Wednesday, September 30, 2020

More Hybrid Work Patterns, but Good Reasons for Face-to-Face

The conventional wisdom about knowledge work is that it will be more hybrid in the future.  About 80 percent of 3,200 respondents to a Blind survey say they believe work will, in the future, involve some combination of “in the office” and “remote” work. 


That now is conventional wisdom. But note something else: about 45 percent of respondents said that not being able to get together in person with their team negatively affects their work, including 64 percent at Facebook, 63 percent of Google respondents and 56 percent of Uber respondents. 


For that reason, many of us expect that although more WFH will happen, more frequently, workers will continue to value face-to-face time. 


Tuesday, September 29, 2020

How Much Mobile Operator Success in 5G Private Networking?

How much revenue upside and value might mobile operators be able to create from 5G private networks? Some, but not as much as some might help, if history serves as a guide. The distinction between public wide area networks and private local area networks always has created leadership by different firms, and types of firms.


Simply put, local area networking has not been a core competency for public network service providers, nor does private networking tend to offer opportunities to achieve scale. Third parties are the low cost providers in the local networking business, making success a difficult proposition for higher-cost public connectivity providers unable to take advantage of economies of scale in private networks.


Private 5G networks, 5G fixed wireless, internet of things networks and large-venue 5G tend to share a characteristic in varying degrees: they shift the focus of connectivity from outdoors to indoors, wide area to local area, public network to private network, recurring connectivity revenue to equipment purchases.


So infrastructure sales will tend to shift a bit to private networks, a trend we now have seen embraced by a growing number of public network suppliers--including Samsung, Nokia and Ericsson--as well as emerging radio infrastructure suppliers. That means suppliers of public network infrastructure increasingly expect to be selling directly to enterprise end users, and not only to service providers.

source: Real Wireless 


What remains unclear is how the support infrastructure will develop. Some mobile operators likely will set up dedicated indoor networking units to design, build and support private 5G networks for enterprises. If history is any guide, most mobile operators will not have a sustainable business case serving anything but the largest enterprise venues or customers. 


Telcos have not managed to develop sustainable revenue models for indoor, private networking. Instead, interconnect firms (voice), system integrators, value-added distributors and other LAN specialists (data networking) have emerged to design, build and support premises networks. 


So third party specialists also will emerge, in all likelihood, particularly among the ranks of firms that historically support premises networking. 


Monday, September 28, 2020

Why U.S. Mobile Operators and Some Telcos are so Big on 5G Fixed Wireless

“Fiber is the network of the future, and always will be,” I once heard an engineering executive quip back in the 1980s. Though not literally true, the statement was a reasonable summation of the business context within which fiber to premises networks are deployed. Put simply, the business case is strongest when only one network can be built, while other platforms, even when built, have some performance or cost issues.


Consider this older analysis of fiber to home payback. Analysts at Delta Partners Group noted that in countries where governments have intervened with financial support in the FTTH market, including Japan, Lithuania, Malaysia, Portugal, Singapore, South Korea and the UAE, homes passed range from 47 percent in Sweden to 95 percent to 96 percent in South Korea and Lithuania. 


More important are take rates. There is relatively quick payback when consumer buy rates are in the 45 percent to 81 percent range, for example. In the U.S. market, where Verizon has deployed FTTH, it has only relatively recently gotten to a bit over 40-percent adoption, after 13 years of marketing, which is literally “off the charts” in this case. 


Delta Partners Group 


The problem for U.S. telcos is that rival cable operators have 70 percent of the installed base and have led in market share (net new additions every year) for two decades. Mobile operator interest in 5G fixed wireless is precisely that it offers a platform with different economics.

Sunday, September 27, 2020

Do Employees Understand AI Impact on Productivity Than Their Bosses Do?

Is it possible that employees of large firms have a better understanding of the impact of artificial intelligence on competitive advantage than their bosses do? Perhaps. 


It certainly seems to be the case that employees and C-level executives have different expectations about widespread AI adoption. 


Citrix sponsored a research effort conducted by Man Bites Dog and research company Coleman Parkes, polling 500 C-suite leaders and key decision makers within both large, established corporations and mid-market businesses with at least 250 employees. The study also involved surveying 1,000 employees. 


