Does Bandwidth "Want to be Free?"

About 25 years ago there was significant discussion in industry circles about the implications of essentially free bandwidth, computing and storage. Bandwidth providers were outraged by the suggestion, as you might guess. 

Around the turn of the century, Bill Gates irritated executives in the communications ecosystem by arguing that “bandwidth wants to be free? ” Others at the time quipped about whether “computing wants to be free?” Others might argue that data wants to be free. And some have been arguing that content wants to be free. 

Twenty years later, we are tempted to argue that Gates was more right than wrong, both about computing and bandwidth. 

To be sure, Gates did not mean computing or bandwidth would literally “cost nothing.” He only meant that neither computation nor bandwidth would not be a constraint to creating new services and apps. 

In 2004, Gates argued that “10 years out, in terms of actual hardware costs you can almost think of hardware as being free — I’m not saying it will be absolutely free — but in terms of the power of the servers, the power of the network will not be a limiting factor,” Gates said.

You might argue that is a position Gates adopted recently. Others would argue that has been foundational in his thinking since Micro-soft was a tiny company based in Albuquerque, New Mexico in 1975.

Young Bill Gates reportedly asked himself what his business would look like if hardware were free, an astounding assumption at the time. Keep in mind the audacious assumption Gates made. In 1970 a computer cost about $4.6 million each. 

The original insight for Microsoft was the answer to the question "What if computing were free?". Recall that Micro-Soft (later changed to Microsoft) was founded in 1975, not long after Gates apparently began to ponder the question. 

source: AEI 

In 1982 Gates did not seem to go out of his way to argue that hardware would be free, but he did argue it would be cheaper and far less interesting than software. 

 Gates made the argument in 1994. Gates was still saying it in 2004.  

The point is that the assumption by Gates that computing operations would be so cheap was an astounding leap. But my guess is that Gates understood Moore’s Law in a way that the rest of us did not.

Reed Hastings, Netflix founder, apparently made a similar decision. For Bill Gates, the insight that free computing would be a reality meant he should build his business on software used by computers.

Reed Hastings came to the same conclusion as he looked at bandwidth trends in terms both of capacity and prices. At a time when dial-up modems were running at 56 kbps, Hastings extrapolated from Moore's Law to understand where bandwidth would be in the future, not where it was “right now.”

“We took out our spreadsheets and we figured we’d get 14 megabits per second to the home by 2012, which turns out is about what we will get,” says Reed Hastings, Netflix CEO. “If you drag it out to 2021, we will all have a gigabit to the home." So far, internet access speeds have increased at just about those rates

How many business models, products and services now are routine and feasible because Moore’s Law keeps driving higher performance and lower cost? How many applications are possible because bandwidth keeps growing in a similar manner? 

Video streaming, early virtual reality and augmented reality, ridesharing, advanced smartphone features, use of millimeter wave spectrum for 5G and all forms of applied artificial intelligence for search, e-commerce and customer service are feasible because computing and bandwidth performance increase while costs are contained. 

Think about the application of computing over time, in situations where business models formerly unthinkable can become quite practical because the cost of computation and storage have become so cheap. 

The key insight is to ask “what would my business look like?” if communications, bandwidth, computing, storage or information or any other scarce or costly input were so available and low cost that those ceased to be constraints to a revenue model. 

The question might also be asked the other way: what does your business look like if a key input becomes too expensive? The key inputs could be labor, knowledge, a raw material, a logistics or supply chain change. 

A related question is “what does my business look like if demand changes in a major way?”

Google, Netflix, Amazon, Apple, Facebook, Square and many other examples illustrate what is possible when computing, communications, devices, transactions and information suddenly cease to be barriers.

But Gates was substantially correct. How many these days would argue against the notion that most public Wi-Fi access is substantially free?

“You can’t use today’s technology constraints to predict tomorrow’s developments,” says Amadeus Consulting CTO John Basso. That fundamental insight, based in large part on Moore’s Law, might once again be more important than often is believed.

You could argue whole businesses now are built on the assumption that technology (especially hardware) constraints disappear over time. All cloud-based apps are built on such assumptions.

