Without Hedonic Adjustment, You Can't Tell What Has Happened to Home Broadband Prices

It is hard to answer the question “have home broadband prices risen since 2009?” with using hedonic adjustment and also adjusting for inflation. The Bureau of Labor Statistics uses hedonic adjustment to track producer prices for home broadband, for example, since speed and other attributes change over time. 

The rationale is that a dial-up internet connection is not a comparable service to home broadband at various speeds (10 Mbps, 100 Mbps, 1 Gbps, for example). Since prices tend to stay about the same over time while speeds have increased for the “most bought” tiers of service, BLS adjusts prices to account for quality improvements. 

source: Bureau of Labor Statistics 

Trends for voice services are harder to track, as that feature is included in the recurring cost of both mobile and fixed network services. Over a few decades, the cost of fixed network voice services has tended to rise (as actual costs cannot be easily subsidized by higher-profit services, as once was the case). 

The cost of mobile service has tended to drop over time. In October 2022, for example, the U.S. Bureau of Labor Statistics said the cost of mobile service dropped 1.4 percent, hedonically adjusted. 

Home broadband also appears to have gotten cheaper by a bit in the September 2022 CPI report. That figure has to be interpreted, however, as the internet services category includes both internet access and other “electronic information providers.” 

That includes subscriber fees for residential internet access, but also other online services such as web hosting, domain names, and file hosting for non-business use. 

Also, this category includes service bundles that might include telephone and TV services bundled with residential internet service and mobile internet access. Obviously, each of those separate services has a distinct retail cost profile that can skew the figure for what we assume “home broadband” actually costs. 

Other monthly subscriber fees are also included in the  but are not limited to internet rental equipment, Wi-Fi service fees, installation and activation fees, and other associated taxes and fees.  

That noted, we might note that service bundles mean lower prices per product, even when some components such as home telephone service might have rising cost profiles. 

Determining what most customers actually pay does require some analysis of the service plans people actually buy, not simply the posted retail prices. If most customers buy bundles, their costs per service are lower than if they purchased each component separately. 

Still, using the BLS data, we can see a dramatic fall in U.S. internet access prices since about 2017, when hedonically adjusted.

 

FTX, Enron, Lehman Brothers

The collapse of FTX has some commentators suggesting the bankrupt cryptocurrency exchange could produce investor losses or wider fianncial damage on the scale of Lehman Brothers in 2008.

Perhaps others might be tempted to compare FTX bankruptcy impact to  investor losses from Enron the early years of the century. I just cannot see that. 

source: Banking Exchange 

FTX had perhaps $32 billion in equity value a year ago. Enron investors lost perhaps $74 billion.  Lehman Brothers had equity losses of about $60 billion (by some accounting $46 billion in equity destruction) although debt holdings were far larger, up to $613 billion or so, balanced against assets. 

But Lehman equity and debt losses, in total, might have reached as much as $135 billion.  

At least so far, FTX does not begin to approach the damage triggered by Enron’s collapse or Lehman Brothers demise. Enron’s bankruptcy occurred at about the time of the “Dot Com Collapse” around the turn of the century, which destroyed hundreds of billions of dollars of equity value in telecommunications and technology and app firms. 

Lehman’s bankruptcy helped bring on the global Great Recession of 2008. So far, FTX appears to pose none of that magnitude of danger.

Gigabit Services are Right on Schedule According to Edholm's Law and Nielsen's Law

U.S. home broadband customers buying gigabit tiers of service grew 35 percent year over year in the third quarter of 2022, according to Openvault. At the moment, more than 15 percent of U.S. home broadband accounts use gigabit connections. 

Also, more than half of home broadband accounts buy service in the 200 Mbps to 400 Mbps range. That group grew 100 percent year over year. 

A little more than a year ago about half of households were buying service in the 100 Mbps to 200 Mbps range, showing that Nielsen’s Law and Edholm’s Law of bandwidth supply continue to operate. 

source: Openvault 

Edholm’s Law states that internet access bandwidth at the top end increases at about the same rate as Moore’s Law suggests computing power will increase. Nielsen's Law essentially is the same as Edholm’s Law, predicting an increase in the headline speed of about 50 percent per year. 

