Another Co-Investment for FTTH: Liberty Networks Germany

Liberty Networks Germany, a joint venture between Liberty Global Ventures and InfraVia Capital Partners, has started construction on a new fiber to premises network in Germany. That move is only part of a broader co-investment trend happening in the access business. 

Investment firm Meridiam is co-investing in fiber-to-home infrastructure with T-Mobile in Austria, each firm investing about a billion euros to construct facilities reaching 650,000 homes in rural areas and small towns. 

The firm began investing in digital infrastructure in 2000, and has made prior FTTH  investments in Germany and Canada. 

The deal essentially solves a problem for Magenta Telekom, namely the high cost of wiring rural and lower-density homes. 

Liberty Global, Telefonica and InfraVia Capital Partners have created a joint venture on a larger scale, aiming to build FTTH past seven million U.K. homes. 

Such moves represent a change in thinking  on the part of fixed network internet service providers, who historically have favored fully-owned access infrastructure. But high capital requirements and heightened risk have led to more willingness to give up full ownership of access infrastructure. 

Telefónica Group, Crédit Agricole Assurances and Vauban Infrastructure Partners are joining to create Bluevia Fibra to build fiber to premises networks in rural parts of Spain. 

The consortium formed by CAA/Vauban will acquire a 45 percent stake in Bluevia from Telefónica España. Telefónica Group will retain a 55 percent stake in Bluevia. 

The 55 percent stake owned by Group Telefónica will be held by Telefónica España and Telefónica Infra, with 30 percent and 25 percent stakes respectively.

Operating with a wholesale model, Bluevia will offer wholesale FTTH access to all telecommunication services providers. Based on an initial footprint of 3.5 million premises currently passed, Bluevia will increase its network to five million premises by 2024.

Bluevia’s anchor tenant, as you might guess, will be Telefónica España. The deal is among many globally where service providers try to decrease the cost of building new infrastructure by partnering with investment firms looking for long-term, stable cash flows in the digital infrastructure area.

Is 1996 Internet Experience Comparable to 2022? Is a Rose Still a Rose?

When is a rose no longer a rose? When is an apple an orange? If you used the internet in 1996, and use it today, is the experience so qualitiatively different that we are talking two different things? 

That is the practical implication of changes in product quality over time, known by economists as hedonic change. 

“Hedonic” changes are hard to quantify, but are crucial in the internet and computing businesses, as improvements in product quality are assumed to exist as a routine and fundamental matter. 

A dial-up internet access product is not the same as a gigabit internet connection. A mobile phone or personal computer that is 20 years old is arguably not the same product as a top of the line device in 2022. 

The same applies to application experiences. Amazon.com offers an experience which arguably is different from a character-only bulletin board of 1990. So does Uber or Google Maps. 

Hedonic adjustments--not to mention indexing for inflation--is crucial for evaluating home broadband as well. Price is one matter; quality (speed, for example) another matter. 

One analysis of home broadband prices using hedonic adjustment showed that speed and price both varied across countries in the Organization for Economic Cooperation and Development in 2016. 

source: Semantic Scholar 

The point is that comparing typical prices has to be qualified by typical speed (and currency differences). A 25-Mbps service in one country and a 800-Mbps service offered at the same currency-adjusted price in another country might arguably represent different products, values and “real” prices when evaluating both quality and quantity.

Assumptions Drive Forecasting Success and Error

If you have ever been called upon to build a financial model or market forecast for any sort of product, you know such models are exceedingly sensitive to the assumptions used to create the model. 

So difficult are such projections that clients might well--n volatile or brand-new markets--be satisfied with forecasts that miss within an order of magnitude (10 times eventual reality). Any forecaster missing by that much in an established market will have problems, as divergence from reality should never reach two to three times the actual circumstances. 

But that can happen--even in mature markets--when forecasters use accurate data without considering the assumptions about that data. 

Cable TV operators in many markets, for example, sell multiple products, but send a single bill. And that can lead to false assumptions about household spending, for example. Is “average” U.S. household spending on linear video closer to $200 per month or $80 per month? It matters. 

Some use the higher figure, but the actual figure is closer to the latter. The mistake is easy to make. A household purchasing linear video and internet access plus either fixed network voice or mobile service could spend, “on average,” $200 or more per month. 

Using either a median or mean approach to generating “average,” the point is that it is reasonable for an “average” video charge to be in the $60 per month to $80 per month range, before bundling discounts. 

source: S&P Global Market Intelligence; Fierce Video 

The point is that all forecasts are extremely sensitive to assumptions made about future developments, but also about current behavior. 

Ignore for the moment the assumption that growth rates are predictable or that no unexpected macroeconomic events will occur. It is quite easy to make faulty assumptions based on an incorrect understanding of user behavior, costs or potential revenues. 

