Customers Often Do Not Like Dynamic Pricing

Many observers would argue that dynamic pricing--differential pricing of products based on criteria such as time of day, volume or some other criteria benefits both suppliers and customers. If peak loads, for example, can be shifted to off peak, there are capital investment advantages for suppliers.

That is why long distance calls once were priced dynamically: highest prices during workday working hours; lower prices on weekday evenings and nights and weekends. 

On the other hand, consumer behavior suggests buyers often do not choose to buy dynamically-priced products, but prefer fixed-price, flat-rate subscriptions. We are left to try and explain why that behavior persists. 

Disney’s latest quarterly report might suggest that customers prefer subscriptions to buying on a dynamic basis. Indeed, we might note the same behavior across a wide range of digital content or communications products. 

Dynamic pricing, where items are purchased a la carte, by the piece and on demand, creates spending uncertainty. Prices vary by criteria such as volume purchased, time of day purchased, possibly how an item is purchased or any discounting methods a seller wishes to use. 

Customers also have notions about the value of specific content items, whole channels or networks. Any customer who has compared the value and price of a Netflix subscription to the cost of buying content dynamically will conclude that the subscription seems to cost less, under any scenario of moderate use. 

Where a linear video subscription--depending on the number of channels purchased--might cost $50 to $80 a month, a streaming service--depending on which services the customer wants to buy--can start at about $7 a month each but might cost $15 a month or so.

Buying only a few pay-per-view or on-demand items a month can exceed the cost of a Disney Plus, Netflix, Prime, Hulu, HBO Max or Peacock subscription, for example. Granted, no subscription offer from any single provider ever offers “most” content, so most customers likely buy more than one streaming service. 

The point is that dynamic pricing offers the most value when a customer’s consumption is low, but offers less perceived value when consumption is moderate (possibly watching more than three movie or TV episodes a month that are purchased dynamically). 

That same trade off exists with other products as well. 

For buyers of cloud computing services, dynamic pricing is a better buy for customers with lower demand, variable workloads, small information technology support staffs or infrastructure and relatively lower adoption of new computing use cases. 

Cloud computing is often not a better buy for customers with high computing workcycle demand, fixed or predictable workloads, large IT infrastructure, staffs and skills or high rates of adopting new computing use cases. 

So there are good financial reasons for customers to see value in subscriptions that offer more content, at lower prices, compared to dynamic buys. 

Many also would argue that the reason customers prefer flat-rate pricing, even when they might pay less buying on a dynamic basis, is unambiguous cost. Any dynamic pricing mechanism--buy by the instance or item--introduces uncertainty of cost. 

Subscriptions offer a static price: the customer knows what the recurring cost is going to be. 

Dynamic electricity pricing is not as popular as one might think, for example, even if consumers could save money consuming more energy off peak. 

Virtually unlimited usage of domestic voice, text messaging or fixed or mobile internet access provide examples. Linear and over-the-top streaming video subscriptions provide other examples. 

Likewise, music streaming has replaced music purchases. Most content subscriptions--physical or digital also are offered on a flat-rate basis. Changes in buyer demand are at work, as well as supplier preferences, but perceptions of value are almost certainly at work. 

Customers seem to value broad catalog access without ownership to ownership of a fraction of the full catalog, which is what the shift to music streaming services, as opposed to content buying (song downloads) represents. 

In the connectivity business there are analogies. Though usage-based (dynamic pricing) is common for some products (international calls in some cases), many other products are sold on a flat rate basis (unlimited usage of internet access, domestic voice and texting. 

Other products are sold based as buckets of usage (subscriptions with different usage allowances). Customers buy subscriptions, but with different usage volumes included, typically with additional costs for usage above the allowance threshold.  

That created the profit driver of “overage charges.” Historically, overage charges were a significant contributor to supplier profits, and avoidance of overage charges became a driver of consumer behavior. 

Customers preferred to buy data plans with more usage than they ever expected, simply to avoid overage charges that introduced uncertainty of cost. 

During the period of video rentals, such overage charges were a major driver of profit for video rental outlets, and a source of customer unhappiness as well. 

For all those reasons, customers often prefer flat-rate pricing to dynamic pricing. They often prefer subscriptions to dynamic purchasing (a la carte, by the piece or instance) as well.

Can KT Become a Platform? Can Any Telco Do So?

Korea Telecom wants to become a digital platform company, not a telco. That ambition arguably is shared somewhat widely among tier-one connectivity service providers globally and has been a strategy recommended in some form by most bigger consulting companies. 

Simply, becoming a platform company changes the business model from direct supplier of products to a role as an ecosystem organizer or marketplace. That arguably is an aspirational goal more than anything else. 

What that aspiration means in practice is that KT as a digico “will shift our focus from the telecommunications sector, where growth is stalled due to government regulations, to artificial intelligence (AI), big data, and cloud computing businesses to become the nation's number-one platform operator in the B2B market," said KT CEO Koo Hyun-mo.

So there are qualifications. KT, if successful, would become a platform in the business market, not the consumer market. It would explicitly aim to become the center and organizer of an ecosystem for artificial intelligence, big data analytics and cloud computing. 

Purists and researchers will likely argue about whether all of that actually adds up to KT becoming a platform, in the sense that Amazon, eBay, Alibaba, ridesharing or lodging apps  might be considered platforms. 

