What Will Drive 5G Business Model?

Among the many unknowns about 5G is the business model: where will new incremental revenue sources develop, and will they develop?

The conventional wisdom is that “enhanced” mobile broadband is one of three key revenue drivers. The others are ultra-low latency services (connected cars, for example) and massive machine applications (internet of things).

If that proves to be true, then it also is possible to say that two out of three expected revenue drivers will be enterprise markets (low latency and machine applications), while one will represent consumer mobile broadband.

And, at least at first, consumer internet access is likely to drive incremental revenue growth. The value proposition (10 times faster) is clear, and the market is large (everybody) and well understood (internet access).

And while consumer internet access will continue to be a “horizontal” value (everybody needs internet access), that might not be the case for the other two drivers. It is logical that success providing low-latency services or machine applications could involve a healthy amount of industry vertical knowledge.

That would be a major evolution for telecom service providers, who arguably have done best supplying horizontal value in the ecosystem.

That noted, service providers are not strangers to specialized enterprise communications, to an extent. Generations of enterprise-specific data networks have been developed and deployed. Perhaps few of those efforts have had the requirements for intimate industry vertical knowledge, however.

That would represent one of several huge shifts. First, growth might change from consumer mobile broadband to growth lead by enterprises deploying huge sensor networks and new use cases where low latency is a fundamental requirement.

Growth might also shift to “vertical” from “horizontal.” That will require additional investment and focus from an industry used to horizontal value propositions, at least in some cases. It also is true to note that there are potentially so many vertical use cases that a rational service provider cannot actually customize for all of them.

That potentially means a shift away from “public networks” and towards “private networks,” as many potential customers decide they must build their own networks, to support their specific use cases. Just how far that goes is unclear.

To illustrate, it is conceivable that, by the end of the 5G era, Amazon is the service provider, not NTT or AT&T, in many use cases. What will matter is whether such providers are substantial wholesale customers, or build and operate their own facilities. If so, the extent to which they do so will affect public services markets.

Also, new network capabilities, such as network slicing, might just be enough to allow service providers to build customized private networks on behalf of customers, to a large extent.

The issue is the amount of uncertainty about 5G business models, not because of anything inherent in 5G, but simply because, over the last few decades, service providers have had to replace about half their current revenue every decade.

Mobility replaced lost fixed network long distance revenue Some service providers used business customer revenue to replace lost consumer revenue.

Cable operators replaced consumer revenue with business customer revenue, voice and data for video revenue.

Mobile operators replaced declining voice and text messaging revenue with mobile internet access.

To be sure, every next generation mobile network has represented some degree of uncertainty, in terms of enabling the growth of new revenue streams and use cases. That will be true for 5G as well.

What seems arguably certain is that legacy use cases will not drive growth. One might argue that never has happened with mobile platforms. Though digital 2G was more efficient than analog, the new revenue came from text messaging and affordability by mass market customers, which drove subscription growth.

The 3G network was the first to support mobile email and web browsing, as well as some amount of tethering and mobile internet access. The 4G network was the first to enable video content consumption and a user experience better than Wi-Fi.

The 5G network is expected to enable internet of things and machine to machine business models, as well as full substitution for the fixed network (internet access).

More 5G Spectrum Coming from U.S. FCC

The Federal Communications Commission will vote in November 2017 to make available 1,700 MHz of high-frequency spectrum for 5G.

Two spectrum bands will be allocated,  providing 700 MHz in the 24 GHz band and 1 GHz in the 47 GHz band.

A year ago, the FCC allocated 11.65 GHz of spectrum with 3.85 GHz of that allocated in the 28 GHz and 37 GHz to 40 GHz bands.  Additional spectrum is still under consideration to be allocated in the future.

All that new spectrum, plus spectrum sharing and spectrum aggregation, will lead to mobile internet access becoming very price-competitive with fixed internet access, for many users and use cases.

Some might still doubt that 5G will create, for the first time, full product substitution by mobile networks for fixed network internet access. Traditionally, the objections were well founded, and based on value and price objections.

Mobile traditionally has been much slower than fixed, and cost per bit has been at least an order of magnitude higher for mobile alternatives.

source: Wavelengths

Of course, nothing stands still, where it comes to network platforms and technologies for internet access. Even before spectrum sharing, aggregation of licensed and unlicensed spectrum and new allocations of millimeter wave capacity, each mobile broadband network generation has reduced cost per bit by about 50 percent.

So there is little reason to believe 5G will be different. To wit, a reasonable person would forecast that cost per bit for mobile internet access will drop at least another 50 percent.

To be sure, mobile bandwidth, on a cost-per-bit basis, remains an order of magnitude or so more expensive than fixed alternatives.

