” Soley says.
A clever engineer who was working on the engines realized that by changing the design of the nacelle, he could redirect some of the airflow that was flowing over the empennage—the tail of the aircraft. When the engineer tried to pull up the directory to contact the empennage group, he couldn’t find it. “So he added a part to the nacelle. It started around the engine, and zoomed back several hundred feet and crunched through the empennage,” Soley says. “That night, the computer saw the problem and sent an email to him and the empennage guy and said: ‘you got to solve this problem.’ Bang! He’s in contact with him.’”
Within a few days, everybody at Boeing was using this strategy as a way to reconnect to the different engineering groups. “I love that story and it is a proof point,” Soley says. Integration requires new ways of thinking to drive collaboration between different types of engineers.
Forging the Future of Integration
But the subject of systems integration becomes more complicated when it comes to the topic of IT/OT integration, which requires new skills from both groups. This is a problem that many universities and industrial companies are working to solve. “What most people are trying to do is to take IT engineers, and add OT expertise, teaching them about Six Sigma, high reliability, high safety, security,” Soley says. “Or they do the opposite, taking OT engineers and teach them to learn modern programming languages and so forth.”
A better approach, however, would be to offer university training to teach both IT and OT domains simultaneously, integrating and testing the insights that both fields offer. “But I’ve been to dozens of universities and have nobody that is doing that,” Soley laments. “Because it is hard—that is the bottom line,” he adds. “Six Sigma, for example, doesn’t come from nowhere. There is a lot of data that proves it works. You have to do that all over again when you generate a whole new way of training. It is a hell of a lot of work, and it requires a high level of expertise.”
Still, the potential of the Industrial Internet is too great to ignore. “People are going to find new opportunities to connect things that nobody ever thought of,” Soley says.
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