Low Take Rates for Subsidized Home Broadband?

Apparently just over one percent of U.K. households take advantage of a home broadband for low-income residents program. Such programs seem to be widely available, but take rates are quite low. 

 In the United States, up to 45 percent of California households appear to qualify for subsidized home broadband programs and 27 percent of those households do so. In Colorado some 20 percent of eligible households appear to take advantage. 

But some observers believe the current program will expire before reaching take rates of 68 percent nationally. 

It is not clear whether participants were “unconnected” before or were already buying internet access. Supporters sometimes count all the participants as having not had internet access prior to joining the program, and that is not likely. The program provides a $30 discount off any published plan. 

Existing ISP programs had routinely offered low-cost access at speeds lower than 100 Mbps. The Affordable Connectivity Plan offers subsidies for 100-Mbps at no cost to qualifying households.  

But there are many reasons why some households choose not to purchase  internet access because they do not want to use the internet or do not need home broadband because they use the internet in other ways, such as by mobile phone, or get access at other locations. 

Mobile Data Traffic is Correlated with GDP

Analysys Mason estimates that a 100 percent increase in mobile data traffic translates into a 0.98 percent impact on gross domestic product. That is a correlation, not necessarily causation, as always is the case for economic impact studies. 

But that is the problem with all efforts to quantify the economic impact of any particular innovation, product or industry. We might estimate impact, but we cannot prove the causal relationship of any single input when results (economic growth, for example) is caused by multiple inputs.

Consider that, in addition to the volume of mobile data traffic, the capacity of undersea cables, home broadband adoption, use of information technology,  transportation systems, energy supplies, broadband speed, educational attainment, household wealth, housing density, business activity levels, ethnicity and age can be correlated with gross domestic product as well. 

It is impossible to clearly separate the impact of each input when determining countrywide economic output. During the Covid pandemic, we discovered correlations between risk factors and deaths. But correlation is not causation. 

One might argue for a correlation between electricity consumption and GDP, for example. 

Among OECD member countries, for example, gross domestic product increases by 1.7 percent per year. Electricity use increased by 0.9 percent per year between 2015 and 2040. In non-OECD countries, GDP increases by 3.8 percent per year, and electricity use increases by two percent  per year over the same period, according to the U.S. Energy Information Administration. 

The point is that there is a correlation between electricity usage and GDP. 

source: Our World in Data 

Higher GDP is associated with higher energy consumption. 

source: EIA 

The other problem is that if one were to try and add up all the claimed economic benefits caused by each input or industry, the results would not comport with reality. The claimed output would vastly exceed reality. 

“We find that a 10 percent increase in the fraction of the population ages 60+ decreases the growth rate of GDP per capita by 5.5 percent,” the RAND Corp. has found. “Two-thirds of the reduction is due to slower growth in the labor productivity of workers across the age distribution, while one-third arises from slower labor force growth.”

Transportation might be correlated with about five percent of GDP as well.  

The point is that better communications and connectivity always are assumed to correlate with better GDP outcomes. We can disagree about the magnitude of such correlations while assuming there is a correlation. 

But neither can we accurately measure the specific causation of any single input.

More Streaming Bundles?

Streaming service bundling was probably inevitable, as bundling of products has been a staple of the consumer content and communications business for some decades. Lower marketing costs, higher perceived value, lower churn and perceived distinctiveness are some of the advantages. 

Bundling also makes price comparisons more difficult, as the retail price for the bundle obscures the actual “price” for any single bundle component. That becomes more obvious as disparate services or products are added to any bundle. 

Some decades ago bundling sometimes was described as having value because it simplified the customer billing interaction. Most of us would have a hard time identifying that as a value which is relevant to most--if not all--buyers. 

In almost all cases, price discounts are the attraction of a bundle. 

For some content owners, discounted offers for purchases of multiple owned steaming services is something of a no-brainer. 

Bundling of streaming services with other products such as a mobile subscription also has become common. The point has been to create differentiation in a crowded marketplace by adding value beyond content access. 

source: Axios 

The other new trend in the U.S. streaming business is multi-sided revenue models, particularly using advertising in addition to subscription fees paid by end users. By effectively lowering price points, demand is stimulated. 

As linear content services always have been about bundles, now streaming will do the same, perhaps eventually creating bundles of bundles. The trade off, as always, will be higher volume at the cost of lower profit margins per unit.

T-Mobile may be prepping the sale of Sprint's wireline business | Light Reading

For those with long memories, it might be shocking that the former Sprint wide area network books just $1 billion annual revenue. http://dlvr.it/SWXWpj
http://dlvr.it/SWXWpj

Digital Transformation is Hard

If you have been around information technology investments long enough, you know that outcomes often are negative: the hoped-for benefits do not emerge at all, or prove to be less than expected. Possibly 30 percent of major IT investments actually produce the expected results. 

