IIoT: Technical vs. people skills

Weaving machine programmer

You want your factory to be IIoT enabled. You’ve seen the videos and read the case studies. It’s obvious: IIoT technologies are central to your digital transformation.

But where do you start? How do you start?

The technologies of IIoT implicitly demand people with technical skills. While we travel through an early adoption phase, some plant can produce the data we need, but we’ll probably have to augment other plant so that it can do the same.

IIoT lends itself to the technophiles; even though the barriers to entry are lowering, if you want to fasten a data reporting capability onto a machine tool, you’ll need to know what you are doing.

If we consider the area where IIoT is flourishing currently – condition monitoring and predictive maintenance – then the domain is populated by technical people, with technical skills, doing technical things.

Some installations are moving to a service-oriented model, where the manufacturer does not get involved with the IIoT at all. The IIoT installer takes care of data monitoring, analytics, reporting and communication, and merely produces processed data to be consumed by the client.

If we want to transform a factory, we shall need to think much more broadly than a predictive maintenance solution. The complex interplay of multiple machines, material handling equipment, finishing plant, assembly lines, etc., suggests that there will be an imperative for the rapid up-skilling of existing staff to become more technical.

But we know that technology projects often fail when the focus is on the technology itself. Of course, it is the potential of the technology that justified the transformation project in the first place; however, people are still central to the operations and they need to be brought along with the change if the change is to stick.

So, IIoT implementation initiatives need a people-centric approach to lead the development of people-skills. Lean is a good way of approaching IIoT adoption as it focuses on the principles of efficiency, supporting the development of appropriate behaviours.

With such behaviours in place, IIoT can be `relegated’ to a technology that serves what people really need.

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