New Business Models are the Biggest Issue of the New Era of Communications

New business models are at the heart of most developments in telecommunications. It is no secret that value within the internet value chain has moved to app providers and away from access, whether you measure by annual revenue, profit margins or equity values.

That automatically raises the issue of whether telcos, cable TV companies and internet service providers can create new business models. Already, many would argue that profit already has been vaporized in the undersea transport business, the long distance voice business and fixed line services in general.

That same process is being seen in the mobile segment, as voice and text messaging revenues are generating less gross revenue and profit in many markets, supplanted by mobile data services that, in turn are becoming problematic in many markets that adopted early.

"The hyperscale guys are so much more efficient" than the access providers," argues Tim Horan, Oppenheimer analyst. "I kind of think everything goes to LTE (mobile) and cannibalizes wireline."

"Do telcos become commodity infrastructure providers?" asks Pierre de Vries, co-director of the Silicon Flatirons Center for Law, Technology, and Entrepreneurship at the University of Colorado. Basically, some might argue, that is the present danger.



If big data ownership is the oil of the coming age of the internet, then it might also be true that spectrum is the beachfront property of the communications networks that support the internet. But there remains huge disagreement about the most-fundamental aspects of the wireless and mobile networks that serve most consumers globally.

For example, there is not complete agreement about whether there is scarcity of available spectrum, and therefore, how important additional spectrum allocations might be. Demand for mobile spectrum has not been as extensive as the Federal Communications Commission predicted in 2010, for example, says Armand Musey, Summit Ridge Group founder.

To be sure, there are discrete industry viewpoints. Satellite industry supporters almost always argue there is no shortage of mobile spectrum. Virtually all supporters of the mobile industry argue much more spectrum is required.

LIkewise, there remains disagreement about the various ways any existing spectrum should, or can, be allocated. Allocation of licensed spectrum (exclusive use) with, or without auctions, have been the preferred methods.

But now shared access (dynamic access) is emerging as a new choice, especially where the objective is to maximize the use of already-licensed spectrum, beginning with the 3.5-GHz bands in the U.S. market, and 2.3 GHz in Europe, for example.

Dynamic access is the key to alleviating spectrum shortages, particularly in the mid-bands, argues Kalpak Gude, Dynamic Spectrum Alliance president. “I’m not sure people understand the potential,” says Gude.

Using several techniques, it is possible to protect existing licensed users, but allow opportunistic use when the licensed spectrum is not actually in use, thus using existing spectrum resources more efficiently, without the expense and time required to move existing users from their existing bands. Though Musey does not believe there is a mobile spectrum scarcity, he does agree that a technology revolution coming, in the form of shared access capabilities.

Still, scarcity might matter greatly. “Without scarcity, there is no business,” says Tim Horan, Oppenheimer analyst.

At the same time, there are big new moves being made to enable sharing of licensed and unlicensed spectrum, including 4G Long Term Evolution and Wi-Fi, for example, or to enable use of LTE in unlicensed bands alone. In the U.S. market, some seven gigaHertz of new unlicensed spectrum is going to be made available.

And while some argue for more use of unlicensed spectrum, others believe that without exclusive use licenses, investment will not be made. “Where is the revenue, if spectrum is unlicensed,” Musey asks. “How do you finance the construction of networks?”

Actually, it is quality of service that has to be assured if investments are made, argues Bob Pepper, Facebook global director.

As a practical matter, regulators globally believe much more mobile spectrum is required, and much more spectrum is coming. Exclusivity of rights is the issue, not so much scarcity of bandwidth, argues Pierre de Vries, co-director of the Silicon Flatirons Center for Law, Technology, and Entrepreneurship at the University of Colorado.

The issue is the right to exclude versus the right to be protected from interference, says De Vries. And under any system of licensed and unlicensed access, we still would have regulation, says Pepper. But the amount of regulation could be reduced if we relied more on technology standards to protect users from interference, says Gude.

Push on Steroids: the Next Era of the Internet

The internet has moved, over time, from push to pull, and then back to push. In the next evolution, push might be even more important.

AOL, the big U.S. ISP in the early days, largely relied on a push model, aggregating content it believed most people would be interested in. Then, with the World Wide Web, the internet moved to a “pull” model, where people knew what they wanted, and asked for it.

In the next big era, push likely will become even more powerful.

Pull is user-initiated. The best example is “search,” where a user seeks information, usually an answer to a question. Google providers the best example.

Push is internet app initiated, where an app sends you information the app believes you value, without any action on your part. Facebook provides a good example of push.

The killer app for push is social networks. Information is pushed from user to user using likes, shares or tweets. Now, people push items. In the next wave, powerful artificial intelligence engines will scour vast data stores to figure out what each user likes, values and wants, and then delivers it, with no direct action on the part of any user.

In a sense, apps on the internet can initiate action and push content and items to each user, based on data mining based on use of machine learning and artificial intelligence. Push and pull have analogies in marketing, and so might change or create new business models.