Anything we see in consumer internet applications--where capabilities are supplied at no cost to users--provides an excellent illustration. The classic question is what does your business look like if a key cost constraint is removed. 

Though we might have mischaracterized key elements of the argument, ride sharing did raise questions about what it would mean if “cars were free.” They obviously are not “free,” but personal transportation based in part on ride sharing does in some cases affect the case for car ownership. 

The important part of the question is imagining whether a business or product can exist, and what it looks like, if a key cost constraint is removed. 

There is almost never a physical world ability to create Moore’s Law rates of change that are possible in the computing world. But there are going to be many other opportunities in the spaces where computing can alter cost profiles. Think e-commerce in general, ridesharing, lodging apps, video and audio content streaming, videoconferencing, use of millimeter wave spectrum that in an analog technology world is not commercially usable for home broadband. 

But it is hard and unusual to ask the right question: what does my business look like if a key cost input is removed?

Metaverse, Web3, Blockchain, VR, AR, 5G: Less Change Than You Expect, Early On; Far More Change Than You Expect in a Decade or Two

I learned early in my career making forecasts that it is better to conservative in the early going. Consider that an application of the maxim that humans tend to overestimate near-term impact of any technology and underestimate the long-term impact. 

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run” is one way of stating the principle. So is “We always overestimate the change that will occur in the short term and underestimate the change that will occur in the long term.”

Or, “People overestimate what can be done in one year, and underestimate what can be done in ten.” All three statements capture the wisdom of how significant new technologies create change. 

There is a bit of business wisdom that argues we overestimate what can be done near term, but underestimate the long term impact of important technologies or trends. The reason is that so many trends are an S curve or Sigmoid function. 

Complex system learning curves are especially likely to be characterized by the sigmoid function, since complex systems require that many different processes, actions, habits,  infrastructure and incentives be aligned before an innovation can provide clear benefit. 

source: Rocrastination 

Also, keep in mind that perhaps 70 percent of change efforts fail, the Journal of Change Management has estimated. We might then modify our rules of thumb further, along the lines of “even as 70 percent of innovations fail, we will see less change than we expect in one year and more change than we expect in 10 years.” 

At least in part, technological impact increases over time for reasons of diffusion (what percentage of people use the technology regularly) as well as enculturation (it takes time for people and organizations to figure out how to best use a new technology). 

Impact arguably also increases as the ecosystem grows more powerful, allowing many more things to be done with the core technology. 

So, applied to 5G, the metaverse, Web3, augmented or virtual reality, blockchain or just about anything else, we will see less early impact than expected, but far more long-term change than we presently imagine.

Would Home Broadband "Utility" Regulation Lead to Lower Prices?

It never is entirely clear to me what people mean when they argue internet access or home broadband home broadband “should be a utility,” or that such services already are a utility similar to  electricity, gas, water, sewers, phone lines, roads, seaports or airports. 

Some might mean home broadband should be, or is, a public utility in the sense of “common carrier” with obligations to serve the general public. Though most of us would undoubtedly agree with that notion, telecom policy already has such goals. That is why we have universal support support funds and subsidies for operators in high cost areas. 

Others might mean essential or regulated in terms of price or conditions of service. That might imply regulated prices and terms and conditions of service. 

Others might fix on the used everyday sense of the term, which is that internet access is fundamental for inclusion in normal life, as are electricity, fresh water, wastewater services, garbage collection. It might mean that home broadband is essential in the same way that roads, schools, medical care, food supply, airports and seaports are necessary to support life. 

None of that seems to capture the implied meaning that home broadband should be a utility. More likely, there is some expectation that things would be better if prices, coverage, terms and condition of service were regulated in ways that led to lower prices, less competition or some combination of the two. 

And that should raise serious questions. There was a time when all “telecom services” were regulated as monopoly public utilities. But prices were high and innovation low, under that framework. Ironically, if what people mean is that internet access should be a regulated monopoly, the outcome would almost certainly be higher prices and less innovation; lower rates of quality improvement and other forms of customer value. 

Were home broadband regulated, we would see less innovation and investment as well, as potential suppliers would find they cannot make a positive business case. 