Risk of this sort arguably is lessened when the modeler has access to multiple different data sources; different methodologies for estimating the current size of the market for any product and  domain knowledge.

Would Utility Regulation Really Lead to Lower Prices?

One frequently hears that home broadband or internet access is a utility similar to  electricity, gas, water, sewers, phone lines, roads, seaports or airports. It is not always clear what proponents of viewing home broadband “as a utility” have in mind when they say such things.

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. Others might mean essential or regulated in terms of price or conditions of service. Others might fix on the used everyday sense of the term.

Classically, the term referred to industries that operated as monopolies, often because they are capital intensive and difficult to replicate. 

   

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 common unstated reason for calling for utility treatment seems to be the expectation that this means lower prices. Actually, it is not clear how prices might be affected. True, some elements of consumer service were price controlled. But other elements were horrendously expensive.

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? It would not wind up being as beneficial as some seem to believe.

Supply and Demand are Dynamic, So Sometimes You Get the Opposite Result from What You Expected

If you have you ever noticed that adding more lanes to an expressway often does not seem to less auto congestion, you are seeing a dynamic supply-demand response in action. 

So one wonders: if video chat for customer service really becomes popular because it works so well, demand might well grow so much that response times are slowed. thus creating an outcome the opposite of what was intended. 

Economist John List talks about this inThe Voltage Effect. Uber wanted to reward its drivers so it raised wages. The higher wages attracted more drivers. So average wages declined, instead of increasing. 

Uber issued discounts to stimulate demand, which apparently worked for a short time. But that demand also lengthened wait times, which depressed demand. 

Supply and demand are dynamic. What you get sometimes is the opposite of what you intended. 

No Productivity Boom from New IT or Remote Work?

It seems incontestable that knowledge and office workers prefer remote working. Whether such work results in higher, lower or no change in productivity is among the issues, though. 

Some economists say there was no post-Covid productivity increase, despite the information technology investment boom that happened during the pandemic lockdown. That is not surprising. 

There long has been a lag--sometimes lasting a decade--before big IT investments show up as correlated with higher productivity. It can be argued that the places new IT was deployed are not likely to grow productivity. 

Supply chain investments might or might not contribute to productivity, even if they improve resilience. Investments in security, remote work, personal computers and so forth likewise might or might not contribute to any measurable lift in productivity, even over a five-year time frame. In fact, to the extent such investment were necessary simply to allow work to continue, and might actually be duplicate investment of sorts (people already had computers and broadband at work), they might reduce output, compared to input. 

Work-life balance arguably is better. But is that necessarily good for productivity? It is terribly hard to say. 

Outcomes also often are based on team output, not individual output. In such cases it is team productivity that matters. And such output often is intangible. How do you properly measure an intangible?  

To be sure, such measurements always are difficult, whether we are looking specifically at post-Covid or “during Covid” time periods or non-Covid times. 

Where it comes to knowledge or office workers, some might say the task is nearly impossible. Indeed, observers often note the difficulty before proceeding to argue such measurements can be made. 

Whether measurements actually can be made remains debatable. The point is that all our discussions about the productivity of remote work are opinions, not facts. We mostly cannot measure knowledge worker or office worker productivity, especially non-tangible outputs, whether remote or local.

Anna Karenina and Successful Startups

If you have ever worked at a startup that failed, the “Anna Karenina principle” will make sense to you. If success requires solving a number of key problems, then failure to solve just a single one of those problems produces failure. My personal experience is that failure happens as much as 70 percent of the time and perhaps closer to 100 percent over a decade’s time, if one considers acquisition to be an outcome or failure to scale outcomes that represent failure. 

To put it another way, failure goes through a wide gate; success through a very-narrow gate. 

source: slideshare 

The way I have come to understand that principle is an analogy to high walls, locked doors or hurdles. Success requires scaling a series of high walls; opening a series of locked doors or jumping over a series of hurdles. And each obstacle must be successfully navigated. Failure at any single obstacle kills the venture. 

source: Inc. 

Those obstacles can include failure to get the next round of funding; making a bad key hire; betting on the wrong product; launching too early or too late. Trying to solve the wrong problem; burning out the founding team; failure to manage remote teams; making the wrong pivot; lack of domain knowledge; team discord or lack of focus also are gates, hurdles or locked doors. 

Not “listening to customers” is a gate. But sometimes one has to ignore feedback as well. Poor marketing; lack of a viable revenue model; user interface problems; the wrong pricing model; a “too high” cost model; more-nimble competitors; having the wrong team; running out of cash before you are ready to go to market or misjudging the existence of a market also can be key hurdles, walls or gates. 

The point is that success requires success at every single obstacle. Failure requires only one obstacle not surmounted.