How Much Did U.K. Benefit from "Superfast" Program?

A report by the U.K. Department for Digital, Culture, Media & Sport claims the program to increase U.K. internet access speeds to 30 Mbps “sparked a surge in home values of up to £3,500” between 2012 and 2019. 

The study also claims a causal and positive effect in any number of economic areas, including employment, sales, firm relocations, wages, home prices, the number of jobs and worker productivity. 

The issue is whether a causal relationship exists, or is simply a correlation, for any of those claimed changes. 

“The program led to an increase in house prices of 0.6 to 1.2 percent” over that period. Of course, the issue is whether house prices were growing during that period for other reasons, such as simple supply and demand. 

According to Statista, U.K. home prices increased dramatically--about 35 percent--between 2010 and 2020. A change of between half a percent to one percent might be considered statistical noise, in that regard. 

source: Office of National Statistics 

Those are impressive results indeed when it also is deemed  “premature to draw any conclusions in relation to the impact of the program on take-up” of faster broadband service. 

One might wonder why there is such confidence about the wider economic impact of the subsidy program if there still is uncertainty about the program’s impact on consumer purchasing of higher-speed internet access.

Also, the program also seems to have reduced speed upgrades in some cases.

“The evidence also suggested that nine percent of premises upgraded would have otherwise received superfast coverage one year earlier in the absence of the program,” the report notes. 

The report also notes inconclusive changes in the number of customers buying the higher-speed services. The program “led to a reduction in the number of premises with superfast connections (by 1.1 to 2.4 premises per postcode) by September 2019.”

In other words, the program delayed “the availability of superfast for some premises that would have otherwise benefitted from commercial deployments.”

The report also notes it is unclear whether the long-term advantages will persist. “It is assumed that the short-term effect of the program persists for the first two years following the upgrade, and thereafter decays at a rate of 13 percent per annum.”

Also, “there was no conclusive evidence that the program had a positive or negative effect on the average download speeds of connections by September 2019.”

In some cases the subsidy program seemed to reduce average download speeds by 2.1 Mbps, while in other cases the program seemed to increase download speeds by 2.2 Mbps.

The program “increased the average upload speeds of connections by 0.9 Mbps to 3.9 Mbps”  and maximum download speeds by 6.2 Mbps to 16.9 Mbps, the report says.

The report says the broadband program is “estimated to have increased employment in the areas benefiting from the program by 0.6 percent, leading to the creation of 17,600 local jobs by the end of 2018.”

Firm sales grew by almost 1.0 percent by 2018, increasing the annual turnover of local businesses by £1.9 billion a year, the report says. 

“The evidence indicated that a share of these local economic impacts were driven by the relocation of firms to the program area,” as faster broadband “increased the number of businesses located in the areas” by around 0.5 percent .

In other words, “the program may have encouraged the relocation of economic activity to rural areas.”

“There were also signals of efficiency gains,” as “turnover per worker of firms in the areas benefiting rose by 0.4 percent in response to subsidized coverage.” Keep in mind that the report argues firms that did not relocate saw annual “turnover per worker rose by just under £12 for each premise upgraded across spatially stable units.”

U.K. productivity rose an average of 0.45 percent between 2009 and 2018, the Office of National Statistics says. Again, it is hard to say what specific impact the broadband subsidy program might have had.  

Employees working for firms located in the areas benefiting from subsidized coverage saw their hourly earnings increase by 0.7 percent in response to the upgrade, the report claims. 

More jobs created also reduced unemployment, the report says. The number of unemployed claims fell by 32 for every 10,000 premises upgraded by 2018. 

“The program led to an increase in house prices (of between £1,700 and £3,500),” as well, the report says. The findings are based on a study conducted by Ipsos Mori. 

The point is that correlation is not causation. If total U.K. employment, sales, firm relocations, wages, home prices, the number of jobs and worker productivity grew during the study period, we do not know what impact the subsidy program might actually have had.

The report itself suggests rather modest changes in speeds and some delays in coverage and deployment caused by the program, even if coverage overall did increase. The claimed increases in productivity likewise are estimated to be modest, on the order of £12 per worker per year. 

