ISP Marginal Cost Does Not Drive Consumer Prices

As the U.S. Federal Communications Commission opens an inquiry into ISP data caps, some are going to argue that such data caps are unnecessary or a form of consumer price gouging, as the marginal cost of supplying the next unit of consumption is rather low. 

Though perhaps compelling, the marginal cost of supplying the next unit of consumption is not the best way of evaluating the reasonableness of such policies.  

If U.S. ISPs were able to meet customer data demand during the COVID-19 pandemic without apparent quality issues, it suggests several things about their capacity planning and network infrastructure, and much less about the reasonableness of marginal cost pricing.

In fact, the ability to survive the unexpected Covid data demand was the result of deliberate overprovisioning by ISPs; some amount of scalability (the ability to increase supply rapidly); use of architectural tools such as content delivery networks and traffic management and prior investments in capacity as well. 

Looking at U.S. internet service providers and their investment in fixed network access and transport capacity between 2000 and 2020 (when Covid hit), one sees an increasing amount of investment, with magnitudes growing steadily since 2004, and doubling be tween 2000 and 2016.

Year	Investment (Billion $)
2000	21.5
2001	24.8
2002	20.6
2003	19.4
2004	21.7
2005	23.1
2006	24.5
2007	26.2
2008	27.8
2009	25.3
2010	28.6
2011	30.9
2012	33.2
2013	35.5
2014	37.8
2015	40.1
2016	42.4
2017	44.7
2018	47
2019	49.3
2020	51.6

At the retail level, that has translated into typical speed increases from 500 kbps in 2000 up to 1,000 Mbps in 2020, when the Covid pandemic hit. Transport capacity obviously increased as well to support retail end user requirements. Compared to 2000, retail end user capacity grew by four orders of magnitude by 2020. 

Year	Capacity (Mbps)
2000	0.5
2002	1.5
2004	3
2006	6
2008	10
2010	15
2012	25
2014	50
2016	100
2018	250
2020	1000

But that arguably misses the larger point: internet access service costs are not contingent on marginal costs, but include sunk and fixed costs, which are, by definition, independent of marginal costs. 

Retail pricing based strictly on marginal cost can be dangerous for firms, especially in industries with high fixed or sunk costs, such as telecommunications service providers, utilities or manufacturing firms.

The reason is that marginal cost pricing is not designed to recover fixed and sunk costs that are necessary to create and deliver the service. 

Sunk costs refer to irreversible expenditures already made, such as infrastructure investments. Fixed costs are recurring expenses that don't change with output volume (maintenance, administration, and system upgrades).

Marginal cost pricing only covers the cost of producing one additional unit of service (delivering one more megabyte of data or manufacturing one more product), but it does not account for fixed or sunk costs. 

Over time, if a firm prices its products or services at or near marginal cost, it won’t generate enough revenue to cover its infrastructure investments, leading to financial losses and unsustainable operations.

Marginal cost pricing, especially in industries with high infrastructure investment, often results in razor-thin margins. Firms need to generate profits beyond just covering marginal costs to reinvest in growth, innovation, and future infrastructure improvements. 

In other words, ISPs cannot price at marginal cost, as they will go out of business, as such pricing leaves no funds for innovation, maintenance, network upgrades and geographic expansion to underserved or unserved areas, for example. 

Marginal cost pricing can spark price wars and lead customers to devalue the product or service, on the assumption that such a low-cost product must be a commodity rather than a high-value offering. Again, marginal cost pricing only covers the incremental cost of producing the next unit, not the full cost of the platform supplying the product. 

Nobody Can Say For Sure Whether Productivity is Up, Down or Unchanged

Some worry that productivity has fallen recently, since the fourth quarter of 2021, according to U.S. Federal Reserve data. But studies have produced contradictory findings, showing

 higher, lower or unchanged worker productivity since about 2020. 

Arguably much of the data most susceptible to change were generated by knowledge or office workers forced to work from home because of the Covid pandemic. 

With the caveat that some of us are skeptical about the ability to measure knowledge worker or office worker productivity, studies can be cited showing higher; lower and “no change” in productivity because of remote work, for example. 

And intangible products accounted for as much as 80 percent of total U.S. output in 2022. The goods-producing sector includes agriculture, forestry, fishing, and hunting; mining; manufacturing; and utilities. 

The service-providing sector includes trade, transportation, and utilities; professional and business services; education and health services; leisure and hospitality; and other services.