Characteristics	Pull	Push
dominant platform	Search	Social
dominant platform company	Google	Facebook
growth era	2000s	2010s
successful content type	Utilities	Media
marketing activity	links and algorithms	shares and people

source: cdixon.org


source: Smartinsights

The Next Generation of the Internet is Coming

You might argue the internet has evolved since its inception. Originally a narrowband tool for researchers, it now is a broadband tool used widely by most consumers and businesses. Early on in the development of the World Wide Web, people gained the ability to publish, says Charles Fan, Cheetah Mobile CTO. Then, with the emergence of search, we gained the ability to find the world's information, he says. The problem is that you have to know what you are looking for, to find it. That makes search less useful.

In the coming wave, content relevant to a consumer will be found and then "pushed" to each user. We already see glimmers of that in the high use of social apps, where people now find "information" useful and relevant to them. Also, "news" is redefined less as what is happening in the broader world, and more what is happening with your friends, family and social circles.

To a large extent, that means we are using an algorithm that essentially assumes "what is interesting to your friends is interesting to you." That is correct, up to a point. The next wave will involve use of artificial intelligence, coupled with big data stores, to actually predict what you like.

In the next generation of the internet, machine learning will be better than knowing your social graph, as a way of connecting you with things you are interested in. That AI-driven model might also lead to creation of huge new business models to replace existing and older models (advertising, e-commerce or peer trading mechanisms like Uber), says Fan.

That reliance on big data stores might have huge implications. On one hand, the algorithms will have huge amounts of new data to work with. On the other hand, algorithms will be commoditized, democratized or “made somewhat obsolete.” In a world where everyone has access to good algorithms, value will shift to access to huge data stores.

“Who has the better quality of data wins,” Fan says. “How do you get better at collecting data?” Fan asks. “Big data ownership is going to be the oil of the modern age.” But that will require artificial intelligence or machine learning.

For most of us, artificial intelligence (AI) has been a science project for the past few decades: interesting and provocative, but not something that actually affects the businesses most of us deal with on a daily or even annual basis.

There are reasons to believe that is changing. Charles Fan, Cheetah Mobile CTO, said it might seem odd for a mobile app and tools company such as Cheetah Mobile to be seriously evaluating AI. Actually, it turns out to be most practical, as Cheetah Mobile launches new applications in the news aggregation area.

Eventually, the ability to personalize and then predict what a particular person might like will require AI to mine and then predict and deliver “suggested items” to individual people.

Your social profile helps, but only so much. Content providers or advertisers can assume you are somewhat like your “friends” in terms of interests. But only up to a point is that correct. Each individual actually is quite different, at a more-granular level. But it will take AI to rapidly process all the data used to assemble a highly-personalized set of content and then match people with highly-targeted offers and ads.

Incentive Auction a "Massive Disappointment?"

Among the conclusions one might draw from the Federal Communications Commission’s 600 MHz two-stage “incentive auction” are that low-band mobile spectrum, in the U.S. market, is deemed to be worth less than always has been argued.

In terms of revenue raised by the new way of auctioning spectrum, some might call the outcome a massive disappointment.

In January 2016, FCC Chairman Tom Wheeler claimed the auction would be the “world's largest spectrum auction that has ever taken place.” Not so, as it turns out. In fact, the auction likely will clear far less (less than half) of the $44.9 billion raised by auctioning AWS-3 spectrum.

By way of comparison, the AWS-3 spectrum (in the 1.7 GHz and 2.1 GHz ranges) raised $44.9 billion for 65 MHz of total spectrum.

The 600-MHz spectrum will raise perhaps $18 billion for 84 MHz of spectrum. The FCC originally had expected to raise as much as $60 billion in proceeds.

This was in sharp contrast to the FCC’s initial expectation of collecting at least $60 billion from Incentive Auction. Spectrum owners had expected as much as $86 billion in sales.

Arguably, AT&T and Verizon believe they have other ways to satisfy any “coverage” capacity they might require in the future, while the “reserve spectrum” conditions that barred both from bidding on much of the spectrum (about a third) might have contributed to the lack of enthusiasm as well.

Some argued that the "reserve spectrum" feature, as always, produces distortions in spectrum markets. Among those distortions are price and demand impacts.

On the other hand, some bidders such as T-Mobile US will pay less for their spectrum, and likely will get some spectrum, simply because competitors were forbidden to do so.

There are a huge number of ways mobile operators will be increasing capacity in coming years. There is an astounding amount of new millimeter wave spectrum coming that dwarfs all current authorizations of communications spectrum.

Offload of demand to Wi-Fi also will help. So will small cell networks operators will build to deploy the new millimeter wave assets. As much as seven gigaHertz of new unlicensed spectrum also will be released by the FCC, allowing use without payment of license fees.

