Friday, July 31, 2020

As 5G Focuses on Enterprise Use Cases, 6G Might Focus on Virtualized and Self-Learning Networks

Mobile and fixed network operators constantly are challenged to reduce capital investment and operating costs as a way of compensating for low revenue growth, challenged profit margins and ever-increasing bandwidth consumption by customers whose propensity to pay is sharply limited. 

The very design of future 6G networks might work to help reduce capex and opex, while incorporating much more spectrum, at very high frequencies and basing core operations on use of machine learning (a form of artificial intelligence that allows machines to learn autonomously). 

New 6G networks might rely even more extensively on virtualization than do 5G networks, featuring now-exotic ways of supporting internet of things sensors that require no batteries, a capability that would dramatically reduce IoT network operating costs. 

It is possible 6G networks will be fundamentally different from 5G in ways beyond use of spectrum, faster speeds and even lower latency. 6G networks might essentially be “cell-less,” able to harness ambient energy for devices that require no batteries and feature a virtualized radio access network. 


The “cell-less” architecture will allow end user devices to connect automatically to any available radio, on any authorized network. Harvesting of ambient energy will be especially important for internet of things devices and sensors that might not require any batteries at all to operate, reducing operating cost. 


source: IEEE


The virtualized radio access network will provide better connectivity, at possibly lower cost, as user devices can use the “best” resource presently available, on any participating network, including non-terrestrial platforms (balloons, unmanned aerial vehicles or satellites). 


Backhaul might be built into every terrestrial radio, using millimeter wave spectrum both for user-facing and backhaul connections, automatically configured. That will reduce cost of network design, planning and backhaul. 


Researchers now also say such federated networks will be based on machine learning (artificial intelligence), which will be fundamental to the way 6G networks operate. Devices will not only use AI to select a particular radio connection, but will modify behavior based on experience. 


The network architecture might be quite different from today’s “cellular” plan, in that access is “fully user centric,” allowing terminals to make autonomous network decisions about how to connect to any authorized and compatible network, without supervision from centralized controllers.


Though machine learning arguably already is used in some ways to classify and predict, in the 6G era devices might also use artificial intelligence to choose “the best” network connection “right now,” using any available resource, in an autonomous way, not dictated by centralized controllers.  


To be sure, in some ways those changes are simply extrapolations from today’s network, which increasingly is heterogeneous, able to use spectrum sharing or Wi-Fi access, using radio signal strength to determine which transmitter to connect with. 


Architecturally, the idea is that any user device connects to the radio access network, not to any specific radio, using any specific base station, say researchers Marco Giordani, Member, IEEE, Michele Polese, Member, IEEE, Marco Mezzavilla, Senior Member, IEEE, Sundeep Rangan, Fellow, IEEE, Michele Zorzi, Fellow, IEEE. 

source: IEEE


Overall, many 6G features will be designed to reduce the cost and improve the efficiency of the radio access network, especially to create “pervasive” connectivity, not just to add more bandwidth and lower latency for end users and devices.


Thursday, July 30, 2020

How Much More Can Tier-One Connectivity Suppliers Become Asset Light?

Occasionally over the last few decades, it has been proposed that telcos consider ways to become asset light operators. That advice--to monetize assets--continues to be offered. The issue is what portions of the infrastructure can be spun off or sold. 


In the U.S. market, asset light was recommended for competitive local exchange carriers, at one time able to buy “unbundled network element-provisioned” wholesale services at as much as a 40-percent discount to retail prices. 


In many international markets, mobile virtual network operators are a less-risky way to enter a new market. 


In Europe and other markets, bitstream and other forms of unbundled local loop access have been created to allow asset-light wholesale entry into the telecom market. 


From time to time, observers have speculated on the degree to which it might be possible for new competitors to use unlicensed spectrum assets such as Wi-Fi to create competition for mobile or fixed internet access. At the very least, cable operators and outfits such as Fon argue that a shared Wi-Fi network allows offloading of local mobile phone traffic, thus reducing purchases of wholesale mobile connectivity. 


In specialized areas, such as cell tower facilities, many mobile operators have concluded that sharing the cost of base stations with competitors or selling such assets (with leaseback) is a way to unlock value while becoming a bit more asset light. 


