Michael Schallehn: Scaling Up in the Internet of Things

Bain Partner Michael Schallehn discusses why there are so many challenges associated with scaling complex IoT concepts and what vendors can do to overcome these roadblocks.


Michael Schallehn: Scaling Up in the Internet of Things

For Internet of Things (IoT) vendors, moving from proof of concept to a scale implementation can be challenging. Michael Schallehn, a partner with Bain's Technology practice, describes the two things that industrial IoT vendors can do to make these transitions effective.

Read the transcript below. 

MICHAEL SCHALLEHN: Industrial and operations technology vendors are critical for the implementation of industrial IoT solutions. They have the customer relationships, they have the domain expertise, and they have the ability to integrate IoT into the equipment on the shop floor.

However, when we talk to IoT customers, we see that these vendors sometimes have difficulties to scale from a proof-of-concept implementation into a broader product. And when we talk to IoT customers, they tell us that some of the proof of concepts are actually more complex to implement.

So, for example, a predictive maintenance use case might require much longer data time lines and much higher data quality in order to derive the insights. The IoT vendors are reacting to these challenges by deploying more engineering resources. But, of course, that is not sustainable if you want to move from a proof of concept into a scale implementation.

So, what should these industrial IoT vendors do? Two things. No. 1 is just focus on two to three industrial verticals. Actually, our research shows that vendors are still focusing on four to six industries, which is too much. That prevents you from accumulating learning-curve effects and deploying end-to-end solutions together with your partners that you can scale from one customer to the next.

The other thing is picking the right partners, and it turns out that the partner selection is highly dependent on the use cases that you have prioritized. So a couple of examples. Remote monitoring is a use case that we see as getting traction, and it turns out that this use case is actually not that complex from a technical point of view. You can often rely on a third-party communication module, and then work with an AWS or an Azure in order to develop the back end, and maybe an app that can be deployed to the front line.

Other use cases rely on heavy analytics, and in a situation like that, an industrial IoT vendor might want to add to his own capabilities through a corporation, for example, with a Pivotal or IBM Watson. Other use cases, such as smart supply chain, rely heavily on a tight integration into an enterprise IT stack.

So, in a situation like that, it might be appropriate to work within enterprise IT software vendors, and examples could be Oracle or SAP. So, stepping back, two things are important: No. 1 focusing on just two to three industry verticals; and second, picking the right partners based on the use case that you have prioritized.

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