S&P 500 4Q 2017 Telecom Earnings Uniformly Below Expectations

It is just a snapshot, but the telecom segment of the Standard & Poors 500 Index faired absolute dead last among industry segments where it came to earnings that were above expectations in the fourth quarter of 2017.

Perhaps no single market is experiencing greater shocks than the Indian telecom market, as rapid consolidation is following dramatically-lower earnings. Vodafone saw a 39-percent drop in profits in the first half of 2017. Bharti Airtel profit dropped 39 percent (77 percent consolidated net profit) in the third quarter.

In Europe, it appears that profit is stabilizing, if there is little revenue growth.

Source: @FactSet

Most Big Data Projects Fail to Some Extent

According to Resulticks, only 21 percent of marketers say their big data software delivers on all its big data promises. About 52 percent of surveyed respondents believe big data projects  deliver “some” of what vendors promise.

That is not a new story, for virtually any type of enterprise computing initiatives. Few big new initiatives actually succeed on the level originally promised. Most likely fail outright.

According to some studies, enterprise “digital transformation” success rates have been as low as 13 percent.

That reflects the larger story that major investments in new technology platforms have tended to lag in producing measurable gains in productivity, sometimes for a decade or more.

That seems to be the broader pattern for some systemically-important technologies such as electricity, steam power, internal combustion engines and other general purpose technologies.

That also has tended to be the trend when enterprises have invested heavily in new computing technologies. There are many theories about “why” the pattern exists. Some think the problem is that we cannot measure the changes.

That is unsatisfying, so many believe the issue is that technology platforms deliver measurable advantages only after business practices are reimagined and refashioned to take advantage of the new technology. Time after time, we have found that big new investments in new technology do not produce measurable results for a decade or even more.

If that was routinely expected, nobody would make the investments. So the expectation is that the payoff will come within three years. Measurable value creation takes much longer, generally speaking.  

How Many "IoT" Devices Already are in Use?

Is it possible there already are as many as 27 billion internet of things devices already in use globally? Most of us would say “no way.” But it all depends on the definitions one uses for “internet of things.” Some definitions arguably are too broad.

For example, there is a difference between “connected devices” and “internet of things” devices. There might be 16 billion mobile phones and PCs--all “connected”--in use in 2017. But that seems to stretch the definition of IoT too far.

Using a more narrow definition, where IoT does not refer to mobile phones, PCs, tablets, IoT would include all manner of sensors other than phones, PCs and tablets that communicate. Using that narrower definition, there might well be as many as 10 billion IoT devices already in use, including more than four billion industrial and commercial sensors. Medical devices and sensors used in transportation also might represent about a billion more IoT sensors.

source: IHS

source: IHS

source: IHS

Reliance Jio Earns "Profit" in Less than 2 Years (Arbitrage, Accounting Rules Help)

It has been two decades since I’ve seen anything like the apparent regulation-assisted business model changes that apparently have helped Reliance Jio earn a profit within two years of launching its attack on the India mobile market.

The profit also is based on accounting rules, as Jio still has negative cash flow. In other words, Reliance Jio is able to capitalize some operating expenses.

Still, it is fair to note that some regulatory changes have simultaneously harmed Reliance JIo’s biggest competitors, and helped Jio reduce its own operating expenses.

The last time I saw this sort of regulatory arbitrage was back pre-2000, when incumbent and upstart telecom firms sparred over reciprocal compensation fees paid to firms for terminating calls on their networks from other service providers.

Basically, because such fees were very generous in a few locales, long distance conferencing services started businesses in those areas, charging very-low calling fees and essentially making their money on the earned reciprocal compensation fees paid by the calls inbound to the conference calling centers.

The same idea was used by call center operations, where most of the traffic, by definition is inbound, rather than outbound.

The same arbitrage could be used by dial-up internet access providers, since--again by definition--the customer traffic was inbound from other networks (customers dialing in to create an access session).

Essentially, disparities in traffic flow also underpin the economics of rural and other small telecom companies as well, where long distance calls (disproportionately important in rural areas) generate an originating access fee that is paid by the long distance carrier to the originating call network.

The point is that, at crucial times, regulatory arbitrage can provide a bit of breathing room while erstwhile upstarts sprint to gain market share and reach sustainability. Arbitrage likely is not a sustainable strategy for Jio, anymore than it has proven to be sustainable for many other service providers.

But, at least in principle, such arbitrage can help in the formative years.

FCC Definitions are Floors, Not Ceilings

Defining what broadband means now is an arbitrary exercise, if a necessary task to measure progress. According to the current minimum definition--on fixed networks--of 25 Mbps in the downstream, many internet access services actually cannot be marketed as “broadband,” using the Federal Communications definitions.

People, app experience and markets are not affected by any such definitions, of course. It probably does not matter at all that fixed network 10 Mbps Ethernet is not “broadband,” using the FCC definition.

The definitions do not apply to other wireless or mobile networks, though, a nuance that often is missed.