The new issue is whether it is possible to unbundle even more elements of a connectivity provider’s asset base, such as optical fiber facilities serving business customers. Attice, for example, recently sold 49.99 percent of its  Lightpath fiber enterprise business to Morgan Stanley Infrastructure Partners. 


Others have suggested that CenturyLink sell its optical network assets, or at least separate the consumer from the enterprise business. Right now, the enterprise part of CenturyLink accounts for 75 percent of revenue, the consumer business just 25 percent. 


source: S&P Global


Some assets are easier to separate than others. Cell towers and data centers are discrete assets many telcos have divested. In principle, the wide area networks could possibly be divested, though owner’s economics would still be an argument in favor of retaining that portion of their networks. As always is the case, volume improves the economics of owning assets. 


In principle, other new assets, such as small cell installations or backhaul facilities, might be candidates for infrastructure sharing, especially when it is possible to separate the value of facilities from the use of those capabilities to support the core customer experience. 


The issue is whether some operators might become so good at creating and monetizing intangible assets that they can risk shifting in the direction of asset-light or non-facilities-based operations on a wider scale. Few tier-one telcos have felt it was wise to divest access networks.


Access network assets remain quite scarce and therefore valuable in most markets and arguably are the hardest parts of the infrastructure to consider divesting. 


“If telcos do not reconfigure their value chains, other parties may step in, as disaggregated telco assets are being valued differently,” consultants at Arthur D. Little have argued. The problem is that creating more value remains a huge challenge, as the ability to enter new parts of the value chain, though risky for any participant, is asymmetrical. 


Connectivity represents about 17 percent of the revenue earned annually by firms in the internet value chain. The bad news is that connectivity share is dropping.

Has WFH Productivity Actually Held Up?

Nobody knows for certain how productivity might be affected, for different companies, industries and countries, as the enforced work from home policies stay in place. In the short term, as “everybody has to do it,” many studies have suggested an unexpected ability to maintain former output levels. 


What is not clear is how and what might change as the WFH period lengthens, and as firms make different strategic choices once the mandatory WFH period eventually ends. 


The point is that, with time, reader fatigue, Zoom fatigure, work from home burnout and lower productivity now are starting up show up, raising questions about whether permanent work from home policies will be as widespread--or useful--as many predict. 


And despite many claims that WFH productivity has been remarkably high, worker perception of their own productivity is not so clear. To be sure, near-universal WFH in office settings means no firm inherently benefits or loses. So far, since “everyone” has to do it, there appears no systematic advantage gained or lost.


All that will change when the Covid-19 pandemic winds down (because we have vaccines and most people take the vaccines, or herd immunity is gained). Then, WFH will be an option firms can choose, and the advantages and disadvantages might be accrued non-linearly by different firms. 


Also, WFH productivity in some pre-pandemic settings suggests WFH productivity is markedly lower than at the office work. Some early studies of WFH productivity also suggest productivity has dropped. 


That argument might puzzle some. The issue is the amount of useful work getting done, compared to the time spent to achieve those results. By definition, if the same results are obtained, but the time to create those results has increased, productivity is lower. 


Most studies of “productivity” during the pandemic WFH period essentially argue that firms aer able to produce the same results, even when most people are working remotely. What those studies sometimes neglect is the fact that many--if not most--of those at-home employees are putting in longer hours. By definition, then, we have “same results, more hours worked.” So productivity is lower, in that sense. 


Wednesday, July 29, 2020

Communications is Generally Good, Unless It Is Overhead

There is a good reason why work teams often are intentionally kept small: to get any work done at all, the amount of communications overhead has to be reduced. 


If you talk to people who work for large enterprises how much time they spend in meetings, many would say “almost all of my time.” Studies often find that senior managers spend at least half their time in meetings. Some estimate there are 56 million U.S. meetings each day


As the number of people you work with increases, communication overhead increases geometrically until the total percentage of time each individual must devote to group communication approaches 100 percent. 


After a certain threshold, each additional team member diminishes the capacity of the group to do anything other than communicate.