Fully 91 percent of professionals believe that by 2035, their organization will spend more on technology and AI than on human workers. Also, 90 percent of business leaders believe that in 2035, AI technology investment will be the biggest driver of growth for their organization.


By 2035, 83 percent of professionals believe that technology will have taken over low-value and repetitive tasks, enabling humans to focus on more meaningful work.


Some 89 percent of business leaders believe AI-powered digital workspaces will increase worker performance and productivity in their organization by 2035. Just 55 percent of employees share this view.


Fully 73 percent of business leaders believe that technology and AI will make workers at least twice as productive by 2035, while only 39 percent of employees share that belief.  


Only about 16 percent of business leaders say they are unclear about how their firms gain competitive advantages from AI, even when every major competitor uses AI. But 65 percent of employees say they are unclear on how their organization will gain a competitive advantage from using AI when it is being used by every business.


At least in part, employees seem to have a realistic understanding that AI will enable replacing humans with machines. Business leaders, though not immune from that process, tend to believe they will not be affected to the same extent. 


Perhaps shockingly, 57 percent of professionals believe that by 2035 there will be no traditional leadership team at all, as AI will make most business decisions.


Will Telecom AI Grow Over Next 5 Years?

Though connectivity providers have been slow to adopt artificial intelligence, that is expected by some to change dramatically over the next five to 10 years. 


source: Omdia 


Mobile operators seem to have moved earlier to adopt artificial intelligence than fixed network operators. At least, that is what STL Partners discovered in May 2019. Telcos that had incorporated at least some AI often used it to optimize existing network operations


Beyond that, some used AI for network planning and optimization, human resources, accounting and fraud-management. Some also use AI for cybersecurity and predictive analytics. 


AI also has been used for sales and marketing and customer experience (fault resolution, churn management) as well as supporting chatbots and virtual assistants. 


Singtel’s DataSpark provides access to GPS and mobile network data that other organizations can incorporate into their applications and services. 


AI is almost certain to be employed to help maintain profit margins as global revenue growth remains slow for the foreseeable future. 

source: GSMA Intelligence 


Is IT Productivity Slowing?

Industry disruption now has a familiar pattern. It starts with a cheaper, simpler version of a familiar product, which has some structural advantage. The product improves cumulatively, until the traditional industry can no longer compete. 


This illustration from Consensys shows value added in the financial services sector, compared to some more “physical” industry verticals. The broader point is simply that, by some accounts, either cloud computing or artificial intelligence are the forces leading productivity change.  


source: Consensys 


Technology optimists and pessimists tend to wage an unending war about the value of technology improvements. Some believe we are reaching an era of limits, such as the end of Moore’s Law, while others believe we will simply find other ways to keep pushing ahead. 


Optimists might counter that productivity now is shaped by software or cloud computing, not hardware.


This visualization by Deloitte shows the percentage of top 500 technology firms in Deloitte’s Fast 500 index. About 78 percent of the firms are in either the software or “digital” categories. About 10 percent of firms are in the hardware, devices or networking categories. 

source: Deloitte 


Nor is that an especially new trend. In consumer computing markets, new hardware has not propelled innovation advances as much as new cloud-based software and applications, for example. A study by Logic Monitor found that 74 percent of information technology executives in the United States, Canada, United Kingdom, Australia and New Zealand expect 95 percent of all software to be run in the cloud within five years. 


source: Logic Monitor 


The point is that pessimists might tend to see hardware limitations as negatively affecting rates of productivity growth. Those who see software, artificial intelligence or cloud as the drivers might tend to be optimists.


Study Shows Managers, Workers Believe Remote Work is Less Productive

A study of remote work at the Research Institute of Economy, Trade and Industry suggests workers and managers do not believe remote work is as productive as many claim. Keep in mind this is a survey of attitudes, not an attempt to directly measure some proxy for actual output. 


The productivity of remote work can improve over time, the researcher expects. Of course, much depends on the type of work. 


Some jobs simply cannot be conducted remotely, such as service jobs requiring physical contact with customers, often including doctors, nurses, hairdressers, and restaurant waiting staff.


Most work conducted by “information” workers in offices are easiest to do remotely, one might argue. The REETTI study suggests that the jobs of managers of knowledge workers might be far harder to do on a remote basis. 


