Friday, June 29, 2018

Skinny Bundles and Viewer Preferences

The thing about WatchTV and other skinny bundles is that they are, by definition, “skinny.” They also tend to feature packages of channels that do not cost much, which is one key way of limiting  retail prices.

The problem for perhaps many potential buyers is that such bundling of less-costly channels also means some broad interest but expensive channels (ESPN and other sports) are not in the bundles.


And here you might glean some of the logic behind the Time Warner acquisition. Several of the most-expensive channels (TNT, CNN, TBS) are in the WatchTV bundle, and AT&T owns all three.

Still, as more users are discovering, purchasing multiple subscriptions often is needed to assemble a menu that matches (more or less) any single person’s interests. In part, single ad-supported channels sometimes are not available to buy, at all, as contracts might prevent it, in some cases, while business models are unattractive for suppliers, in other cases.  


The problem is that while most households watch just about 17 or 18 channels, they are not usually the same 17 or 18. Undoubtedly, each person, in each household, also has a rather unique viewing pattern, as well, possibly including a dozen or fewer channels that are routinely viewed.

source: AT&T

Does 5G Access Cause, or Only Reflect, Underlying Innovation?

Some observers seem to believe rapid 5G mobile adoption equates to broader economic activity related to 5G (applications, platforms, devices). So early 5G adoption provides an advantage.

Some of us do not really agree with that assessment. As with some other measures of adoption, rapid 5G adoption might simply reflect other developments, rather than causing them.

Some believe supplying high-speed internet access boosts economic growth. Others might argue that high economic growth drives higher incomes, which in turn leads to more availability and use of high-speed internet access.

In other words, faster broadband tends to follow economic success, not cause it. If that is the case, then early 5G deployment simply is a reflection of economic growth drivers already in place.

source: Ericsson

Mobile Media Consumption Now Approaches TV Levels

There is a simple reason why some tier-one mobile service providers believe they will profit from mobile entertainment and advertising: that is where people increasingly are spending their time consuming internet-delivered media content. And advertising “follows eyeballs” (audiences).

Until recently, U.S. digital media consumption did not rival television or radio media consumption, but digital media consumption now exceeds TV and radio combined, while most other categories of media consumption are decreasing.

One can see the same trend in China, where digital media consumption is greater than television, for example. And digital media consumption also has moved from the desktop to the mobile device.



One can ask legitimate questions about whether any mobile service provider can create an advertising platform to compete (at some level) with the likes of Facebook, Google or Amazon. But the logic of trying to do so is clear enough.

Media consumption on mobiles creates both new revenue sources (advertising and subscriptions) as well as new sources beyond simple internet access (connectivity).

Thursday, June 28, 2018

Media and Telecom Debt Bomb?

If an anticipated wave of big media and communications mergers happens, a significant number of big firms are going to come under scrutiny for their new debt loads. Right now, AT&T is in the spotlight, but either Disney or Comcast or maybe both will face scrutiny as well, as their debt loads are going to climb, depending on which firm winds up buying the Twenty-First Century Fox assets.

But those moves perhaps illustrate the risks firms in the media and communications industries now might have to undertake in order to reposition for the next phase of industry change.

Adding debt to acquire new assets is a gamble many firms will conclude they must make. For media firms, it now appears that Netflix has changed the game, forcing both a new global distribution focus and a need to shift beyond traditional distribution to streaming alternatives at greater scale.

For tier-one access providers, the issue longer has been the maturation of the access business (fixed and mobile) and the search for alternative revenue sources as voice, messaging and internet access businesses shrink or plateau.

There were many criticisms of the AT&T acquisition of DirecTV at the time. Some believed that AT&T would have been better served investing capital in its fixed network. Others argued that even if AT&T wanted to grow its video subscription business, it would have been better to try and grow organically. Some argued that linear video was a mature business, at best.

Some focused principally on the debt load. Others might have focused on the purchase price, which is related to the issue of debt burden.

AT&T of course had, and has, a strategic rationale. The company has a voracious free cash flow need to support and grow its dividend. The firm arguably also was executing on a plan to move revenue opportunities “up the stack,” into applications. And video entertainment subscriptions are among the few huge and proven consumer apps that are dependent on the networks AT&T operates.

Since then, video has contributed to supporting AT&T’s mobile business, apparently reducing churn and increasing net new subscriptions. In 2017 the entertainment group generated $51 billion of revenue, throwing off $11.6 to $12 billion in revenue every quarter, mostly from video operations.

Those results suggest AT&T could not have grown its video business organically. DirecTV contributes about 82 percent of AT&T video subscription revenue, and AT&T now is the largest U.S. linear video provider, something it almost certainly could not achieved, in the years since the DirecTV acquisition, had it tried to grow organically.

At the end of the fourth quarter, AT&T had about 3.7 million linear video accounts, while DirecTV had 20.3 million accounts. One might well argue it would have been impossible for AT&T to grow its linear business organically, by an order of magnitude, in just a couple of years. Even if AT&T had unlimited capital to invest in its linear video business, it could not have grown that fast.

To be sure, profit margins from the consumer segment are far lower than from business services or consumer mobility, but DirecTV also represents 70 percent or more of consumer fixed network revenue, and perhaps 25 percent of free cash flow (prior to the Time Warner acquisition, which might add another $4 billion of free cash flow and perhaps $31 billion in annual revenue).

Is there risk? Of course. But the traditional media and communications industries are under pressure, and consolidation is among the ways they hope to cope with greater competition and slower growth in the core businesses.

Where is the Edge and What Does One Do There?

One practical issue with edge computing is that not everybody uses the same definition of “edge,” even if everyone seems to agree edge computing means putting compute capabilities at the logical edge of a network.