The desire to claim a program worked is understandable. The evidence seems to show correlation, but perhaps not out of line with larger trends in the U.K. economy. Causation is likely another matter.

How Much Business Revenue Will Telcos Lose Because of Covid?

How much revenue will connectivity providers lose from small business bankruptcies? There are at least two different effects. Businesses that have gone bankrupt will no longer be able to buy connectivity services. 

Business mobile revenue might drop 12 percent, according to Analysys Mason estimates. Business fixed network services revenue might drop 10 percent. But Analysys Mason also believes mobile revenue will climb back up in 2021, albeit still declining at least one percent  

But there also is the matter of bad debt. Verizon, for example, has set aside a $228 million reserve for expected bad debt. 

“Despite the upside from governments and large corporates seeking higher bandwidth for VPN and conferencing facilities, the B2B segment is more adversely impacted owing to potential bad debts, which have primarily arisen from inability of SOHOs and SMEs to pay their bills,” Arthur D. Little says. “Additionally, increased unemployment, business closures and the overall decline in economic activity implies reduced spend by businesses on telecom services.”

It is fairly easy to quantify the revenue impact on businesses. Taxable sales in California during the first two quarters of 2020 dropped $152 billion in the second quarter alone, a 17.5 percent decline from the previous quarter, according to a new study published by the National Bureau of Economic Research. 

But the losses were not evenly distributed. Accommodation sector revenue dropped 91 percent), followed by bars at 86 percent. Entertainment venues saw sales drop 83 percent, while full-service restaurants saw a decline of 61 percent. Small shops selling gifts and souvenirs, clothing, or books also were hard hit, according to economists Robert W. Fairlie and Frank M. Fossen. 

source: NBER

Pharmacies, liquor stores, supermarkets, agriculture, and building material and garden equipment stores gained, however. 

“The number of active business owners in the United States plummeted from 15.0 million in February 2020 to 11.7 million in April 2020,” they say. 

P Morgan Chase data shows that small business revenues dropped 30 percent to 50 percent at the end of March and early April and 40 percent into May, they say. 

About 60 percent of business owners reported lower sales in April and 50 percent of owners reported lower sales in May.

All of that is likely to depress smaller business communications spending, as some customers will no longer be in business, while others might be frugal with additional spending. 

source: Arthur D. Little

Most Digital Transformation Projects Will Fail

Most digital transformation projects are going to fail, based on historical rates of success of all manner of information technology initiatives. 

“Most of the leaders we surveyed (companies representing 17 countries and 13 industries) reported poor returns on their digital investments,” say Accenture executives Mike Sutcliff,

 Raghav Narsalay and Aarohi Sen. 

“A whopping 73 percent of enterprises failed to provide any business value whatsoever from their digital transformation efforts, according to an Everest Group study last year,” says Peter Bendor-Samuel is CEO of Everest Group, a management consulting and research firm. “Furthermore, 78 percent failed to meet their business objectives.”

The rationale for digital transformation is that it is supposed to create favorable business outcomes, including higher revenue, higher profits, higher growth, lower costs, higher new customer acquisition rates and lower churn rates. 

In fact, it might be more realistic to argue that the primary purpose of digital transformation efforts is to increase the volume of revenues earned by any enterprise selling digital rather than physical products; selling products without using physical channels; or altering physical products in some way to emphasize other digitally-enabled value. 

Non-quantifiable goals might include higher engagement with potential and existing customers; better customer service; higher customer satisfaction or doing all of that at lower cost. 

But digital transformation normally involves the application of technology to business processes. And history suggests at least 70 percent of projects applying technology in such a way fail. We might therefore expect 70 percent or so of all digital transformation efforts to fail, in the sense of not reaching the intended goals. 

The typical thinking is that business processes and culture must change if digital transformation efforts are to succeed. So, in an important way, digital transformation is not about technology.  

One might argue that digital transformation is something new. It is not. Firms and consumers have been increasing their use of digital machines, applications and systems since the early 1980s. So we have not been at this for 40 years. 