Nielsen's Law, like Edholm’s Law, suggests a headline speed of 10 Gbps will be commercially available by about 2025, so the commercial offering of 2-Gbps and 5-Gbps is right on the path to 10 Gbps. 

source: NCTA  

Headline speeds in the 100-Gbps range should be commercial sometime around 2030. 

How fast will the headline speed be in most countries by 2050? Terabits per second is the logical conclusion. Though the average or typical consumer does not buy the “fastest possible” tier of service, the steady growth of headline tier speed since the time of dial-up access is quite linear. 

Gigabit tier subscribers hit an inflection point last year. The rule of thumb is that any successful and widely-bought consumer technology enters its mass adoption phase when about 10 percent of homes are users. For U.S. gigabit adoption, that happened in 2021. 

Some might attribute the Covid pandemic and work from home as driving the change, but adoption rates would have taken off in 2021 in any case, as predicted by the 10-percent-of-homes adoption theory. 

It also is easy to predict that 2 Gbps to 4 Gbps is the next evolution, as speeds at the top end continue to increase by 50 percent a year. Ny 2025 we should start seeing the first 10-Gbps services deployed at scale.

What Business are You In?

From time to time, "telcos" and "access providers" (ISPs, cable companies, satellite firms and system integrators) essentially ask themselves "what business are we in?" and "what business should we be in?" In nearly all cases, those questions are answered in a way that suggests the solution is "we need to be in X, in addition to our present business." X can be marketing, advertising, internet of things, private networks, edge computing, content ownership, content retailing or some enterprise vertical.

In the past, telcos have tried to be in computing hardware and software, app stores, data centers or consumer hardware. Success has been mixed at best. In the internet era, when all access service providers have adopted internet platforms as their next-generation network, almost all efforts to find X will require moving into some different part of the internet ecosystem.

But startups often face tougher issues. Telcos at least know who their customers are, where they are located, why they buy, what the minimum viable product is, where price points must be set, competitor strengths and weaknesses, how distribution channels work at scale, and so forth.

New industries or product categories sometimes are hard to pinpoint, when defining contestants in a “market.” Kyte, for example, says it is in the “on-demand vehicle rental business.” But its business model includes having a Kyte driver deliver the vehicle to the renter’s location. So Kyte might be competing with Uber, Lyft or other ride hailing apps to an extent. 

In a larger sense, as ride hailing competes with use of taxis and public transportation and car ownership, Kyte might be viewed within a larger transportation market. 

Such market definitions remain even for contestants in more-established markets. Is Amazon a contestant in cloud computing? Yes. Is it also a contestant in online retailing or retailing in general? Yes. Is it a competitor in video and audio streaming? Also yes. Is it a retailer of consumer electronics devices? Yes, again. 

Defining a market matters for startups. It matters for market researchers, who must decide who the participants are in a market before quantifying their market shares. It matters for business leaders who must benchmark against their key competitors and craft growth strategies to match.  

A firm must define its market to understand where to compete, who its cusotmers are and who are the key trading partners. Defining markets also helps firms focus on what their customers value.

Perhaps the classic example is railroad operators. “The railroads  did not stop growing because the need for passenger and freight transportation declined,” noted marketing professor 

Theodore Levitt. “The railroads are in trouble today not because that need was filled by others (cars, trucks, airplanes, and even telephones) but because it was not filled by the railroads themselves.”

In other words, they saw themselves as in the “railroad” business, not the “transportation” business.

Expect 70% Failure Rates for Metaverse, Web3, AI, VR Efforts in Early Days

It long has been conventional wisdom that up to 70 percent of innovation efforts and major information technology projects fail in significant ways, either failing to produce predicted gains, or producing a very-small level of results. If we assume applied artificial intelligence, virtual reality, metaverse, web3 or internet of things are “major IT projects,” we likewise should assume initial failure rates as high as 70 percent.

That does not mean ultimate success will fail to happen, only that failure rates, early on, will be quite high. As a corollary, we should continue to expect high rates of failure for companies and projects, early on. Venture capitalists will not be surprised, as they expect such high rates of failure when investing in startups. 

But all of us need to remember that failure rates for innovation generally and major IT efforts specifically will have high failure rates of up to 70 percent. So steel yourself for bad news as major innovations are attempted in areas ranging from metaverse and web3 to cryptocurrency to AR, VR or even less “risky” efforts such as internet of things, network slicing, private networks or edge computing. 