The same continues to be true of digital transformation efforts and investments. A new survey of IT professionals suggests DX has the same outcomes. 

source: Walkme 

The study also had respondents estimating that, of all IT projects, fully 41 percent failed to meet objectives, in the form of key performance indicators. And the larger the organization, the more likely it is that DX or any other IT initiative will fail. Larger enterprise respondents reported failure rates at six times the rate of small entities. 

source: Walkme 

To be sure, the more-important KPIs deal with financial performance: productivity, equity value growth, higher income or lower costs. 

Such “failures” are not hard to understand. Most large enterprises rely significantly on third-party integrators to attempt complex initiatives. That means lots of organizational complexity. And the number of persons who must not only agree to support, but actively ande usefully support such initiatives is therefore quite high. 

source: Walkme 

And that runs squarely up against an immutable law: the more permissions one requires to get anything done, the lower the chances of success. Consider any project with a number of key influencers. Assume that at each stage, the chances of getting a “yes” are 50 percent.

If only one “yes” is required, odds of success are 50 percent. If two “yes” hurdles are required, success rates drop to 25 percent. If three “yes” hurdles exist, odds drop to 13 percent. Each successive hurdle reduces success rates further. 

As you can see, even a small number of hurdles, each with a 50-50 chance of success, quickly reduces odds of success to an impossible level. After seven hurdles, odds of success are one in 100. 

Obviously, any complex IT project has many more gates than seven. With sufficiently vigorous top-level support, the odds of success at each gate are likely higher than 50 percent. But there are so many more hurdles or gates that odds of success are low; odds of failure high. 

The conventional wisdom is that about 30 percent of big IT projects actually succeed as expected.

Is Sustainable Advantage from "Digital Transformation" Illusory?

Competitive advantage from “digital transformation” will be as transitory as all earlier applications of computing and information technology, one might conclude from a Gartner assessment. 

In other words, sustainable competitive advantage will not be possible. 

As digital networks, “always on” connectivity, and smart devices become ubiquitous and commonplace, computing will simply fade into the background, becoming as unobtrusive as the dumb thermostat or light switch, says Ed Gung, Gartner Research Board managing VP.

As digital technology becomes embedded into the way all parts of the business operate, “digital” will cease to be a useful modifier, he also notes. In the end, digital technology will become just one more dimension on which companies compete. 

Distribution networks, capital assets, exploration rights, customer relationships and content are other levers companies can pull. But sustainable advantage will be difficult to maintain in those realms as well.

Can We Actually Measure Knowledge Worker Productivity, In Office or Remote?

The debate about the productivity of remote work will likely never be fully settled, in large part because it is so difficult, perhaps impossible, to measure knowledge worker or office worker productivity. 

Whether knowledge worker productivity is up, down or flat is almost impossible to say, despite claims one way or the other. Much of the debate rests on subjective reports by remote workers themselves, not “more-objective” measures, assuming one could devise such measures. 

Measuring intangible output is inherently more challenging than measuring output of physical goods. And some “test effect” occurs, at least temporarily. The output of workers who know they are being tested tends to rise during the period of the test. 

There will always be room to contest managerial effectiveness at managing remote workers; the ability of workers to perform as well remotely as “in the office” and differences between workers (motivation and actual output). 

There also will be room to contest the impact of heavy remote work on company culture; collaboration and other “soft” outcomes at levels beyond individual effort and output. Do work groups actually perform as well, or better, in remote work settings? Do companies benefit in other ways that are measurable and offset any potential costs?

And beyond all that, productivity arguably is an issue affecting broad swaths of the U.S economy, no matter what the form of work setting. 

Productivity—defined as output per labor hour—has grown at a below-average rate since 2005, representing a dramatic reversal of the above-average growth of the late 1990s and early 2000s, according to the U.S. Bureau of Labor Statistics. 

source: Bureau of Labor Statistics

Assume you believe the measurements are correct, and that non-farm productivity actually can be measured. Labor productivity compares the amount of goods and services produced (output) with the number of labor hours (inputs) used to produce those goods and services. Productivity is defined mathematically as output per hour of work, and growth occurs when output increases faster than labor hours.

As always, there are caveats. Such measures are not good at capturing hedonic improvements. 

Hedonic qualIty adjustment is a method used by economists to adjust prices whenever the characteristics of the products included in the consumer price index change because of innovation. Hedonic quality adjustment also is used when older products are improved and become new products. 

Hedonically adjusted price indices for broadband internet access in the U.S. market--adjusted for quality improvements such as speed--then looks like this:

source: Bureau of Labor Statistics 

Also, the productivity of knowledge or office workers is very hard--perhaps impossible--to measure. Virtually any quantitative way of measuring “input” is only a supposed proxy for productivity itself. 

Perhaps of notable significance are changes in “multi factor” inputs beyond capital investment and labor cost. That is where information technology, managerial skill, changes in goods produced or cultural changes apply. 

The point is that the debate over “remote versus in-office work” is more about politics and emotion than economic facts. Firms can do it or not do it, but we should stop claiming we are motivated by clear economic facts.