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IoT and manufacturing - where the skills are and aren't

Stuart Lauchlan Profile picture for user slauchlan April 5, 2016
For manufacturers to exploit the potential of the IoT, they're going to need data science skills - and those are in short supply.

Dave Bartlett
Dave Bartlett

In the first part of this three part look at the Internet of Things and its impact on the manufacturing sector, Michael Porter, Bishop William Lawrence University Professor at Harvard Business School, highlighted what he saw as a tension between Boston as an industrial hub and Silicon Valley when it comes to who ‘owns’ the IoT.  Porter’s argument is that in terms of the industrial internet, the East Coast wins out over the West Coast.

That said, Silicon Valley is home to the data scientists who are needed to make sense of the vast amounts of data flowing in from systems of interconnected, smart products, as  Dave Bartlett, Chief Technology Officer, Current, powered by GE, notes:

Current is headquartered in Boston, epicenter for industry. We got to go after the data scientists. So we also have a presence in Silicon Valley. But one of the things I love about working for GE is that as our computer scientists work side-by-side with our engineers, we have a very successful program rotating our engineers into our data science group. Thanks in part to the entrepreneurial spirit we have in this country of people being willing to re-invent themselves, it’s a huge resource that we shouldn’t overlook. A lot of people want to step up to it. Combining those talents is really where the magic happens.

Glenn Baker, Global Director, Enterprise Strategic Manufacturing, Deere and Company, issues a warning that there is likely to be a skills shortage around the IoT:

There are not going to be enough data scientists coming out of university to meet the needs that we will all have. There is going to be an expectation from customers that your products are going to be connectable. Whether you use the data or not is probably immaterial, but there’s going to be an expectation that your product is connectable and that someone can get data off of it if necessary.

That’s going to mean a need for skilling-up and training operators internally, as well as providing them with the information they need to make decisions in the smart workplace. Baker explains:

The thing we’re relying on is being able to deliver information to the operator in a way that is much less intrusive than paper or having their hands occupied with an iPad or a tablet of any kind.

One solution lies in the area of augmented reality technology, he adds:

Augmented reality is one of the ways that we’re going to enhance operator training and take operators who may not have the skills sets and use that as a way to substitute that knowledge with information coming in through the cloud in terms of assembly. We have products that are built in 45 seconds and we have products that are built over 3 or 4 or 5 days. Being able to keep that sequence of events and operator methods requirements upstairs is almost impossible. So having augmented reality to augment the capabilities of our operators is going to be critical. Operators tend to rotate and with an ageing workforce retiring at an age where we need to refresh, it’s the only way we can do it effectively.

That need for data science skills is going to be crucial with the IoT, but the challenge here dates back a long time, says Baker:

When I started with Deere back in the late 1970s, I was told we were data rich and knowledge poor. The computer was going to be the panacea that was going to resolve all this knowledge and give us all this insight. Thirty years later we’re still data rich and knowledge poor and we see the IoT as being the panacea to provide the insights. I believe the most elegant IoT solution is the one that requires the least amount of data to give you the best insight into your business. That will require less integration between the data scientists and the operational people on the floor. But skill sets are going to be a critical determinator of our ability to advance this as rapidly as we want to.

Innovation and the USA

For his part, Porter points to innovation skills in the US as a key enabler of success and that these are hard-wired into the American way:

Unlike Germany and Japan, this country is a major software innovation center. In Japan, there’s hardly one major software company, Germany there’s a few. So we have this software, data, data analytics and enabling technologies that are very firmly embedded in the US. We’ve been having trouble competing with the rest of the world in the old paradigm. Here, if we play our cards rights, we’re going to have an opportunity to rebuild our competitiveness. That doesn’t mean it’s going to change overnight and all the jobs are going to come back to the US, but it does mean that this is an area in which the US is disproportionally competitive.

He adds:

We tend to be in the US a little more flexible. The ability to change things and redefine things and re-organise, we have more of a tradition of that level of dynamism here, compared to some other countries. That’s going to serve us well because this is a big change. This doesn’t just change technology, it changes the way that we work. It changes how you organise. It changes how you service. We have to relearn a lot of habits. If we can keep our US dynamism and not try to preserve the last century, then that’s going to serve us well. But make no mistake, there’s a lot of companies in China and Europe and Korea thinking about this.

In the final part of this series, real-world learnings from manufacturers around the IoT. 

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