As senior director of product management / R&D—architecture & security with AspenTech, Keith Flynn is more than just a long title. He guides product development for the process industries software/service provider, and advises those working in the industrial space to widen their skills—to develop holistic expertise related to the IIoT.
Today he shares his thoughts on the role of education in this IIoT era. Take a look…
Smart Industry: What’s the state of data-science education?
Keith: I think formal education in IoT is the next big movement coming. So many of the hot jobs of the future will be based around the IoT that a regulated, formal IoT education is inevitable and, frankly, critical.
If you needed a job done 20 years ago you’d find skilled people to do that job. These large automation and data-management projects would require a team of people with individual skill sets to deliver the full project scope and demand large financial budgets just for the installation and deployment. Consider the industrial world: we required electricians for wiring the assets and sensors, system integrators for the automation and controls, IT for the infrastructure and networking and then a separate team of database administrators and software programmers—with database and reporting skills—for the data-collection side. However, with the rapid change of the tech landscape, new skills are now needed all the time, requiring more than vertical-specific expertise.
Smart Industry: What are the new needs prompting these new skills?
Keith: Future IoT projects will be different than traditional automation or data-management projects. We will see projects that are smaller in scope (asset or sensor-based) and nimble when it comes to cost. This new structure will not be able to support traditional, full engineering/deployment teams like larger-scale automation projects do. Therefore, there will be a demand for smaller teams with broader skill sets to keep the deployment costs lower.
This extends beyond Industry; it is the reality across all sectors. The problems stay the same, it’s just that the tools have changed and rely more on cross-trades. We must combine the traditional project-deployment skills with new technology skillsets for evolution into one course and individuals need to be able to understand it all. Cross-trades ease the knowledge gap and everyone can speak the same language. It’s important when solving a problem and designing a solution to know all these different fields. That’s what will be achieved with an IoT education.
Smart Industry: What type of professional does this education produce?
Keith: If education programs are created that combine all the necessary skill sets for IoT projects, you can get relatively new graduates in the field and it opens the doors for smaller businesses to take advantage of the new tools of the trade, creating a demand for jobs with this skill set. The big industries can still afford to have people dedicated to one area of expertise, say an instrumentation tech, an electrician on scene and an IT person working together. Smaller businesses can’t. So, I think formal IoT education is going to become increasingly critical to level the playing field in technology jobs. If we cross-train, through an IoT education, smaller businesses will be able to afford to hire individuals devoted to both IT and OT and problem-solving will become much easier. They always said IoT will open doors for industry; you just need cost-effective people in the industry that can deliver it.
Smart Industry: How is this different from data science?
Keith: Simply put, IoT experts deliver data and data scientists consume it. Those who are employing data scientists have some means of getting their hands on the necessary data already, though it may not have been easy. Data scientists process the information and come back to them with a solution, although, to put the solution online, maintain it, scale it, and evolve it, you need a different skill set—IoT expertise.
In my opinion, I see data science as the second part of a two-phase approach. The industry has put the cart before the horse. Some won’t know what to do with a data scientist if they have no visibility into their organization’s data sources and process. The tools of the trade for data scientists is the data, but if they don’t’ have skill sets to retrieve or collect the data, then data scientists can’t to do their job.
Most businesses need the IoT skillset first. Data scientists are highly academic in the mathematical areas; they know how to model, build incredible representations, single order or multi-order equations, and can take data, look at it and see what’s happening. But they typically don’t have the skills to extract the data. If a formal IoT education comes to fruition, I think it would make perfect sense to do an undergraduate IoT degree, and then a master’s in data science. You’d be a unicorn in IoT! That’s what this evolution will look like.
Smart Industry: What will an IoT major look like?
Keith: It has to start in chronological order. It will need a sequence, starting with the classics, like instrumentation, teaching people how to measure things, what to measure, the basics. The courses will then move into teaching students how to transmit that information, which is IoT networking. DBA or database side courses will come next, teaching students how to manage and administrate information in the cloud.
I think this would make most sense as a two-year tech course, where semester one is E&I, semester two is networking, and the following year’s semesters are all focused on database and the cloud. This could even be tacked on as an IoT supplement to an existing engineering course. Combining engineering with IoT adds that problem-solving component.
Smart Industry: What background or skills people should possess before considering this kind of education?
Keith: Problem-solving…problems that span different trades. You need the ability to holistically see the entire solution to every problem. You need to be able to visualize what you measure, where you have to start and what you’re going to do with the data. You’ve got to be able to see the end-to-end problem and solution so that you can make informed decisions. Which cloud provider to use? What type of networking to use? What type of devices and sensors to use? The job of the future in this ecosystem is one where you have to be able to problem-solve in multi-dimension.
Smart Industry: What challenges are there related to IoT education?
Keith: IoT is changing so fast that formal education programs will need to adjust curriculum semester to semester and year by year. They’ll consistently need to be iterating on the program to educate students on things that are relevant. Now, that may stabilize within a decade, as IoT technology levels off, but it’s entirely plausible that what you learn in an IoT major today may not be relevant when you graduate. Even when I came out of my PLC course, nothing I learned in school was applicable on the field. The tech in today’s world is changing so fast, it will be hard to build a curriculum around it.
Another challenge is that you can’t just have these college programs and private schools popping up everywhere touting their IoT courses. You need something that is regulated. You need oversight on these programs to ensure that if an organization hires someone with an IoT degree, they get what they’re paying for.