Large companies are slow because they suffer from communication overhead. “If you’re responsible for working with a group of more than five to eight people, at least 80 percent of your job will inevitably be communicating effectively with the people you work with,” argues Personal MBA.


That is one reason why some advocate meetings with no more than seven people. That is literally a rule of seven


Some might argue that is related to Miller's Law, which states that humans can only hold about seven items in short-term working memory. That is why Bell Labs designed U.S. phone numbers with seven digits. 


Likewise, span of control research suggests one person can only effectively and directly manage six people. That is why small teams are the building block of every military, and also applies to business “direct reports.”


That noted, work from home could have some impact on meeting length and frequency. Perhaps the good news is that meetings are shorter, if there are even more meetings to attend. 


Some research from Microsoft suggests the pandemic and dramatic increase in work from home has lead to more meetings that are shorter, suggesting many of those new shorter meetings were replacing informal communications that would have occurred in the office, but which are not possible when everyone is working remotely. 


The important point is that, as important as meetings are for communications and aligning group effort, they are, in effect, substitutes for actually accomplishing the organizational mission. “We can do meetings, or we can do work” might be a crude way of putting matters.


Tuesday, July 28, 2020

Definitions Matter

Minimums, median and maximum all are valuable indices in life, business and nature, including measures of internet access adoption or “quality.” It also has to be noted that constantly moving goalposts--changing our definitions--is a way of creating permanent problems.


That is not to deny the usefulness of revising our definitions over time. It is a truism that yesterday's power user is today's typical user


The percentage of U.S. customers buying internet access at the minimum speeds keeps dropping, as customers migrate to tiers of service that offer higher speeds at the same or only slightly-higher cost. 


But such definitions matter for both consumers and suppliers. Customers might sometimes buy services that actually are overkill. Most internet access customers buy what they believe is good enough to support their actual use cases, and rarely what is the “best” available level of service. 


Suppliers might imperil their business models by forcing investment in facilities that customers will not use, overprovisioning service in ways that raise sunk costs of doing business without providing capabilities customers actually buy. 


Those buying patterns also suggest why some ISP offers that are not state of the art can still be commercially viable. The reason is that, beyond a certain point, additional speed provides no tangible user experience benefit.  


And permanent problems are essential for those who claim to be in the business of “solving those problems.” That matters for education, health, disease, economies, social and economic equality, sports and just about anything else you can think of. In other words, one cannot marshall public policy support to solve a problem that does not exist.  


To be sure, our definitions of “broadband” have evolved, and will continue to evolve. 50 years ago, broadband was defined as any speed at 1.5 Mbps or faster. Once upon a time, Ethernet ran at 10 Mbps, while fiber to the home offered 10 Mbps. Today’s systems all run much faster than that. 


But it also makes a difference to “problem solvers” that definitions are revised upwards. Doing so always creates a “bigger problem.” 


Changing the minimum definition of broadband would shift the size of the “underserved” population or locations, for example. Today, perhaps 20 percent of U.S. buyers of fixed network internet access purchase services at the minimum speed of 25 Mbps. 


Changing the definition to 100 Mbps would increase the size of the underserved locations to nearly half of all buyers. Again, we will keep increasing both minimum levels of service, customers will keep changing the speed tiers they purchase and internet service providers will keep supplying faster speeds. 


The point, however, is that changing minimum definitions does not change the number or percentage of tiers of service customers purchase or that ISPs supply. Already, we find that the percentage of customers buying the fastest-possible speeds (at least 1 Gbps) is in mid single digits. 


More to the point, the typical buyer prefers a service offering 100 Mbps to 400 Mbps. Changing “minimum” to “average” has consequences, arguably distorting our understanding of “good enough” levels of broadband speed. 




Benchmarks are valuable when trying to measure “progress” toward some stated goal. A minimum speed definition for broadband access is an example. But that does not obviate the value of knowing maximum and median values, either, especially when the typical U.S. internet access buyer routinely buys services significantly higher than the minimum. 


In the first quarter of 2020, for example, only about 18 percent of U.S. consumers actually bought services running at 40 Mbps or less. All the rest bought services running faster than 50 Mbps. 


source: Openvault


An analysis by the Open Technology Institute concludes that “consumers in the United States pay more on average for monthly internet service than consumers abroad—especially for higher speed tiers.” 