   

source: Market Business News 

As it pertains to “home broadband,” generally the term refers to fixed network supply of home broadband, not mobile network supply. 

The expectation that utility regulation would lead to lower prices is almost certainly wrong.

Most of us are too young ever to have experienced “connectivity services” as a public utility. But prices were not uniformly low. 

In 1984, before the breakup of the U.S. AT&T monopoly, calling between states cost about 90 cents a minute. In 1955, a phone call between Los Angeles and San Francisco (not even interstate) cost about 70 cents a minute, not adjusted for inflation.

In 2022 currency that would be about $7.75 per minute. So, no, prices were not uniformly lower under monopoly or public utility regulation. 

Of course, that was by policy design. High long distance charges and high business services were intended to subsidize consumer local calling. 

Were home broadband to become a regulated service, something similar would happen. While prices for some features and plans might be price controlled, other elements of value would increase sharply in price. 

And price is only one element of value. Service innovation was sharply limited in the monopoly era. In the U.S. market, consumers could not own their own phones, or attach third party devices to the network. All consumer premises gear had to be purchased from the phone company, for example. 

To be sure, AT&T Bell Labs produced many innovations. But they were not directly applied to the “telephone service” experience. Those included Unix, satellite communications, the laser, the solar cell, the transistor, the cellular phone network, television and television with sound. 

Though ultimately quite important, none of those innovations arguably applied directly to the consumer experience of the “phone network” or its services. 

The point is that monopoly regulation tends to produce varied prices for different products (some subsidized products, some high-cost products), but also low rates of innovation in the core services. 

Utility regulation would likely not wind up being as beneficial as some seem to believe. Be careful what you wish for.

"Sending Party Pays" is a Classic Example of Channel Conflict

Whatever positions one takes on whether a few hyperscale app providers ought to pay fees to internet service providers, there is no question that the emergence of the internet as the next-generation “telco” platform raises tricky issues about business models, competitive dynamics and available supplier responses. 

Differences in regulation of “public telephone networks,” radio and TV broadcast, cable TV and data networks always have existed. Those differences are exacerbated now that the internet has effectively become a universal distribution system for all content, communications and media. 

“Sending party pays” is a new concept that would make a few hyperscalers pay ISPs for usage by ISP customers. Ignore for the moment whether that is just, fair or reasonable. The concept highlights new business model strains in the internet ecosystem between content owners and distributors. 

Sending party pays also illustrates changes in the ways regulators might--or could--change their thinking about how to regulate various communication networks. There also are major issues around how much value chain participants can, or should, work out business agreements between themselves. 

That also necessarily raises questions about where value lies in the ecosystem, and what policies best promote the growth and health of the ecosystem. Industrial policy also is inextricably interwoven in those choices. 

Value chains are different for the internet, compared to traditional “telecommunications.” Traditional voice is a vertically-integrated app created, controlled and sold by telcos over their own networks. Enterprise wide area data networks provide another example. 

The internet is different: it consists of loosely-coupled ecosystem partners operating on “open” rather than “closed” networks. No app or content or commerce provider needs an internet service provider’s permission to be used by any internet-connected user (government permission is another matter). 

In other words, an ISP’s customer buys internet access service. The ISP does not control access to any internet-available app, service or site, and does not participate in a direct way in monetization of those apps, services and sites. 

source: Kearney 

Like it or not, an ISP’s role in the ecosystem lies in supplying internet access to its own customers. Some ISPs might also participate in other roles, but in their role as access provider, their revenues are based on access customer payments, supplemented in some cases by universal service payments, government subsidies or, in a few cases, advertising. 

That does not mean ISPs are barred from other roles and revenue streams. It does mean that in their role as access providers, their customers are the revenue drivers. 

That has been the general pattern for home broadband and mobile internet access: customers pay based on consumption, or potential consumption, with mobile services having the clearest consumption-based pricing. 

Mobile buckets of usage differentiated by potential consumption limits have been the norm, where for fixed networks “speed” has been the mechanism for pricing differential. 

The big principle is that the usage is paid for by the access customer. The proposed new taxes on content providers move beyond that framework, making a few content providers liable for usage, not just the access customers. 

