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Industrial IoT must move from optimisation to transformation
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).
This clearly underlines the fact that to be successful with IIoT requires a company transformation, a central aspect of which is that you need new skills and mindsets. Other challenges to many companies are transformational issues like missing organisational structures (27 per cent) and wrong governance and management (21 per cent).
The survey makes clear that transformation also applies to the technology that underpins IIoT initiatives.
You can't just buy IIoT technology - IIoT requires a fundamental redesign of the information technology and operational technology architecture.
We also asked which role edge and cloud computing will play for those architectures in the coming years. Many market observers have emphasised the crucial role of the cloud for the IIoT.
But as our survey shows, edge computing is as important and will grow in strength.
The three most important reasons for using edge computing in the IIoT are security (52 per cent), latency (41 per cent) and bandwidth (35 per cent).
Let's look at latency and bandwidth first.
Imagine a self-driving car going at 100kmh towards an obstacle on the road - the IT systems in the car have to analyse mega- and gigabytes of sensor data within milliseconds to avoid a crash. There is simply no time to send that sensor data to a remote cloud and wait for an answer.
This equally applies to production machines, among other things. In security, sending all that data via the network opens a big attack vector for hackers, so it's better to analyse the data onsite and send only selected and encrypted data to the cloud.
Similarly, there are important reasons to use the cloud, the top three being correlation analysis (66 per cent), deep learning (51 per cent) and horizontal integration (36 per cent).
It's not enough to have intelligence in one machine, car or plant. You can create more value if you bring their data to one central place to compare and correlate their behavior.
Then you are able to derive deep insights from the data - deep learning - which you can play back to the things and enable them to perform better, adapt to new and unknown situations better, and avoid outages.
This also allows us to better coordinate cars, machines and plants, enabling things like swarm intelligence in traffic or highly automated supply chains.
This means the IIoT will be a hybrid world. And one of the key tasks will be to create integrated architectures that bridge from the edge to the core data centres to the cloud and all the way back.
Again, the journey towards the IIoT goes beyond optimisation - it is a transformation which requires change on all company levels: technology, architecture, processes, people, and business models.
Overall, our survey results show that the industry is still learning. But we have to consider that IIoT is an emerging concept, and therefore it's encouraging to see that transformational approaches already play a significant role in the way companies plan and execute IIoT.
Similarly, I'd suggest talking about a 53 per cent success rate, not a 47 per cent failure rate. The glass is half-full. But this also means there's still a lot of work to do.
My appeal to the industry is: Embrace and master transformation, and accelerate your journey because there's not much time.
- Writer is general manager (IoT & global connectivity platform) at Hewlett Packard Enterprise.