As with many earlier architectural decisions app providers and transport providers must address, the issue boils down to “intelligence at the network edge” or “intelligence in the network core,” even if some functions might logically need to be centralized, while others can be distributed.

Consider even the hyperscale data center. Is such a computing facility, by definition located “at the network edge,” functionally a “core” or an “edge” function? Functionally, many would have to agree, it functions as a “core” element, not an edge element, though the webscale data center actually resides at a particular edge.

The important point is that for all the other endpoints, any particular data center actually “acts” like a “core” element, as it is remote.

The Linux Foundation defines edge computing as “the delivery of computing capabilities to the logical extremes of a network in order to improve the performance, operating cost and reliability of applications and services.” The key concept there is the plurality of “extremes.”

“Edge” only makes logical sense if “you” and your device are in the same local area as your  compute facilities. In other words, your use of cloud computing happens generally as you would use a localized (metro) area network, and not as you use a wide area network.

In a real sense, you move from reliance on WAN-based hyperscale cloud centers to use of metro-level cloud facilities, and the issue is latency performance.

“By shortening the distance between devices and the cloud resources that serve them, and also reducing network hops, edge computing mitigates the latency and bandwidth constraints of today's Internet, ushering in new classes of applications,” the Linux Foundation definition states.


In practical terms, this means distributing new resources and software stacks along the path between today's centralized data centers and the increasingly large number of devices in the field, concentrated, in particular, but not exclusively, in close proximity to the last mile network, on both the infrastructure and device sides.

That has likely implications for where and how augmented intelligence (artificial intelligence) gets implemented in wide area networks. Just how much applied machine learning or augmented intelligence gets deployed in the core, as opposed to the edge, to create new service capabilities or gain operational advantages, remains an open question.

By definition, the whole advantage of edge computing is to avoid “hairpinning” (long transits of core networks), when local access can be provided. If so, when edge computing is widely deployed, the upside to using AI to groom traffic or reduce latency is less.

Nor is it entirely clear what new network-based capabilities can be created in the core network, using AI (for example), and which AI-based features actually are possible only, or implemented easier, at the edge. Some security features or location features might be possible only at the edge, some argue.


How to apply new technologies such as AI will remind you of similar debates and decisions that happened around “making core networks smarter” or relying on “smart edge” and simply building high-performance but “dumb” core networks. Those of you with long memories will recall those precise debates around use of ATM and IP for core networking.

Wednesday, June 27, 2018

Big Assumptions Underlie Big Forecasts for 5G

How big 5G revenue streams could be depends largely on how big an impact 5G can have in enabling all sorts of other businesses requiring 5G connectivity and features (low latency, ultra-high bandwidth, retail user costs as low as provided by fixed networks).

In the area of what 5G might provide, in terms of connectivity revenues, hinges largely on incremental new activity, above and beyond what retail customers are willing to spend on 4G.

If most customers wind up substituting 5G for mobile internet access, there will be some incremental revenue potential, but not so much incremental revenue growth. If 5G winds up supporting many new use cases (sensors, for example), then brand new revenue will be created.

Just how much revenue depends on connection volume more than per-connection prices, which might be quite low.

On the other hand, perhaps 60 percent to 90 percent of total 5G-enabled revenue might come from applications, platforms, devices and other services to implement 5G-using applications for business or consumer markets.

Truly-significant revenue generation might well depend on whether 5G enables brand new internet of things, virtualization use cases, automated vehicles and processes or solutions based on artificial intelligence and machine learning.

Those are very big assumptions.

Some researchers predict that 5G will become a “general purpose technology,” and that matters because GPTs are the foundation for huge waves of economic growth. Some past GPTs are said to include:
  • Interchangeable parts and mass production
  • Military and commercial aircraft
  • Nuclear energy
  • Computers and semi-conductors
  • The Internet
  • The space industries

Others might be more selective and cite electricity and information technology as general purpose technologies that have mattered. The steam engine and electricity are seen by others as GPTs. Some cite the internal combustion engine as being a GPT.

Spoken language, the wheel, written language, printing, railways, automobiles and mass production are other often-mentioned GPTs.


Few observers seem to count “communications” as a GPT, though some have considered the telegraph or telephone a GPT.

So it is not clear whether 5G will produce as much economic activity as some predict.

source: Graeme Chamberlin, Linda Yueh  

Tuesday, June 26, 2018

FairlawnGig Claims 50% Take Rates for its Municipal Broadband Service

FairlawnGig, an open access internet access network serving the city of Fairlawn, near Akron, Ohio, now is poised to expand outside Fairlawn. The gigabit services is sold to consumers for $75 a month. Prior to FairlawnGig’s launch, the fastest available internet access speed sold in the area was 50 Mbps.

It appears take rates are highest for the 300-megabit speed package, costing $55 per month (boosted from the initial 150-Mbps level). Business services sell for $500 a month, with speeds up to 100 Gbps.

FairlawnGig says it gets a 50-percent “sign up” rate, which might mean the initial take rate is quite high, compared to most other new internet access services launched by a competitor in any U.S. market.

FairlawnGig also sells phone service for $25 a month.

The city has 3,579 houses, of which 3,320 are occupied. The city also counts about 800 businesses. Assuming it cost $10 million to build the network, that implies a cost of perhaps $2284 per location, if the full cost of the $10 million in debt raised by the city was used to build the network.

The addressable consumer market is about 3,320 locations, implying FairlawnGig could have as many as 1,660 paying consumer accounts (not including business accounts).


It is possible that the cost of activated drops is as much as $2,000 per consumer customer location in additional spending.

Agentic AI Could Change User Interface (Again)

The annual letter penned by Satya Nadella, Microsoft CEO, points out the hoped-for value of artificial intelligence agents which “can take a...