Gartner estimated in 2018 that through 2022, 85 percent of AI projects would deliver erroneous outcomes due to bias in data, algorithms or the teams responsible for managing them.

That is analogous to arguing that most AI projects will fail in some part. Seven out of 10 companies surveyed in one study report minimal or no impact from AI so far. The caveat is that many such big IT projects can take as much as a decade to produce quantifiable results. 

Investing in more information technology has often and consistently failed to boost productivity, or appear to have done so only after about a decade of tracking.  Some would argue the gains are there; just hard to measure, but the point is that progress often is hard to discern. 

Still, the productivity paradox seems to exist. Before investment in IT became widespread, the expected return on investment in terms of productivity was three percent to four percent, in line with what was seen in mechanization and automation of the farm and factory sectors.

When IT was applied over two decades from 1970 to 1990, the normal return on investment was only one percent.

This productivity paradox is not new. Even when investment does eventually seem to produce improvements, if often takes a while to produce those results. So perhaps even AI project near-term failure might be seen as a success a decade or more later. 

Sometimes measurable change takes longer. Information technology investments did not measurably help improve white collar job productivity for decades, for example. In fact, it can be argued that researchers have failed to measure any improvement in productivity. So some might argue nearly all the investment has been wasted.

Most might simply agree  there is a lag between the massive introduction of new information technology and measurable productivity results.

Most of us likely assume quality broadband “must” boost productivity. Except when it does not. The consensus view on broadband access for business is that it leads to higher productivity. 

But a study by Ireland’s Economic and Social Research Institute finds “small positive associations between broadband and firms’ productivity levels, none of these effects are statistically significant.”

Among the 90 percent of companies that have made some investment in AI, fewer than 40 percent report business gains from AI in the past three years, for example.

Dramatic Rethinking of Where FTTH Makes Sense Earns Mercury Broadband PE Investment

Mercury Broadband, an internet service provider serving rural customers near Topeka, Ks., has gotten an investment of up to $230 million from private equity  investment firm Northleaf Capital Partners.

The investment is part of a larger trend of private equity firms investing in digital infrastructure assets. The latest wrinkle is an increase in investment in rural ISPs able to leverage new government funding in rural areas where the bigger ISPs are unlikely to want to compete. 

Mercury Broadband is among firms that have secured Rural Digital Opportunity Fund (RDOF) grants by the Federal Communications Commission to bring fiber optic broadband to underserved communities, especially in rural areas. 

The construction is expected to add more than 12,000 plant miles and pass tens of thousands of locations. 

As a rule, the availability of RDOF grants lowers the fiber access plant capital investment hurdle by 30 percent or so. That, among other things, has dramatically reshaped thinking about when FTTH deployments make financial sense. 

The economics of connectivity provider fiber to the home  have always been daunting, but they are, in some ways, more daunting in 2022 than they were a decade ago. The biggest new hurdle is that expected revenue per account metrics have been cut in half or two thirds. That would be daunting for any supplier in any industry. 

These days, the expected revenue contribution from a home broadband account hovers around $50 per month to $70 per month. Some providers might add linear video, voice or text messaging components to a lesser degree. 

But that is a huge change from revenue expectations in the 1990 to 2015 period, when $150 per customer was the possible revenue target.  

You might well question the payback model for new fiber-to-home networks which assume recurring revenue between $50 and $70 per account, per month, with little voice revenue and close to zero video revenue; take rates in the 40-percent range; and network capital investment between $800 and $1000 per passing and connection costs of perhaps $300 per customer. 

But that is the growing reality. Among the reasons: higher government subsidies; indirect revenue contributions and a different investor base. 

All that has shifted fiber-to-home business models in ways that might once have been thought impossible. 

In the face of difficult average revenue per account metrics, co-investment and ancillary revenue contributions have become key. Additional subsidies for home broadband also will reduce FTTH deployment costs. All that matters as revenue expectations are far different from assumptions of two decades ago. 