Research Institute of Economy, Trade and Industry 


The study suggests four main classes of issues impairing higher productivity. Many people said the user friendliness of software and hardware for remote access was an issue. But Masayuki Morikawa, Research Institute of Economy, Trade and Industry, believes that is an issue which is resolved over time as workers become more experienced. 


Some tasks, conducted in the office, sometimes for security reasons, were hard to replicate in a remote context. 


Some people “emphasized the loss of the valuable, quick communication that is only possible through face-to-face interactions with their colleagues,” he said. 


Finally, a poor working environment at home, particularly the lack of a private room specifically designed for work, was reported as a serious constraint by many respondents. 


User experience and better remote location security and communications might be easier to fix. Home working environments will be much tougher to improve, as will the loss of face-to-face interactions. 


Friday, September 25, 2020

Will AI Upset Our Notions of How Much "Upskilling" Will be Needed by 2030?

It is hard to disagree with this McKinsey analysis of how skill requirements might change in the United States and Europe between 2016 and 2030. On the other hand, it also is possible to argue that we simply do not know yet how much artificial intelligence will reduce requirements for cognitive skills or technology skills.


In principle, AI should reduce the need for humans to acquire many cognitive or technology skills, as AI will automate so much of what we now believe will be required that perhaps there will be less “upskilling” need than the analysts expect. 


source: McKinsey 


"Five Nines" Availability Might Not be Possible Anymore

In the internet era, something profound has happened to traditional connectivity provider thinking and spending related to network service availability. Something equally important has happened to consumer expectations about service or app availability, as well. 


Service and app providers using the internet as the access platform generally cannot expect to reach 99.999 percent availability. Neither can mobile services of any type. Virtually all fixed network services except perhaps voice also now will fail to reach 99.999 percent availability. 


The reason is simply the math. Availability of any single device, in principle, could reach 99.999 percent availability, though that is not true of routers or servers. End user devices also never reach 99.999 percent availability. 


But system availability is the sum of every single device in the delivery chain. And even if every device and network element had 99.999 percent availability (“five nines”), reliability shrinks with the number of devices. 


It is demonstrably not possible for most end user internet experiences or applications, almost certainly. In the transport business, 99.999 percent availability is probably possible only on the portions of the network with the fewest total network elements, end to end. 



As a rule, I think we safely can assume that any internet-delivered will not ever reach 99.999 percent availability at the user level. It also is safe to assume that mobile voice, text messaging and internet access virtually never reach 99.999 percent. Possibly only legacy fixed network voice can hope to do so. 


It goes without saying that the Internet is a complex system, with lots of servers, transmission paths, networks, devices and software all working together to create a complete value chain.


And since the availability of any complex system is the combined performance of all cumulative potential element failures, it should not come as a surprise that a complete end-to-end user experience is not “five nines.”


Any end-to-end network, and the applications delivered over that network, have many single points of failure. Even if most network element has five nines levels of availability, and there are just eight total elements in series, with one device having 85 percent availability, and one device has 95 percent availability, total end-to-end system availability is just 59.87 percent. 


That is calculated as 85%*90%*99.9%*98%*85%*99%*99.99%*95%, or 59.87 percent. 


Redundancy is the way performance typically is enhanced at a data center, by a transmission network or application. But the total number of network elements for any single app also is going to be more than eight. 


Component

Availability

Web

85%

Application

90%

Database

99.9%

DNS

98%

Firewall

85%

Switch

99%

Data Center

99.99%

ISP

95%


So one way of thinking about reliability or availability is that modern application delivery systems cannot actually meet the old “five nines” standard, end to end. There are simply too many network elements involved in any end-to-end system. 


The business implication is that “five nines” increasingly is not possible. 


But consumer expectations also are involved. Consumers know mobile phones are not as reliable as fixed network phone service. They are willing to make the trade off. They know computers, operating systems and web apps are not “five nines” available. They know they will have to reboot on occasion.


The business implication is that consumers can live with “less than 99.999 percent availability if value is high enough. The corollary is that they also might not be willing to pay what it theoretically costs to move closer to five nines availability. 


The bottom line is that five nines cannot be provided, nor will consumers pay for it. Some level of availability less than 99.999 percent is acceptable and even expected. The question is how much availability is required to keep a user satisfied, as they might not be willing to pay much more--if anything more--to get that level of availability. 