And the historical record on the impact of those investments is perhaps modest. Over recent decades, the ICT productivity contribution to total productivity growth has been perhaps minimal. 

From 1973 to 1990, productivity growth was less than one percent, economy-wide. In the 1990s the total economy productivity was a bit greater than one percent. In the decade of the 2000 to 2010 period,  we got higher productivity growth in the area of 1.5 percent.

Even if one attributes all the productivity boosts solely to information and communications technology, we might characterize the returns as important, but not stellar. The long run average of total productivity growth between 1870 and 2010 is 1.6 percent to 1.8 percent. 

Between 1995 and 2000, the productivity impact of applying information and communications technology had some impact on gross domestic product growth. According to OECD figures, ICT investments accounted for 0.3- 0.9 percentage points of growth in GDP per capita between 1995 and 2000 with the United States, Australia and Finland being close to the upper and Japan, Germany, France and Italy to the lower level, according to Pál Gaspar, ICEG European Center, Budapest University of Economics. 

source: Congressional Budget Office 

Some might attribute regional differences in productivity impact simply as the result of the volume of investment: more investment equals more productivity increase. Others might argue the results are more complicated, and are the result of changes in organizational processes to maximize the value of technology, and not simply the application of technology to existing processes. 

Others might point to differences in regulatory regimes which can create obstacles to, or support technology adoption. The level of taxation, depreciation schedules and other fiscal and accounting policies can support or depress appetite for investment. 

Market scale and management cultures also can retard or support the commercially-positive use of new technology. Yet others might point to the role of government policies supporting the adoption of new technology. 

The bottom line is that digital transformation projects are information technology projects, and most such projects fail to meet their objectives.

Small Business Connectivity Revenues Will Take a Hit from Covid-Caused Small Business Bankruptcies

It likely will not surprise you that taxable sales in California during the first two quarters of 2020 dropped $152 billion in the second quarter alone, a 17.5 percent decline from the previous quarter, according to a new study published by the National Bureau of Economic Research. 

But the losses were not evenly distributed. Accommodation sector revenue dropped 91 percent), followed by bars at 86 percent. Entertainment venues saw sales drop 83 percent, while full-service restaurants saw a decline of 61 percent. Small shops selling gifts and souvenirs, clothing, or books also were hard hit, according to economists Robert W. Fairlie and Frank M. Fossen. 

source: NBER

Pharmacies, liquor stores, supermarkets, agriculture, and building material and garden equipment stores gained, however. 

“The number of active business owners in the United States plummeted from 15.0 million in February 2020 to 11.7 million in April 2020,” they say. 

P Morgan Chase data shows that small business revenues dropped 30 percent to 50 percent at the end of March and early April and 40 percent into May, they say. 

About 60 percent of business owners reported lower sales in April and 50 percent of owners reported lower sales in May.

All of that is likely to depress smaller business communications spending, as some customers will no longer be in business, while others might be frugal with additional spending. 

source: Arthur D. Little

“Despite the upside from governments and large corporates seeking higher bandwidth for VPN and conferencing facilities, the B2B segment is more adversely impacted owing to potential bad debts, which have primarily arisen from inability of SOHOs and SMEs to pay their bills,” Arthur D. Little says. “Additionally, increased unemployment, business closures and the overall decline in economic activity implies reduced spend by businesses on telecom services.”

Verizon has set aside a $228 million reserve for expected bad debt, for example.

Can "Digital" Telco Sales be Measured?

Digital transformation is a term that can mean next to nothing. Consider a recent survey of connectivity service providers suggesting that retail stores and call centers account for 71 percent of sales, classified as physical channels. 

source: Upstream Systems 

By way of contrast, sales driven by email, websites, text messaging, data rewards programs or push notifications of some sort are considered “digital” channels. 

It is fair to say that the classification of sales “by channel” is imprecise and open to many judgment calls. Sales might be fulfilled physically, at a store or by call center order, when the sales process actually began with a digital channel. Conversely, sales might be fulfilled digitally when the sales process began physically. 