As always, methodology matters. The OTI study examines standalone internet access plans, even if that does not account for the plans most consumers actually buy. The figures do not appear to be adjusted for purchasing power differences between countries. Were that done, it might be clearer that average internet access prices are about $50 a month, globally


Global prices are remarkably consistent, in fact, when adjusting for purchasing power conditions in each country.  


Nor does any snapshot show longer term trends, such as lower internet access prices globally since at least 2008. A look at U.S. prices shows a “lower price” trend since the last century. U.S. internet access prices have fallen since 1997, for example. 


source: New America Foundation


The OTI study claims that, comparing average prices between markets with and without a municipal system shows higher prices in markets with government-run networks. Not all agree with that conclusion. 


“The OTI Report’s data, once corrected for errors, do not support the hypothesis that government-run networks charge lower prices,” says Dr. George Ford, Phoenix Center for Advanced Legal and Economic Public Policy Studies chief economist. 


“Using OTI’s data, I find that average prices are about 13 percent higher in cities with a municipal provider than in cities without a government-run network,” says Ford. 


Our definitions of “broadband” keep changing in a higher direction. Once upon a time broadband was anything faster than 1.5 Mbps. Ethernet once topped out at 10 Mbps. 


Today’s minimum definition of 25 Mbps will change as well. The point is that having a minimum says nothing about typical or maximum performance.


About 91 percent to 92 percent of U.S. residents already have access to fixed network internet access at speeds of at least 100 Mbps, according to Broadband Now. And most buy speeds in that range. 


source: Broadband Now


It is useful to have minimum goals. It also is important to recognize when actual consumers buy products that are much more advanced than set minimums. 


Sunday, July 26, 2020

Covid-19 Has Not Been Good for Communications Service Providers, Despite Conventional Wisdom

There is an unfounded belief that widespread lockdowns and stay-at-home orders in many countries “must be good” for communications service providers. 


That is not the case. In some cases service providers have experienced subscriber losses. A revenue contraction has widely been expected, is expected and earnings reports are starting to show that has happened. 


source: Analysys Mason


Recent times of economic contraction or business failure (2008 Great Recession the former case; Dot-com bubble burst the latter case) have lead to contractions in spending on communications services, if brief (rebound in one to three years). 


Consumer spending arguably changes less than business spending in times of stress, in part because consumer and small business spending is more often based on “what we must have” than “what we’d like to have.”


So consumers operate closer to minimum viable spending (need to have), where enterprises tend to operate with more spending headroom (nice to have).


Saturday, July 25, 2020

Why UCaaS and Cloud Have Not Displaced Older Alternatives

“Build versus buy” or “own versus rent” remains a key framework for sourcing any capability a firm requires. That basic analysis of total cost of ownership arguably explains why smaller firms often rent rather than own, or why very-large firms often own rather than rent. 


Some 20 years ago, some of us would have argued that hosted voice (now we call it unified communications) sold “as a service” would displace most use of business phone systems. Adoption has been far slower than some of us expected back in 2000. 


To be sure, a shift in demand has happened, but not as rapidly or completely as once expected. Total cost of ownership explains some of the “resistance.” Since feature parity for premises systems and hosted services has generally come to exist (that was not generally the case 20 years ago), total cost of ownership comes into play. 


The other variable is that the value of related services once separate from basic business phone service (conferencing, unified communications) now are all considered part of a single unified communications market. 


source: Grand View Research


Keep in mind that hosted voice  services have been commercially available since the early years of the 21st century, though arguably not commercially viable for business use until perhaps 2005 or 2006. 

source: Grand View Rsearch


And that is where cost of ownership becomes a key argument for continuing to own business voice systems, rather than buying it “as a service.”


In a 100-user situation, the total cost of ownership over a five-year period favors a premises deployment over either private cloud or public cloud, according to TTx varies:

  • On-premise UC: $220-$240 per user per year

  • Public cloud UCaaS: $360-$480 per user per year

  • Private cloud UCaaS: $250-$350 per user per year


That includes upfront capital investment and recurring costs. A rough estimate of the cost per user for the first year for each system would be:

  • On-premise UC: $70,000-$90,0000 for hardware/infrastructure, software licenses, endpoints, and installation/deployment support.

