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In data we trust – or do we?

According to a recent blog post on the ARC Advisory Group website, data analytics are critical to the concept of IIoT. But what if we don’t trust what the data indicates? Asset condition monitoring and management applications have been the initial IIoT target, but are the benefits being realised?

Reliance on data may represent a cultural change in the standard operating procedure of an enterprise that requires leadership, change management, and plenty of patience.

In a recent magazine article, Burt Hurlock, CEO Azima DLI suppliers of condition monitoring solutions, compared the situation to the self-driving car.

Hurlock asked would you be the first to buy a self-driving car? Despite the availability of experience data available, Hurlock surmised the lag in adoption of asset condition monitoring systems is due to the human need to be in control.

In another recent Information Management opinion piece, Eddie Amos, GM/VP APM Software at GE Digital, stated that manufacturing companies are not realising the productivity gains expected from the digital enterprise.

Amos further noted that learning to trust the data is fundamental to achieving digital transformation.

For at least a decade, ARC clients have said that they have enough data but were lacking the ability to analyse it and therefore to leverage it.

A plethora of data analytics solutions are now available to help make sense of the data, but why do we not have confidence in it?  Is lack of understanding of how the decision is derived to blame?

Or perhaps it is human nature as Hurlock suggested, as well as proper design and implementation, and an understanding on the part of all stakeholders of what is involved. It also takes time.

ARC concluded that data will prevail in the end as systems are getting smarter all the time. Like climate change, the scientific data supports it and those that choose to ignore it do so at their own peril.

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