At a high level, this is a somewhat normal sparring between buyers and sellers in a value chain, where one partner’s costs are another partner’s revenue. But there are issues. If an electrical utility requires more generation capacity, it has to build new power plants, encourage conservation or take other steps to match generation with consumption. 

If a water utility has to support more customers, homes and businesses, it has to increase supply, by building dams, acquiring new rights to tap aquifers or other bodies of water, or discourage consumption restraint, or both. 

There is an obvious remedy that ISPs have not taken, possibly because they feel they cannot do so: raise prices on customers (subscribers) that recover the costs of network capacity. Nor do ISPs generally take any measures to encourage conservation. They could do so; they simply do not. 

With the caveat that there are revenue or business reasons for such inaction, it nevertheless remains the case that ISPs could act themselves to better match capacity supply with customer demand.

Assuming network neutrality rules are not a fundamental issue, ISPs also could institute policies for trading partners that likewise discourage “wasteful” bandwidth consumption practices, such as enabling autoplay video. 

ISPs need the right to do so, if such practices benefit their customers by reducing the need to invest in new capacity at high rates without any compensation for doing so. 

To be sure, the problem results from the economics of delivery networks. Content delivery networks are most efficient when they can operate in multicasting mode (broadcasting). Those networks are least efficient when they must operate in unicast mode (traditional voice sessions or any form of on-demand access). 

In principle, edge-based content delivery networks help reduce wide area network capacity demand. It is never so clear even content delivery networks alleviate access network congestion, though. 

That leaves a few levers yet not pulled: raise subscriber prices to approach the full costs of actual usage, and create incentives for conservation. Subscribers could be rewarded for downloading content overnight (when networks have spare capacity), stored locally and then consumed later. 

Stripped to its essentials, channel conflict is what the telco-hyperscaler “sending party pays” proposals are about.

Big Companies Good at Innovation are Rarities

Practitioners of innovation almost always believe their chances of succeeding are quite high. They would not make the effort unless they did believe that was the case. But, statistically, innovation tends to be quite hard. Consider venture capital, which is innovation with clear or+metrics for success

A general rule of thumb for venture capitalists is that 75 percent of venture capital startups fail completely. Another three or four return the original investment, and one or two produce virtually all the significant financial returns. 

Also, keep in mind that perhaps one percent of proposals actually wind up getting funding. 

According to Cambridge Associates. Information technology digital media startups from 2001 to 2011 produced uneven multiples of the original investment. In more than 60 percent of cases, the startups did not earn enough to produce a return on invested  capital. About seven percent of all funded companies are able to produce returns in excess of five times the original investment. 

source: jtangoVC 

So outright failure is the case at least 63 percent of the time. Another 30 percent produce an actual return. Less than one in ten are big winners. 

Some studies suggest 74 percent of digital transformation efforts fail. Historically, most big information technology projects fail. BCG research suggests that 70 percent of digital transformations fall short of their objectives. 

From 2003 to 2012, only 6.4 percent of federal IT projects with $10 million or more in labor costs were successful, according to a study by Standish, noted by Brookings. IT project success rates range between 28 percent and 30 percent, Standish also notes. The World Bank has estimated that large-scale information and communication projects (each worth over U.S. $6 million) fail or partially fail at a rate of 71 percent. 

McKinsey says that big IT projects also often run over budget. Roughly half of all large IT projects—defined as those with initial price tags exceeding $15 million—run over budget. On average, large IT projects run 45 percent over budget and seven percent over time, while delivering 56 percent less value than predicted, McKinsey says. 

Beyond IT, virtually all efforts at organizational change arguably also fail. The rule of thumb is that 70 percent of organizational change programs fail, in part or completely. 

Of the $1.3 trillion that was spent on digital transformation--using digital technologies to create new or modify existing business processes--in 2018, it is estimated that $900 billion went to waste , say Ed Lam, Li & Fung CFO, Kirk Girard, former Director of Planning and Development in Santa Clara County and Vernon Irvin Lumen Technologies president of Government, Education, and Mid & Small Business. 

All that accumulated experience helps us understand why innovation so often comes from the young, who have less to lose; from small firms rather than big, established firms; from outside an industry rather than from within it. 