At the same time, better radios also will help boost capacity, using any specific set of frequencies. And some potential bidders, such as cable companies, also can buy existing companies and thereby acquire their spectrum assets.

We will have to wait to see whether other large auctions of new spectrum (India and Egypt  also have found far less demand than anticipated) continue to show lower prices.

But it seems markets are rational. With vast increases in supply now possible, and more supply coming, prices should fall.

Where Should India Focus Internet Access Capital Investment?

Some might say, in terms of fixed network internet access, across South Asia. Others might say that is less important than achieving robust mobile access at higher speeds, since that is the way most people are going to use internet access services.

Perhaps paradoxically, India and others should not deploy excessive capital on fixed facilities, instead focusing on mobile access at higher speeds, one might argue. The best way to get everyone connected is to use the mobile and wireless platforms that can be deployed and used faster, at lower cost and lower investment levels, right now.

Infrastructure is a major barrier, among several, for Indian internet access ubiquity, according to McKinsey and Company. In fact, according to McKinsey, infrastructure is the single biggest barrier to widespread internet access.

source: TRAI

source: TRAI

"No material impact" if Strong Net Neutrality Rules Go Away: Netflix

“Weakening of US net neutrality laws, should that occur, is unlikely to materially affect our domestic margins or service quality,” says Reed Hastings, Netflix CEO. Oddly enough, cable TV companies said the same about common carrier regulations: they did not prevent those firms from investing in faster access services. Telcos clearly reduced capital investment.

But the incentives and behavior arguably fall into a couple of buckets. Netflix believes it clearly benefits from rules that mandate “best effort only” access, in large part because that prevents creation of quality of service (QoS) mechanisms that could raise Netflix costs of doing business.

Telcos believe they clearly are harmed, because they cannot create new QoS tiers of service that could create new revenue models (business services, with QoS assurances, have higher gross revenue and profit margins, for example).

Cable companies, positioned to gain market share because they could quickly improve speeds, were in position to do so even if no QoS were possible, simply because their networks could rapidly and affordably be boosted into multi-hundreds of megabits per second ranges, plus gigabit speeds. Despite the rules, cable was able to justify new investments.

So there is no easy way to assess the impact of the net neutrality rules in some uniform sense. Netflix arguably benefited, but no longer needs the rules. Cable companies also benefited, despite the rules. Telcos, already losing the market share battle, arguably were dissuaded from investing.

The point that might be made is that network neutrality has been a blunt instrument with different impact on different participants in the market. Going forward, and without arguing for imposing new rules on app providers in advance of demonstrable problems, a more nuanced approach could work.

Competition in access markets, for example, would be enhanced if telcos were convinced they could do something--especially in the quality area--to compete more effectively with cable companies, and would invest to do so.

The new perspective that will at least get a hearing is that net neutrality or other rules designed to protect consumers from abuse of market power--the sorts of policies normally the domain of the Federal Trade Commission--might need to be symmetrical. That is to say, they perhaps should apply to edge providers (app providers) and access providers alike.

Netflix continues to favor” strong net neutrality” rules (no QoS). That arguably will not happen, which is why Netflix reassures its investors that it can thrive even without the rules.

Artificial Intelligence is Becoming Quite Practical

For most of us, artificial intelligence (AI) has been a science project for the past few decades: interesting and provocative, but not something that actually affects the businesses most of us deal with on a daily orFor most of us, artificial intelligence (AI) has been a science project for the past few decades: interesting and provocative, but not something that actually affects the businesses most of us deal with on a daily or even annual basis.

There are reasons to believe that is changing. Charles Fan, Cheetah Mobile CTO, said it might seem odd for a mobile app and tools company such as Cheetah Mobile to be seriously evaluating AI. Actually, it turns out to be most practical, as Cheetah Mobile launches new applications in the news aggregation area.

Eventually, the ability to personalize and then predict what a particular person might like will require AI to mine and then predict and deliver “suggested items” to individual people.

Your social profile helps, but only so much. Content providers or advertisers can assume you are somewhat like your “friends” in terms of interests. But only up to a point is that correct. Each individual actually is quite different, at a more-granular level. But it will take AI to rapidly process all the data used to assemble a highly-personalized set of content and then match people with highly-targeted offers and ads. even annual basis.

There are reasons to believe that is changing. Charles Fan, Cheetah Mobile CTO, said it might seem odd for a mobile app and tools company such as Cheetah Mobile to be seriously evaluating AI. Actually, it turns out to be most practical, as Cheetah Mobile launches new applications in the news aggregation area.

Eventually, the ability to personalize and then predict what a particular person might like will require AI to mine and then predict and deliver “suggested items” to individual people.

Your social profile helps, but only so much. Content providers or advertisers can assume you are somewhat like your “friends” in terms of interests. But only up to a point is that correct. Each individual actually is quite different, at a more-granular level. But it will take AI to rapidly process all the data used to assemble a highly-personalized set of content and then match people with highly-targeted offers and ads.