5G Telecom New Revenue Growth Shifts to Enterprise Sources

The telecom industry is moving to new business models that change revenue opportunities in both mobile and fixed realms. Among the biggest changes: mobile revenue growth is going to shift to enterprise, away from consumer; from people to sensors. And fixed network revenue growth likewise is shifting from retail to wholesale.

In the mobile segment, the advent of 5G networks actually represents a discontinuity. As mobile subscriptions sold to people saturate, growth is going to come from selling connections to sensors and internet of things devices, in part.

The bigger change is that mobile access providers will have to move up the stack into higher-margin services and apps that underpin the value of IoT.

The precursor is what is happening in media and communications, as more mobile and fixed operators discover that growth hinges on moving into the content portions of the internet ecosystem.

In the fixed network, more of the value is coming from backhaul for smaller cells, as well as services for IoT, inherently an enterprise opportunity, for the most part.

As mobile and untethered access becomes dominant, with new mixes of licensed and unlicensed spectrum, the business value of the fixed network also is changing, with unlicensed spectrum assuming a bigger part of the facilities mix.

There is a simple explanation for that forecast. Essentially, 5G cannibalizes 4G, as 4G cannibalized 3G and 3G cannibalized 2G, and 2G displaced 1G.

Revenue upside from new applications and use cases does occur, though. Apps and use cases based on internet access are displacing voice and messaging revenue, for example.

That will be true for 5G, as well. In principle, it is services and apps supporting internet of things (non-human users) that represents the incremental growth, as 5G for human users will mostly be simple displacement.

And most of those non-human use cases will involve enterprises building networks, and offering services, involving sensors and big data analytics to “do things in the real world” based on insights gleaned from patterns in all that big data.



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