Thursday, September 24, 2020

Much More AI Use in Telecom in 5 Years

If a recent forecast by Omdia is correct, telecommunications service providers will be spending quite heavily on artificial intelligence software over the next five years. Though AI will be a bigger capability for virtualized networks in the future, the current use cases often focus on customer service, especially call centers. 


source: Omdia 


AT&T, for example, uses AI-assisted systems to optimize technician schedules, minimizing commute time, for example. AT&T reportedly recorded a seven percent reduction in miles traveled per dispatch and a five percent increase in productivity.


The AI incident management process also uses AI to detect network issues in real-time, even before the customers are aware there is a potential problem. It is said that AT&T has the ability to manage about 15 million alarms per day.


Users Will Migrate to 5G, Maybe Because of New Value, But More Likely Because of Supplier Push

End user demand for various connectivity services changes over time, but typically when some new need arises. But sometimes supplier push drives the change.


That might be the case for 5G, early on. Since 5G requires new devices, 5G device availability, especially for the most-popular brands, is a key requirement for higher 5G adoption. It is less clear that any immediate new use cases will be obvious.


Changes in demand have many drivers other than new needs, of course. At other times, revolutionary changes in supplier policy can shift demand quite radically. 


There was a time when a deliberate pricing strategy by AT&T mobility drove a huge amount of product substitution, literally leading to huge use of mobile calling as a direct substitute for long distance, and also leading to mobile substitution for local telephone service as well. 


 source: Telecom Policy Institute


Few now recall it, but AT&T Wireless once drove rapid mobile adoption by consumers by revolutionizing the way consumers paid for--and how much they paid for--long distance calling.


Back in 1998, AT&T unveiled a major new pricing plan for mobile users that priced all domestic calls for 10 cents a minute. That Digital One Rate plan effectively erased the distinction between local and long distance calling and provided a major incentive for consumers to buy mobile service.


Even many astute industry watchers did not appreciate the revolutionary nature of the plan. Technology pundit Walt Mossberg once called Digital One Rate “marketing hype.”


“It promises to make your cell phone as simple and affordable to use as a landline phone, so that you'll use it even for casual calls without a second thought,” said Mossberg. “The actual service behind the marketing isn't good enough to really allow that. I've been frustrated with it again and again.”


Digital One Rate was anything but hype. It really did revolutionize the way consumers and businesses made calls. It really did begin the mass adoption of mobile phones and the demise of landline service.


Beyond that, Digital One Rate changed the key profit drivers in telecom, from long distance revenue to mobile service. Within a decade, the industry profit driver changed from long distance to mobility. The shift from voice to data would follow.


In the ensuing years after Digital One Rate was introduced, long distance revenue plummeted, as did use of landline phone services. Digital One Rate was the driver, as the whole industry shifted pricing and packaging.


It is unclear how much 5G can shift end user demand. It is clear that at least some mobile service providers in the U.S. market are going to try and drive a substitution of mobile broadband for fixed network access. It is not clear whether end user demand shifts will mostly be driven by end users or suppliers. 


Some of us can remember the new needs that caused us to upgrade to specific devices, and then to web-centric devices. I actually do not recall which 2G device I was using when the “need” for a Blackberry happened. Odd enough though it will seem now, “mobile email” was a huge draw, providing enough value to make it an easy choice. 


I also remember when the Blackberry became a barrier. There was a time when smartphones did not routinely offer access to turn-by-turn directions, and for no subscription fee. That alone was the killer app that made the Blackberry suddenly less capable than I needed, and made the value of a 4G device much more attractive. It meant I did not need a discrete GPS device, with a required subscription. 


I had used 3G dongles for wireless internet access when on business travel, as painful as it was, experience wise. The shift to a 4G dongle was a “no brainer” decision because the user experience was so much better. 


The visual web made routine upgrades of my fixed network, to get higher speeds, a logical decision. It has been years since download speed actually has been an issue, though, as speeds and pricing have been more than adequate for all my use cases. 


Work from home has not been a particular issue, as I have worked remotely, and out of my home, for most of the last 25 years. But what is new is the amount of time I spend on videoconferencing services. And since my connection is asymmetrical, with what now insufficient bandwidth for consistent user experience. 


The new need is “more upstream bandwidth,” for the first time. At least so far, my 4G experience is not a pain point, as I tend not to do work videoconferencing on the mobile device. 