Still, productivity changes in both goods and services has been in a 1.5-percent to two-percent annual rate of change since shout 1980, according to the Bureau of Labor Statistics. That estimate is based on hours worked, compensation levels and therefore unit costs. 

Just anecdotally, one might conclude that knowledge worker productivity has neither increased or decreased since the enforced “work from home” policies caused by the Covid pandemic. The line of reasoning is that so many people report being able to get their work done in less time while working at home. 

But studies exist that argue productivity is higher, lower or unchanged because of remote work. 

Study	Date	Publisher	Findings
The Impact of Remote Work on Productivity	2020	Stanford University	Increased productivity by 13%
Remote Work: A Review of the Evidence	2021	McKinsey & Company	No significant change in productivity
The Future of Work: How Remote Work is Changing the Way We Work	2022	Gallup	Productivity increased by 5% for remote workers
Remote Work and Productivity: A Meta-Analysis	2023	Harvard Business Review	Productivity increased by 10% for remote workers
Knowledge Worker Productivity in the Age of COVID-19	2022	University of Oxford	Productivity decreased by 2% for knowledge workers
The Impact of Zoom Fatigue on Knowledge Worker Productivity	2022	University of California, San Francisco	Productivity decreased by 10% for knowledge workers who use Zoom for more than 2 hours per day

So people use the time to do other things. That might well be interpreted as higher productivity by some; lower productivity by others.

But, strictly speaking, the ability to get one’s expected workload completed in less time should represent higher productivity, assuming one believes the output is measurable. The issue, perhaps, is that employees do not always use the time saved to do additional work. 

So firm productivity is likely unchanged, but personal productivity arguably could be higher. Firm unit costs might not change if the same output happens in a remote rather than workplace setting. 

But remote workers might create a time surplus that is not used to boost output further. 

That would essentially mean a  hypothesized “loss” of firm productivity, even if individuals were “more productive,” in terms of getting their accustomed workloads finished faster. There is extra time, but that  extra time is not used in the form of “productive” effort for their employers. 

Here we must also acknowledge that “extra time” exists even when workers are face to face at work, and such time is not mobilized “productively” in that context, either. 

There are all sorts of other possible productivity-related variables. To the extent some firms have been “hoarding” workers “in case” they needed them would be expected to result in lower “output” from those workers. They actually were not hired for “real” unmet needs, but as a hedge against needing their work later. 

That might be considered unproductive using any measurement method. A recent study by Microsoft of the amount of time people are using tools such as Microsoft 365 might, or might not, shed much light on “productivity.”

The study looked at the amount of time users spent with various Microsoft 365 apps. Some might say this is a measure of input, out output, but presumably has some indirect effect on “output.” 

The study shows people spend 57 percent of their time communicating in meetings, email, and chat, with 43 percent in activities that Microsoft calls “creation” and include use of spreadsheets, word processing, presentation software or notes. 

The 2023 Work Trend Index, which surveyed 31,000 people in 31 countries, is not a direct productivity measurement, but tracks time spent in applications, all of which are assumed to have some enabling role in producing actual knowledge worker output. 

source: Microsoft 2023 Work Trend Index

The key issue for some of us is that we do not actually believe knowledge worker productivity can be measured accurately. And most of the proposed measures--high level or detailed--seem to confirm the coarseness of metrics. 

At a high level, some might argue that knowledge worker or office worker productivity, at a high level, could possibly be measured using metrics such as the “number of units” produced. 

That might be lines of code, calls answered, courses taught or stories written. None of that can account for the quality of output, however. 

But much knowledge work is intangible, and the intangible is, by definition, harder to measure than the tangible. How do we measure the productivity of those who produce “experiences” for users or customers?

Also, much knowledge work is collaborative. By design, that makes individual contributions hard to measure. And much knowledge work is creative, such as problem solving or innovation. How do we measure, in quantitative terms, qualitative outcomes?

Some might argue that “revenue generated” is a productivity metric, but is nearly impossible to measure at an individual level, since sales are a product of the work of so many different teams. 

Yet others might prefer measures of “customer satisfaction.” Again, this can be hard to measure on an individual basis and might be nearly impossible at any level much lower than the single product or company reputation level. 

In some cases, a high level “time to market” metric might be considered, but again that is more a work group metric than a single individual measurement. 

Cost savings are almost never an actual measurement of productivity, though in principle it might be part of an evaluation in the short term. 

The bottom line is that we still have no idea whether knowledge worker productivity is rising, falling or remains unchanged.