Word of mouth and advertising also play a part in consumer sales. How a sale is closed is one thing. How a sales journey began and was sustained might be quite another matter. 

The problem is that sales attribution cannot account for such nuances. Where and how revenue was booked is the only way most consumer sales are tabulated. So actual sales attribution is distorted. 

Some might argue that everything contributing to a sales journey is “marketing,” while “sales” refers strictly to a closed transaction with revenue attached. The larger point is that it is hard to differentiate between digital and physical channels for sales. Sales fulfillment might be the only thing we actually are measuring.

Is Covid a White, Grey or Black Swan? It Matters

Is the Covid-19 a white swan, a grey swan or a black swan? The answer portends the amount of disruption we could see, post-Covid. 

A “white swan” event that is one that could have rationally been expected to happen at some time, and has major effects. If Covid-19 was a white swan, the world will not be disrupted as much as many expect. Essentially, change will happen without expected and “normal” statistical ranges. In other words, Covid will have about as much impact as a normal recession. 

White swans are said to have relatively few negative implications, impacting the life of one or a group of people rather than the entire globe. 

Grey swans--neither a completely unexpected black swan nor a predictable white swan--can be devastating for many, and can have radically unsettling implications. To be sure, black swan or grey swan events can be positive, not just negative, though the most common outcome is a negative impact. 

The main difference between a grey swan and a black swan event is that one is known about beforehand, while the other takes us completely by surprise. But the bottom line is that a grey swan event can still be disruptive and devastating. 

If Covid-19 was a grey swan, we might see unexpectedly large outcomes, in terms of change. 

A true black swan event is typically expected to have disruptive implications. Black swans are outliers, events that are outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. 

Climate change, population growth or rising debt levels could be grey swans. Long-term water shortages could be a grey swan. 

Black swans typically have “extreme” or “massive” impact, exposing fragility in ideas or practices that had underpinned “normalcy.” Many would consider the personal computer and the internet as examples of black swans. 

Keep in mind that highly-disruptive events can still be white swans. Some consider the internet bubble burst of 2001 and the Great Recession of 2008 to be white swans. If that is the test, a grey swan or black swan would have unimaginable consequences. 

Others might consider the 2001 internet bubble burst a white swan, but the Great Recession of 2008 a black swan. World War I, World War II, the fall of the Soviet Union, the rise of Islamic fundamentalists, 9/11 and the internet might be called by some black swan events.

Others might consider the Great Depression and World War II as a single black swan event. Some consider the sinking of the Titanic a black swan event. Others might consider larger events, such as the Spanish defeat of the Aztecs, to be black swan events. 

The point of black or grey swan events is not “how to prevent them.” By definition, they cannot be predicted or prevented. But organizations can try and create robustness for their occurrence. 

Small businesses, sadly, almost by definition cannot create much robustness. 

Many businesses--large and small--will survive or die based on when economic activity can be resumed on a “normal” basis. A survey of U.S. respondents taken mostly in January 2021 suggests most believe it will be six months until they feel comfortable attending large public events. 

A plurality say it will be six months until they are comfortable taking a vacation. Other life sustaining activities--such as going to work--are largely believed safe now. A majority of respondents feel safe shopping in retail stores now. Less than half are comfortable eating at a restaurant. 

If these attitudes do not change, many restaurants and travel-related businesses will not be in business by the end of 2021. Failures in many OECD countries will eliminate more than three percent of jobs. 

source: Civic Science 

The number of active business owners in the United States plummeted by 3.3 million or 22 percent in just two months from February to April 2020. The drop in active business owners was the largest on record, according to the National Institutes of Health. 

By December 2020, 42 percent of small businesses surveyed on Alignable said they were in danger of going out of business. By the fall of 2020, at least 49 percent of businesses reported they were unprofitable. Some 18 percent were operating at about breakeven levels. 

It almost does not matter whether economic shutdowns and travel bans are classified as white, grey or black swans. For small businesses, they have the impact of a black swan, even if other segments of the economy will not be so affected. 