Of course, that comparison has been based solely on “mobile” versus “fixed” economics. In the next era of spectrum sharing and aggregation of licensed and unlicensed assets, “fixed” access becomes part of “mobile” access.

That logically should propel “mobile” access faster down the cost curve, as “mobile” access is based, in substantial part, on use of unlicensed (“no incremental cost”) assets.

When aggregating mobile access with unlicensed, the assumed cost of the unlicensed capacity is fairly close to zero, as there is no “cost of goods” (the unlicensed access is provided on a no-additional-charge basis).

A mobile service provider supplying a unit of access service to a device blends the cost of using its own network ($ per delivered gigabyte) with “no out of pocket cost” (close to zero dollars per gigabyte) unlicensed gigabytes.

If you assume the mobile network cost of delivering a gigabyte will drop 50 percent from 4G to 5G, an incremental drop will be added by shifting much usage to the Wi-Fi or other unlicensed spectrum networks.

The point is that the cost of using a gigabyte of “mobile” access will be quite close to the cost of using a gigabyte of “fixed” access, especially on an “actual consumption” basis.

Obviously, the actual cost of using any internet access service, no matter what the posted retail rate, is directly related to the actual amount of usage, compared to the retail recurring cost.

A user might pay for use of 10 Gbytes on a mobile network, at $2 to $8 per gigabyte, compared to a fixed network cost of perhaps five cents per gigabyte.

The out of pocket cost of the mobile access might be $30 a month, while the cost of the fixed access might be $60 a month. The new reality, though, is that the mobile cost will include use of an almost-unlimited amount of unlicensed network access.

That means the “actual” cost of a $30 a month mobile plan includes hundreds of gigabytes of effective usage. In that case, the cost per bit of mobile access is virtually indistinguishable from the cost per bit for fixed access.

Why Gigabit Mobile Matters

Though retail pricing is an issue, mobile network peak data rates above the gigabit-per-second barrier are important because it brings “a mobile user experience that at least matches the home fixed broadband experience,” according to Nokia.

In other words, the value is not so much “gigabit speeds for smartphones,” but the ability of mobile networks to rival fixed network user experience. That, in turn, matters for several reasons.

source: areppim.com

In markets where mobile provides nearly all the internet access, gigabit peak rates mean typical user experiences in developing markets that are substantially on a par with developed markets.

In developed markets, gigabit mobile rates mean both the ability to create a full substitute product for fixed access, as well as the ability to serve many locations where the business case for a fixed solution at such speeds is unworkable.

For fixed service providers, gigabit mobility therefore also calls into question the value and business model for the fixed network, which shifts away from retail consumer internet access, and towards backhaul and business customer revenue models.

Auto Industry Mirrors Telecom Industry Transition

Eventually, the auto industry will make vehicles as the foundation of a range of other revenue-generating activities, but not as the sole driver of revenue, much as the telecom industry is in transition to business models that are built on the need for connectivity, but not connectivity revenue itself.

It is easy to forget that whole industries, not just products created by any industry, have product life cycles. Now it is the auto industry as a whole that seems to have reached a peak of its life cycle, something we already have seen in the telecom industry regarding voice and messaging products, might be seeing in mobility and video entertainment as well, and will soon affect internet access.

source: Marketing Fanatics

With the caveat that global trends sometimes are not reflected in some particular markets, Moody’s Investors Service says the global auto industry outlook is negative, with “stagnant or falling demand for vehicles, a shift back to larger vehicles despite new energy efficient technologies, historically high levels of lease expirations and lengthening auto loan terms” in the U.S. market.

Eventually, as the legacy revenue model erodes, the industry will try--as others have--to create a new business model. For the auto industry, that might well include a shift to autonomous vehicle transportation or other transportation services, not the production, sale and maintenance of autos themselves.

If the telecom industry provides any useful model, the model will still include “making vehicles,” as telecom builds on its connectivity platform. But as connectivity itself does not drive revenue growth, making vehicles will become just a part of the revenue stream.

It is worth recalling that the only reason the early telecom industry built networks at all--and continues to do so--is that the application it wanted to sell required such networks. LIke Facebook, Google, Netflix or Amazon, which require the existence of internet access networks for their business models, so early telcos needed telephone networks to sell voice.

Eventually, if they are successful, automakers will continue to make vehicles, but only as an underpinning for their transportation services businesses.

AI in Telecom: Customer Service is an Early Use Case

As was the case for cloud computing, so artificial intelligence is going to appear in consumer-facing apps where the user is not always aware of its presence. Voice interfaces provide the best example.

That also seems to be the case in telecommunications as well. But AI also is expected to play a growing role in network operations as well.