Still, for most users, it does not matter that most of their Wi-Fi and mobile internet access sessions are not “broadband,” using the fixed network definition. What matters is that user experience is good enough to provide satisfactory interactions.

“Satisfactory” often hinges on the actual use case, of course. Relatively modest speeds are required for most consumer apps, including video, somewhere between 5 Mbps and 25 Mbps. “Twitch” gamers mostly will need more.

Also, floors are not ceilings. Availability is not usage. In fact, U.S. consumer internet access speeds double about as fast as Moore’s Law would predict, and grow by an order of magnitude about every five years.

By some measures, U.S. average speeds are in the range of 19 Mbps. By other tests, even mobile access speeds are in the 23 Mbps range. Some other tests show 2017 average speeds of 55 Mbps.  

source: Speedtest

Though we tend not to pay much attention, U.S. fixed network internet access speeds used by consumers have grown about as fast as Moore’s Law would predict, at least on cable TV networks.

Cable One Offers Gigabit Internet Access to 95% of its Passings

Cable One’s “GigaONE” gigabit internet access service is now available to residential customers across more than 95 percent of its U.S. footprint, representing more than 200 communities.

The primary impact likely will be that more people buy access at lower speeds, ironically. The reason is that when gigabit services are offered, the price of lower-speed tiers tends to drop. And, as you would guess, consumers buy more of a product they like when the price is lower. Verizon, for example, introduced its new gigabit per second at a retail price half that of the former 760-Mbps service, for example.

Gigabit services launches tend to reduce prices of services in the 100 Mbps or hundreds of megabits per second range to drop about  $27 per month, or about 25 percent, according to an Analysis Group study.

In markets where gigabit service has been introduced, prices for internet access in the 25 Mbps and lower speeds also tend to drop, by 14 percent to 19 percent.

Likewise, when two providers sell gigabit services, prices for that service tend to decline by $57 to $62 per month, or 34 percent to 37 percent less.

Actual revenue upside might also be complicated. On one hand, gigabit sells for a higher price. But gigabit availability also tends to mean prices for lower-speed tiers fall. So net incremental revenue is tough to evaluate.

Take rates are part of the equation. Some believe adoption of gigabit services could range between five and 10 percent, in markets where lower-speed tiers also are available.

"Price anchoring" is the reason most consumers able to buy gigabit internet access will not do so. Price anchoring is the tendency for consumers to evaluate all offers in relationship to others. As the saying goes, the best way to sell a $2,000 watch is to put it right next to a $10,000 watch.

Anchoring is why "manufacturer's suggested retail pricing" exists It allows a retailer to sell a product at a price the consumer already evaluates as being "at a discount." Price anchoring is why a "regular price" and a "sale price" are shown together.

In the internet access business, price anchoring explains why gigabit access speeds are priced in triple digits, while low speeds are priced in low double digits, while the tiers most consumers buy are priced in between those extremes.

Service providers who sell a range of internet access products differentiated by speed and price might “typically” find that a minority of customers actually buy the “fastest” tier of service. That is largely because of price anchoring.

People often evaluate a "best quality offer, at highest price" one way against the "lowest quality offer, at lowest price, before concluding that the "best" value is the mid-priced quality, at the mid-tier price.

That was true in the past when the top speed was 100 Mbps as well. Most consumers did not buy the "highest quality" offer, whatever it was.

So it can be argued that gigabit internet access speeds have complex effects on internet service provider business models. Most customers will not buy the top speeds, but will upgrade to faster tiers of service. At the same time, prices generally fall, on a “cost per Mbps” basis.

Consider that Comcast internet access average revenue per account is about $40 a month. Given that Comcast gigabit offers, where it faces little competition, are as high as $160 a month, and perhaps as low as $70 where Comcast faces gigabit competitors, that $40 average suggests uptake of the fastest tiers of service remains less robust than some would imagine.

Against that ISPs must balance the capex to build the faster networks, as well as evaluate the upside from any new apps and services that might be enabled by the faster networks, top speeds or rising average speeds.

The new wrinkle is that ISPs often make gigabit service available in neighborhoods where demand is highest. Doing so might lead to 30 percent take rates in those neighborhoods, as AT&T claims.

Telcos Developing Practical AI Apps

As exotic as artificial intelligence and machine learning might seem, they are becoming routine tools for optimizing networks, discovering and preventing problems on networks, and supporting consumer interfaces and third-party AI aps.

Telefonica is working with Juniper Networks to develop its “Self-Driving Network” solution, which uses machine learning to enable self-configuration, self-monitoring and self-diagnosis. THe idea is to give the network the ability to identify potential problems and correct them--without human intervention--before they cause issues.

Vodafone has been working on artificial intelligence trials in Germany and Ireland with Huawei and Cisco on ways to create a “centralized self-organising network” (C-SON) that identifies the optimal conditions for voice-over-LTE.

AT&T, for its part, also is creating a platform for supporting artificial intelligence apps that run on its networks, in addition to using AI to virtualize its network.

Verizon, among other apps, is looking to use AI to support voice interfaces.