It remains unclear whether Covid will prove a black swan for cruise lines, retailing, the travel industry, airlines, entertainment or real estate. As with small businesses, Covid might well turn out to have black swan impact on some industries. 

Causation is Clear for Short-Term Rentals, Less Clear for Broadband

“Who benefits and who loses?” is a reasonable question for analyses of public policy and economic studies. As with all questions related to public policy and economics, though, correlation is easier to demonstrate than causation, simply because the number of variables is so great. 

In the connectivity business, the issue is most common in analyses of broadband impact on economic growth, household income or job growth. We assume broadband “causes” economic growth, but correlation is not causation.  

We assume quality broadband is associated with job growth, but cannot prove causation. We assume better mobile broadband also “causes” economic growth, so we might also believe 5G will similarly cause growth. We might be wrong. 

It also is plausible that areas with strong economic growth, above-average household income and wages, higher educational levels and wealth create demand for better broadband. In other words, demand for broadband is a result of strong economic growth, rather than its cause. 

Other cases arguably have stronger causation relationships. Consider the argument that use of short-term rental apps causes a reduced supply of housing and higher housing costs. It seems plausible for the simple reason that housing vacancies in any market tend to be fixed, and rental property managers can make choices about how to market their rentals: short term or long term. 

The issue is how much difference a robust short-term rental has. It also seems plausible that the biggest impact should be in “touristy” areas where there is high demand for short-term housing. Areas with modest tourist demand should also have modest demand for short-term housing. 

It also seems plausible that the greatest effect is in “touristy” areas that also are affluent. 

Airbnb leads to a reduced supply of housing as properties shift from serving local residents to serving Airbnb travelers, which hurts local residents by raising housing costs, according to Josh Bivens, Economic Policy Institute director of research. 

That assessment seems mirrored by some other studies. Short-term rentals using apps such as Airbnb contribute to housing shortages and rent increases, according to Felix Mindl and Dr. Oliver Arentz, researchers at University of Cologne in Germany. 

They attributed 14.2 percent of overall rent increases to short-term rentals or 320 euros ($385) per year for new tenants.

“While a large proportion of hosts can be considered home sharers, we find an increasing proportion of providers who have developed a professional business model from short-term rentals,” Mindl said in a statement. “Professional short-term rentals are available to tourists throughout the year, and thus compete directly with long-term tenants, for whom the rooms are then no longer available.”

Researchers also have found that in local neighborhoods with a lower share of owner-occupancy, Airbnb had a higher impact on rising housing prices and rents. In areas with a higher share of owner-occupancy, Airbnb had somewhat less of an impact on property prices and rents.

The study also found that the total supply of housing was not affected by the entry of an Airbnb property in a given neighborhood, and that Airbnb listings tend to increase the supply of short-term rental units, while contributing to a decrease of the supply of long-term rental units.

Aside from the presumed effect on housing, short-term rental apps also shift revenue between lodging suppliers. As with sports stadiums, which arguably mostly shift spending from one form of entertainment to another, short-term rental apps shift revenue from hotels to individual property owners.

“The most obvious benefit stemming from the creation and expansion of Airbnb accrues to property owners who have units to rent,” EPI noted.

There are other issues, though. The housing market is affected by forces other than Airbnb, such as gentrification and economic trends. A one-percent increase in Airbnb listings is causally associated with a 0.018 percent increase in rental rates and a 0.026% increase in house prices, other researchers argue. 

“In aggregate, the growth in home-sharing through Airbnb contributes to about one fifth of the average annual increase in U.S. rents and about one-seventh of the average annual increase in U.S. housing prices,” say researchers Kyle Barron, Edward Kung and Davide Proserpio. 

In contrast, annual zip code demographic changes and general city trends contribute about three fourths of the total rent growth and about three fourths of the total housing price growth.

“These results translate to an annual increase of $9 in monthly rent and $1,800 in house prices for the median zipcode in our data,” they say.

The biggest impact comes if a long-term rental unit is converted to a short-term rental unit on a full-time basis, as that subtracts one living unit from the long-term rental stock. On the other hand, an owner-occupied home that rents a room in that house does not do so.