A rational actor in any large, established industry or firm has more to lose than to gain from an attempt at innovation: odds of success are three in 10. A small attacker might well conclude that those odds are worth the effort, especially if the attacker is led by young people who can survive an early failure or two with little long-term damage. 

Quite the opposite is true for older leaders who have risen to the top precisely because they know how the legacy business runs, and benefit from it. A professional manager who expects to remain in the top post for less than a decade has much more to lose than to gain by any serious effort to transform the existing business model. 

When the person at the top of any big organization is three to five years away from retirement, what else would you expect, other than behavior that is basically “do not mess it up?” 

The upshot is that innovation is risky, destined to fail seven times out of 10. “Letting someone else take the risk of attempting innovation” therefore can appear a wise strategy. The exceptions often occur when a firm’s core business model is unraveling. Then the risk of trying to innovate is less than the risk of staying a failing course. 

There seems to be far less research done on how successful firms are at rescuing themselves from failing business models. Impressionistically, the odds are even worse than seven out of 10, as the common remedy is a sale of the asset to some other entity, assuming outright bankruptcy is avoided.

After the Big Fiber Builds, Consolidation

Somewhere in excess of 68 percent of U.K. consumers now can buy home broadband services at gigabit speeds, though fiber to the premises covers only about 37 percent of U.K. homes and business locations, according to Ofcom. 

source: Ofcom 

More important, from BT’s standpoint, is actual retail customer adoption, which seems to be about 27 percent of homes passed. That is a problem, balanced somewhat by Openreach wholesale sales. 

If one assumes that any fiber-to-home network is sustainable with a minimum of about 30 percent take rates (actual paying customers as a percentage of locations passed), then BT has a bit of a way to go to reach sustainability. 

“For their models to work, most operators assume a 40 to 50 percent penetration rate,” say analysts at Kearney. That arguably applies to larger internet service providers with legacy operations, rather than upstarts that typically have lower operating costs. 

“The difference in net present value between a 50 percent and a 30 percent penetration rate may well be the difference between a positive NPV and a loss,” they note. 

That can be difficult in a multi-supplier market with three or more competent suppliers of fixed access, plus two or three suppliers of fixed wireless targeting. 

If one believes that three to six suppliers is too many in the home broadband business, then consolidation seems inevitable.

Linear TV Value Prop Keeps Getting Worse

Linear TV subscriptions have been cannibalized by video streaming alternatives for a decade, partly because on-demand provides more value; partly because some like the lower cost per service; partly because linear value now increasingly comes down to sports, news and unscripted reality content. 

But lower overall cost seems less and less a value driver, as many consumers buy four or more streaming services. Most scripted content has largely shifted to streaming delivery. 

source: Ark Investment 

A recent survey by FinanceBuzz of 1,000 U.S. adults found that 24 percent of households are buying “at least three additional streaming services than they did one year ago,” while another 21 percent of respondents are now paying for two more streaming services.

The point is that consumers are buying multiple services at a higher rate than they did five to 10 years ago. 

source: Financebuzz 

About 25 percent of respondents spend more than $75 per month on streaming subscriptions. If you assume the typical linear service costs between $60 and $80 a month, it is clear that consumers are not buying streaming services because the necessarily save money. 

The issue is where linear TV value will lie, as the shift of scripted content to streaming continues. Even sports now are shifting to streaming delivery, leaving unscripted reality shows and news as the anchors for linear. That will be a declining value proposition for a greater range of customers over time. 

I, for example, never watch anything but sports or news on linear, so the entire value proposition comes from just those two types of programming. Most channels never get watched, which always was true, even before streaming. 

But the whole value-price relationship keeps getting worse. Not that many younger people watch news channels and more sports content is moving to streaming, perhaps leaving unscripted reality TV as the last bastion of “value” for linear TV, assuming one watches that genre. 

The point is that it is fairly hard to justify spending $60 to $80 a month for what boils down to regular viewing of two news channels and one-season viewing of up to two sports channels. The only channels that get watched all year are the two news channels. Looked at that way, the value proposition is even worse.