Industrial IoT must move from optimisation to transformation 

By March 2, 2018Product News

INDUSTRIAL IoT (IIoT) can be seen as a way to optimise existing processes and business models, for instance by achieving higher degrees of automation, or by avoiding outages with help of predictive maintenance.

But IIoT can and must be more than that. We have seen how new digital business models have disrupted industries like media, retail or travel - and the same will happen over time to industries like manufacturing, chemicals or energy.

Thus, at its core, the IIoT is not about achieving some percentage points of efficiency but about which companies will capture which portion of this trillion-dollar opportunity, and which companies will become an extended workbench of a predominantly digital value creation.

This means adopting the IIoT must go beyond optimisation - it has to be a transformation.

It means introducing new data-enabled processes in R&D, production, marketing and sales, new forms of cooperation in the supply chain, new ways of creating and commercialising products and services - all backed by a technology architecture that enables interoperability between "things" and provides data insights with the required speed.


Together with Industry of Things World, one of the leading IIoT conference series globally, Hewlett Packard Enterprise (HPE) conducted a survey to find out to which degree company leaders approach IIoT as optimisation or as a transformation, how successful they have been, and what the biggest obstacles are.

We also wanted to know which technology architectures they implement - how important will the public cloud be for IIoT, and which role will Edge Computing play?

When asked about the business goals they want to achieve with their IIoT initiatives, majority of respondents (64 per cent) named "increase efficiency".

Similarly, other high-ranked IIoT goals like increase flexibility (48 per cent) and reduce time to market (35 per cent) aim to optimise the existing business, not create the new.

In comparison, transformative goals like establishing new business models (34 per cent), improving marketing (27 per cent) and product development (26 per cent) with help of IoT data, or the transformation from product sales to as-a-services model (25 per cent) ranked relatively low.

To be clear, increasing efficiency or time to market are important business goals, but the dominance of optimisation goals in the context of IIoT can be seen as an indicator that many companies have not yet fully embraced the transformational nature of this concept.

Can we then expect that the IIoT projects of our respondents have not been entirely successful? Yes, we can.

Over 50 per cent said their IIoT projects in the past 12 months either met or exceeded their goals, while 47 per cent did not reach their goals - a small portion even said their projects were a complete failure.

So, for which reasons did companies struggle with their IIoT projects?

Respondents named the lack of skills and culture within their own company as biggest obstacles (both 38 per cent).

Read more: Industrial IoT must move from optimisation to transformation