In all those instances, a shift to different or new services, though anecdotal, was driven by a change in demand for features or services. 5G will be the same sort of thing for most people, and might initially be driven simply by the need for a new device that just happens to use the 5G network. 


Wednesday, September 23, 2020

Are Happy Workers More Productive? Maybe Not

Are happy workers productive workers? That always seems to be the assumption, just it always seems assumed that “better broadband produces higher economic growth.” But it that a reasonable assumption? Yes, most studies suggest. But some question the theory that happiness leads to productivity.  


Industrial psychologist Fredrick Herzberg is among those who might argue the link is not as causal as most of us believe.


One issue is what we actually are measuring, though. Is it morale, engagement, employee satisfaction scores, fulfillment, or something else that is the proxy for “happiness.” Sometimes such measurements look at job satisfaction


Other times “well being” is what researchers try to measure. By definition, well being involves not only the job, but also everything else in a person’s life. In other words, it might be possible that people are happy for other reasons, or engaged for other reasons, also are able to produce more effectively. 


At least in principle, organizations might have a mix of happy, yet low-performing employees, as well as unhappy low-performing employees. Organizations might also have unhappy high performers or happy high performers. 


source: Professor Charles D. Kerns 


Though studies suggest all are correlated with higher productivity, the empirical results vary based on which proxy is used.  


But some argue--perhaps counterintuitively--that happiness doesn’t necessarily lead to increased productivity. 


“A stream of research shows some contradictory results about the relationship between happiness — which is often defined as “job satisfaction” — and productivity,” according to researchers André Spicer, professor of Organizational Behavior at Cass Business School in London and Carl Cederström professor of Organization Theory at Stockholm University.


One study on British supermarkets even suggests there might be a negative correlation between job satisfaction and corporate productivity,” they note. The more miserable the employees were, the better the profits, they note.


But it also is fair to point out that the direct relationship between performances and positive attitudes has not been proved, at least not yet. 


The belief that happy workers “must be” more productive workers is widespread. Most of us instinctively wish to believe it. The correlation might generally exist (though the causal relationship remains arguably unproved). 


Correlations might be enough, though, in the sense that people act as if the statement were true, regardless of fact.  


Most of us act as though “broadband causes economic growth.” Correlations obviously exist. But nobody yet has been able to prove causation, as there always are other explanations. 


Places with high economic growth tend to produce wealthier and better-paid employees, who are in position to pay for better broadband. Places with high employment of knowledge or information workers likewise might also be places where demand for faster broadband is highest, both for reasons of “we can afford it” as well as “we prefer and want it.” Higher income is always correlated with higher demand for quality broadband. 


Such places also tend to be populated by people with advanced college degrees, and that also correlates with demand for more-costly or faster broadband. Places with more younger people have higher broadband demand than places populated with older people. 


Demand for better or more-costly broadband also correlates with workforce status. Retired people tend not to have as much demand for the “fastest” services, which also are the most costly. People still at work have higher levels of demand. 


We might generally prefer that employees be happy, for all sorts of reasons. Whether they also are more productive for that fact is what is harder to prove, especially since there is no unquestioned way to measure “happiness” directly. What we actually can measure are proxies for “happiness.” 


And we might even have that wrong. The point is that we actually cannot “prove” that happier workers are more productive. In extreme cases, the “happiest” employees might be those who are paid generously, yet produce questionable results, and are not expected to do so. 


Few of us would question the likely negative impact of unhappy workers at any workplace. But it is also possible to argue that removing the sources of unhappiness has value. 


That arguably is a different process from fostering higher productivity. Low pay might make you unhappy. But high pay might not produce long-term happiness or productivity. Unsafe work conditions might make you leave a job. That does not mean making the workplace safe necessarily increases one’s productivity. 


Think of “unhappiness” and “happiness” as being on two separate scales, not one. The task is remove sources of unhappiness and low productivity on one scale, and hopefully increase happiness or productivity on the other scale. 


Industrial psychologist Frederick Herzberg is known among organization theorists for his motivation-hygiene theory of satisfaction and dissatisfaction. Put simply, the opposite of satisfaction is no satisfaction.


The opposite of dissatisfaction is no dissatisfaction. Satisfaction and dissatisfaction are in separate dimensions.


"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...