“Our fiber ARPU was $61.65, up 5.3 percent year over year, with gross addition intake ARPU in the $65 to $70 range,” said John Stankey, AT&T CEO, of second quarter 2022 results. “We expect overall fiber ARPU to continue to improve as more customers roll off promotional pricing and on to simplified pricing constructs.”

Lumen reports its fiber-to-home average revenue per user at about $58 per month. For those of you who have followed fiber-to-home payback models for any length of time, and especially for those of you who have followed FTTH for many decades, that level of ARPU might come as a shock. 

Though some honest--and typically off the record--evaluations by some telco executives 25 years ago would have described the FTTH business model as “you get to keep your business” rather than “we boost revenue.” Few financial analysts would have been impressed with that argument. 

But revenue expectations were quite different back then. The thinking was that per-home revenue could range as high as $130 to $200 per month. 

Contrast that with today’s view, which is that monthly review per account is closer to $60 a month. And yet investors believe that provides a reasonable business case, in the right markets, with subsidies and a chance to create competitive moats.

Remote Workers Like It, C Suite Tends to Have Doubts

The general end of remote work at Twitter will be controversial in some quarters, for reasons related to differences of role between the C suite generally and employees generally. By now, mostly everyone who is an “employee” knows why they prefer remote work. Anecdotal evidence suggests that many workers can get “their work” done in far less time than seemingly was required in the past, allowing them more free time for “non-work” activities.

As welcome as “work-life balance” is for employees, C suite executives instinctively question the productivity implications. Leaving aside “control freak bosses who do not trust their employees,” there still is a growing body of evidence suggesting that, in fact, happier at-home workers are not “more productive.” They are just happier. 

Though is is counterintuitive, “happy workers” are not always “more productive.” Unhappy workers can be more productive; happy workers can be less productive or both can be equally productive. The nature of the work often dictates outcomes, not perceived happiness. 

Looking only at engineering output, for example, some studies suggest remote workers are less productive than similar workers “in the office.” 

“A study conducted in 2012 shows those office workers who were assigned boring tasks performed better and faster in the regular office setting. Home-life distractions are more likely to prevent productive work when you don’t enjoy the work,” notes Apollo Technical. 

On the other hand, the same study also found the reverse. More-creative work often were completed faster than “in the office.” 

But what many workers do with the extra time is the issue. Some will argue that if workers complete the minimum-required quantitative outputs, there is no harm. The same amount of work gets done and employees can simply use the extra time as they choose. 

But the same “group norms” hold for remote workers as for workers “in the office.” In other words (those of you who have worked union jobs know this well), there are disincentives for workers to outperform others, as it “makes the others look bad” and also tends to raise output expectations for the entire class of workers.

In other words, expected output levels will rise generally if enough workers in the class start producing at higher levels. That sort of behavior will be peer group discouraged. That will happen in both in office and remote settings. 

Another more recent study states that the more hours an individual works from home, the less productive they become, for the perhaps-obvious reasons that there are more distractions at home: pets, children, housework, household chores and entertainment options.

“Those who worked full time (eight  hours per day) at home are 70 percent less productive than those who don’t work from home,” says Apollo Technical. 

Leaving aside other issues, including the ability to structure self-supervised work effort, productivity, in principle, for some jobs, could be higher when knowledge work that can be conducted individually is performed. 

As a long-timer journalist, analyst and researcher who has worked remotely for 30 years, monitoring work is unnecessary when output can be quantified: so many stories per day, week or month; a major report delivered in three months’ time; a white paper produced by deadline. 

But not all jobs can be evaluated purely quantitatively. How does one measure the “quality” of computer instructions; a painting; a report; a story? But those intangibles exist no matter where the output is produced. 

Since it is nearly impossible--if not completely impossible--to measure knowledge worker and office worker productivity, much of what we think we know consists of opinion. So we really cannot say whether remote work “always” leads to higher productivity. It might just as often lead to lower productivity or equivalent output. 

What we might observe anecdotally is that lots of remote workers like remote work because it leads to “more free time.” They can use that free time to do other things than work. Whether employers have a “right” to expect more is a matter of debate. 

But it already seems clear enough that C-level executives question the productivity impact of widespread remote work. I suspect we would not be having discussions about quiet quitting, and much anecdotal evidence that remote workers get their work done faster, but then use their free time for non-work pursuits, if this were not the case.