  • Public cloud solution: In a 100 user environment, in most cases the upfront costs are $0.

  • Private cloud solution: Highly variable but declining


The recurring cost per user per year for each system might be:

On-premise UC: $120 to $145 per user, per year for ongoing maintenance, cost of upgrades and public network access. 


Public cloud UCaaS: Between $360 to $480 per user per year which includes the license cost per month and included deployment support. (This assumes an average of $30-$40 per user for licenses which includes renting the endpoints)


Private cloud UCaaS: $250 – $350 per user per year for financing and 3rd party maintenance


Of course, much hinges on volume. For smaller entities, hosted arguably provides lower TCO, especially when the customer wants a fully-featured platform. The tradeoffs and TCO are harder when mobility is a viable solution, when the customer does not require advanced features, and when the customer is willing to keep a premises system longer than five years. 


Any TCO analysis can be shifted when considering “soft costs” contract lock in, supplier instability, software upgrade and maintenance fees or situations where the number of supported users changes dynamically and often, for example. 


The same sort of analysis also applies to use of cloud computing (public or private) versus enterprise owned infrastructures. Generally speaking, volume tends to favor TCO of owned platforms. Episodic or dynamic variations in demand tend to favor cloud computing. Low volume favors cloud solutions, largely because of savings on capex. 


 And some argue the soft costs or value tip TCO one way or the other. License cost also can tip an analysis over a 10-year period as well. 


The point is that “as a service” solutions often make great sense. But so do “owned platform” choices. 


Needs to support dynamic and frequent shifts in demand can make a difference. But incorrect forecasting of demand also can lead to under-used resources, as when users overestimate the magnitude of cloud resources they require. 


And even when the “cost of compute or storage” TCO is understood, there might be other less-quantifiable business values deemed important, such as ability to interwork with business partner systems, apps and use cases. 


In other words, neither “cloud” nor “owned” computing or voice infrastructure “always” is the best choice.


Friday, July 24, 2020

Does Broadband Cause Growth, or Does Growth Cause Broadband?

Despite ongoing information technology investments, labor productivity growth declined sharply across OECD countries over the past decades, the OECD said in a 2019 report. The OECD argues that information technology has supported productivity, but that economy-wide productivity gains have been disappointing for other reasons.


source: OECD


That is worth keeping in mind. IT intensity--in and of itself--does not explain productivity or economic growth, any more than the mere existence of broadband internet access, no matter how high the quality or low the cost, alone drives economic growth, though this sometimes is argued. “If we only had better broadband…”


One can note correlations, to be sure. But correlation is not causation. Many would agree that broadband contributes to growth. But many things contribute. And the evidence about broadband access actually driving growth is unclear. 


It might well be the case that economically vibrant areas create the demand for quality broadband. 


What matters is how much value can be wrung from broadband and all the other complementary assets that must be in place to drive significant economic growth. 


“Digital technologies are characterised by strong complementarities (i) between the technologies themselves; (ii) with firms’ capabilities and assets, such as technical and managerial skills, organisational capital, innovation and financing capacity; and (iii) with policies that promote competition and an efficient reallocation of resources in the economy,” OECD says. 


In other words, economic growth results from many complementary sources. “Shortfalls in these complementary factors have slowed the diffusion of digital technologies and reduced the associated productivity benefits,” OECD said.  


It has been argued that gains are happening, but we cannot measure them. OECD does not believe that. 


“This is not just a measurement issue,” the report states. “Most researchers assess that mismeasurement is not the main reason of the observed productivity slowdown.” 


To the extent more-intensive application of IT has helped, it has not been enough to counteract the other negative forces. Perhaps that is typically the case. IT investment helps, but the drivers of results largely come from other sources.


"Tokens" are the New "FLOPS," "MIPS" or "Gbps"

Modern computing has some virtually-universal reference metrics. For Gemini 1.5 and other large language models, tokens are a basic measure...