A platform, definitionally, makes its money putting buyers and sellers and ecosystem participants together. In computing, a platform is any combination of hardware and software used as a foundation upon which applications, services, processes, or other technologies are built, hosted or run.

Operating systems are platforms, allowing software and applications to be run. Devices are platforms. Cloud computing might be said to be a platform, as systems are said to be platforms. 

Standards likely are thought of as platforms by some. 

In other cases components such as central processing units, physical or software interfaces (Ethernet, Wi-Fi, 5G, application programming interfaces) are referred to as platforms. Browsers might be termed platforms by some. Social media apps are seen as platforms as well. 

The platform business model requires creation of a marketplace or exchange that connects different participants: users with suppliers; sellers with buyers. A platform functions as a matchmaker, bringing buyers and sellers together, but classically not owning the products sold on the exchange. 

A platform orchestrates interactions and value. In fact, a platform’s value may derive in large part from the actions and features provided by a host of ecosystem participants. Facebook’s content is created by user members. Amazon’s customer reviews are a source of value for e-tailing buyers. 

Consumers and producers can swap roles on a platform. Users can ride with Uber today and drive for it tomorrow; travelers can stay with AirBNB one night and serve as hosts for other customers the next. Customers of pipe businesses--an airline, router or phone suppliers, grocery stores-- cannot do so. 

So KT can increase the percentage of revenue it earns from supplying digital, computing, application or non-connectivity services without becoming a platform. As a practical matter, that is what most telco executives have in mind when talking about becoming platforms. 

For KT, even limiting its ambitions to generating more digital and non-connectivity revenue does not make it a platform. That would still be an important, valuable and value-sustaining move. But KT has a very long ways to go, even in its stated objectives of becoming a B2B platform.

Total KT revenue is about 24 trillion won. All B2B revenues at the end of 2020 were about 2.78 trillion won (about 11.5 percent). Information technology services were about 1 trillion won, or about four percent of total revenues. AI and other digital services were about 0.5 trillion won, or about two percent of total revenues. 

It might be a long time between non-connectivity revenues in the B2B part of its business are as much as half of total revenues. And those revenues might not represent a platform transformation of the business model.

KT could win significantly without ever becoming a platform. And some might argue few telcos can ever actually hope to become platforms in the classic sense. Perhaps the more important goal is simply to reduce reliance on traditional connectivity revenues.

Long-Term Implications of Extensive Remote Work are Not Yet Clear

The long-term implications of social distancing for the connectivity business are not clear, though arguably better guesses might be made about travel-related industries. The short-term consequences of policies to combat Covid arguably also are far clearer: a significant percentage of small businesses will cease to exist, depressing sales of products to that segment of the market. 

The longer-term impact on connectivity provider revenues might hinge on the perceived advantages or disadvantages of remote work. If employers see no downside--or minimal downside--from remote work, such policies could lead to less connectivity spending at work sites.

That could be balanced by greater spending on remote work products and services of all types, with a shift of usage away from urban centers and towards suburban and exurban areas. 

That redistribution of usage patterns could then also reorient the pace and location of network capacity upgrades, both fixed and mobile, consumer and business. 

The issue is that the long-run productivity of work-from-home policies is yet to be determined, even if the hope is that productivity remains the same as when information workers are based “in the office.” 

Nor can we yet measure the impact of extensive remote work on social capital, "the networks of relationships among people who live and work in a particular society, enabling that society to function effectively".

Social capital matters for firms and societies because it enables the effective functioning of social groups through interpersonal relationships, a shared sense of identity, a shared understanding, shared norms, shared values, trust, cooperation, and reciprocity.  

The point is that we can burn through some social capital for short periods of time, likely without ill effect. Long term if another matter. Social capital has to be recreated, produced or replenished over time. To the extent that full-time remote work does so less well than regular face-to-face relationships, social capital stocks will fall, and so should organizational effectiveness. 

So far, many employers say publicly that productivity has not suffered. Many surveys indicate remote workers believe their productivity has not suffered. But the longer enforced remote work goes on, and the more surveys are taken, it appears productivity in many cases is suffering. 

It is not too early to note at least some differences between groups of workers. Younger workers are more likely to say they have had a hard time feeling motivated to do their work since the coronavirus outbreak started, according to a December 2020 survey by Pew Research. That suggests there is some productivity risk to full-time remote work by significant portions of nearly the entire information worker base. 

source: Pew Research 

Most adults who are teleworking all or most of the time say it has been at least somewhat easy for them to feel motivated to do their work since the pandemic started, Pew notes. But there is a distinct age gap.

About 42 percent of workers ages 18 to 49 say motivation has been difficult for them, compared with only 20 percent of workers 50 and older. The youngest workers are among the most likely to say a lack of motivation has been an impediment for them. About 53 percent of those ages 18 to 29 say it’s been difficult for them to feel motivated to do their work, Pew reports. 

More than 60 percent of remote workers say it has been very easy or somewhat easy for them to feel motivated to do their work. Still, more than 30 percent say this has been difficult. 

To be sure, motivation is not the same thing as productivity. And we might question whether we can accurately measure productivity of information workers. 

source: Pew Research

Also, productivity arguably is different for workers without children. Half of parents with children younger than 18 who are working at home all or most of the time say it’s been difficult for them to be able to get their work done without interruptions since the coronavirus outbreak started. Only 20 percent of workers who don’t have children under 18 say the same.

We do not--at present--fully understand the implications of permanent remote work for connectivity provider business models, much less long-run productivity.

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.