The most-popular AI applications in use by a number of tier-one U.S. telcos include customer service apps such as chat bots. In those roles, AI-assisted apps automate customer service inquiries, route customers to the proper agent, and send prospects with buying intent directly to sales people, according to Tech Emergence.

Those use cases also are obvious in the area of speech and voice services for customers, allowing customers to explore or purchase media content by spoken word rather than some other method.

In the network, AI is starting to be used for predictive maintenance, allowing staffs to fix problems with telecom hardware (cell towers, power lines) before they happen.

Likewise, AI is used to support self-optimising networks (SON). It also is possible that AI will be used to create “deep neural networks” to support customer engagement tasks with those networks.

Software defined networks (SDN) and Network Function Virtualisation (NFV) also have use cases for AI, allowing customers to interact with services behind the network, for example.

At the customer service level, AT&T leverages AI to process all “online chat interactions”. predictive maintenance as a major AI initiative within the company.

Verizon has launched Exponent, a set of services offered to other global carriers. The suite of digital tools is designed to allow customers to apply their data to personalized marketing campaigns, laser-targeted advertising, and deep customer engagement.

Comcast uses AI to support its X1 voice remote interface.

The Charter Communicatins Ask Spectrum virtual assistant uses AI to help customers with troubleshooting, account information or general questions about Spectrum services. The AI-driven assistant named Angie was designed by Conversica.

DISH Network works with Amazon to support customer use of its digital video recorder, integrating voice response with Amazon’s Alexa.

None of those customer-facing apps are likely going to produce a “wow” reaction. But all are practical, every day implementations of artificial intelligence.

Will Autonomous Vehicles Increase or Decrease Traffic?

You might think significant use of autonomous vehicles would increase--or at least not affect--primary reliance on public transportation. You might also guess that use of autonomous vehicles would reduce use of traditional taxis.

A study conducted by Boston Consulting Group suggests the former would not happen, while the latter would. The study looked at existing and expected traffic patterns in downtown Boston.

source: Boston Consulting Group

The risk of unintended consequences arguably is substantial. If autonomous vehicles make transportation  cheaper and more convenient, traffic congestion could increase.

If people use autonomous vehicles more often and in an ad hoc manner, more congestion could result.

Greater congestion could also result from a rise in certain types of zero-occupancy trips, such as when empty autonomous vehicles cruise the streets to sautonomous vehiclee on the costs of parking.

The base case assumes that 56 percent of the trips start, end or occur entirely within the 0.45-square-kilometer study area involve public transit, 33 percent involve a traditional personal vehicle and 11 percent involve taxi or ride-hailing services.

Scenario A, the evolutionary scenario, assumed a substantial shift from traditional to autonomous privately owned cars and a steady increase in the use of shared modes of mobility.

Specifically, it assumed that 11 percent of trips would be by traditional private car, another 11 percent by privately owned autonomous vehicle, 50 percent by public transit, and 22 percent by ride-shared autonomous vehicle taxi.

Traditional taxis and ride-hailing account for the remaining six percent of trips in this scenario.

Scenario B postulated a revolutionary change from privately owned vehicles to the on-demand use of electric autonomous vehicle fleets. This scenario assumed that 34 percent of trips would be by public transit, 24 percent by single-passenger autonomous vehicle taxi, 14 percent by ride-shared autonomous vehicle taxi, and 28 percent  by autonomous vehicle shuttle bus.

source: Boston Consulting Group

Business Case for Much More Fiber Remains a Challenge

Verizon’s decision to deploy NG-PON2 networks, AT&T and Verizon fixed wireless plans and use of unlicensed spectrum, plus spectrum sharing, are among the ways various internet access providers are working to improve the economics of next generation fixed networks.

As always, competition and the business model are key constraints.

Policymakers and regulators always have to balance competition and investment incentives in the communications business. Too much perceived competition lowers profits, and inhibits investment; but lack of competition tends to inhibit consumer-facing innovation.

At the moment, incentives are a key problem where it comes to next generation fixed network investment.

If consultants at Deloitte are correct, and as much as $130 billion to $150 billion in additional optical fiber investment is needed in the U.S. market, under conditions where financial incentives do not exist, something will have to give.

As Deloitte sees matters, at the moment, U.S. service providers do not have incentives high enough to support that level of deployment of new facilities. For starters, some major suppliers--including both cable TV and telcos--have high stranded assets.

If you assume a typical cable operator has revenue generated by roughly 60 percent of its passed consumer locations, while at telco gets revenue from about 40 percent of residential locations, stranded assets range from about 40 percent to 60 percent of the invested distribution network.  

That obviously creates a return on invested capital problem. Unless something changes, in terms of revenue upside, many of the largest internet service providers will have a hard time vastly increasing their optical network investment.

source: Deloitte

source: Deloitte