Long Tail Doesn't Apply?

As observers have started to track sales of digital goods more closely, some apparently-contradictory evidence has started to appear about the "long tail" theory of sales in the digital domain. The concept: cheap digital distribution changes the retail sales function, allowing profitable sales of low-volume titles or items on a scale not possible in a physical distribution strategy. Most observers instinctively would agree. 

The key prediction has been that online distribution would allow niche businesses, content and goods to thrive in a digital distribution context impossible to sustain in a physical distribution context. As commonly understood, perhaps an additional 20 percent increase in volume should be feasible, as well as a change in "mass culture" that would fragment demand. 

But some sales data contradicts the notion. A new study by Will Page, chief economist of the MCPS-PRS Alliance, a music royalty collection organization, suggests that online sales success still relies on big hits. The study found that 80 per cent of all revenue came from around 52,000 tracks. For albums, of the 1.23 million available, only 173,000 were ever bought, meaning 85 per cent did not sell a single copy all year.

Frankly, the long tail now appears, in one sense, as the triumph of hope over experience. Many "wanted" online distribution to change purchasing patterns. The notion was that once huge variety was available, tastes would change. It isn't so clear why it is assumed "tastes" will change with different distribution. It is clear why fulfillment will change with cheaper distribution. But efficient, or better, distribution still should result in a "long tail" of demand that is the same as a distribution-induced "short tail" of demand. 

The reason derives from the theory itself. The idea behind the "long tail" is not actually new, and dates back to an Italian economist, Vilfredo Pareto, who in 1906 coined the Pareto Principle, popularly known as the 80-20 rule. Basically, the idea is that in much of life and nature,  roughly 80 percent of the effects come from 20 percent of the causes.

The same concept is known as Bradford's Law. 

As implied by the theory of the long tail, online distribution should allow retailers to sell small volumes of hard-to-find items, instead of selling a smaller number of highly-popular items. Most people can grasp that. What isn't so clear is why that expected distribution curve will be a "new" Pareto curve, instead of validating the existing Pareto curve. 

Under any normal set of circumstances, a Pareto distribution is what one would expect to see. Some have pointed to music sales at Rhapsody, an online music service. Of the 735,000 items for sale, 39,000 account for 78 percent of sales, while 796,000 titles represent 22 percent of sales. 

Likewise, Netflix data suggests 20 percent of total rentals are of "tail" or low-volume titles, while 80 percent of rentals are basically "hit movies" one would expect most people to be interested in. 

Is that confirmation of the operation of a Pareto distribution? Yes. Does it represent incremental sales of 22 percent that might not occur in a physical distribution scenario? Yes. Are the results unexpected? Not if one expects to see a Pareto distribution. 

Is the idea wrong, or useless? Not really. A Pareto distribution can assume a 70-30 pattern, for example, suggesting a bigger role for niche products than before. That represents an important shift of opportunity for providers of niche services and products because of online or Web distribution. 

But the long tail might not mean a revolution. Forrester Research, for example, estimates seven percent of retail sales in 2008 will have been made online, up from 3.2 percent in 2007. What does that mean? Most sales follow a Pareto curve: 97 percent of things sold still are sold the traditional way. There will be further shifts, of course.

But Pareto would suggest online sales will settle in at around 20 percent of total sales, at best, on a sustainable basis. 

Pareto Theorem, or 80/20 Rule, Applies to Telecom Attackers as Well

This is a good illustration of the Pareto theorem, which states that 80 percent of instances or outcomes in business or nature come from 20 percent of the cases or effort. The Pareto theorem is popularly known as the 80/20 rule . 

Of the 83 challengers in 20 telecom markets analyzed by Bain & Company, only (22 percent) grew both their revenue and free cash flow and increased their share of profit from 2010 to 2017.

source: Bain and Company 

That is a nearly-perfect example of the predicted Pareto pattern. 

source: IP Carrier 

Vilfredo Pareto, an Italian economist, was studying the distribution of wealth in1906. What he found was a distribution most people would commonly understand as the "80/20 rule," where a disproportionate share of results come from 20 percent of actions. The Pareto distribution has been found widely in the physical and human worlds. It applies, for example, to the sizes of human settlements (few cities, many hamlets/villages). It fits the file size of Internet traffic (many smaller files, few larger ones).

It describes the distribution of oil reserves (a few large fields, many small fields) and jobs assigned supercomputers (a few large ones, many small ones). It describes the price returns on individual stocks. It likely holds for total returns from stock investments over a span of several years, as most observers point out that most of the gain, and most of the loss in a typical portfolio comes from changes on just a few days a year.

The Pareto distribution is what one finds when examining the sizes of sand particles, meteorites or numbers of species per genus, areas burnt in forest fires, casualty losses: general liability, commercial auto, and workers compensation.

The Pareto distribution also fits sales of music from online music stores and mass market retailer market share. The viewership of a single video over time fits the Pareto curve. Pareto describes the distribution of social networking sites. It describes the readership of books and the lifecycle value of telecom customers.

No Bandwidth Hogs?

Some would argue there is no "exaflood" and no such thing as a "bandwidth hog." 

I have no more detailed data from any Internet service provider than anybody else does, so I doubt anybody can prove or disprove the thesis definitively. But I also have no reason to think the usage curve will be anything other than a Pareto distribution, since so many common distributions in the physical and business world conform to such a distribution.

Vilfredo Pareto, an Italian economist, was studying the distribution of wealth in1906. What he found was a distribution most people would commonly understand as the "80/20 rule," where a disproportionate share of results come from 20 percent of actions. The Pareto distribution has been found widely in the physical and human worlds. It applies, for example, to the sizes of human settlements (few cities, many hamlets/villages). It fits the file size of Internet traffic (many smaller files, few larger ones).

It describes the distribution of oil reserves (a few large fields, many small fields) and jobs assigned supercomputers (a few large ones, many small ones). It describes the price returns on individual stocks. It likely holds for total returns from stock investments over a span of several years, as most observers point out that most of the gain, and most of the loss in a typical portfolio comes from changes on just a few days a year.

The Pareto distribution is what one finds when examining the sizes of sand particles, meteorites or numbers of species per genus, areas burnt in forest fires, casualty losses: general liability, commercial auto, and workers compensation.

The Pareto distribution also fits sales of music from online music stores and mass market retailer market share. The viewership of a single video over time fits the Pareto curve. Pareto describes the distribution of social networking sites. It describes the readership of books and the lifecycle value of telecom customers.

So knowing nothing else than that the Pareto distribution is so widely represented in the physical world and in business, I would expect to see the same sort of distribution in bandwidth consumption. As applied to users of bandwidth, Pareto would predict that a small number of users in fact do consumer a disproportionate share of bandwidth.

I certainly can't say for sure, but would be highly surprised if in fact a Pareto distribution does not precisely describe bandwidth consumption.

Pareto Theorem Suggests Where and Why Millimeter Wave Spectrum Will be Useful

Pareto distributions--often colloquially referred to as the “80/20 rule.--are common in business, technology and nature.

Most of us are familiar with the 80/20 rule, which suggests that roughly 80 percent of value or outcomes are generated by about 20 percent of actions. Formally, it is the Pareto theorem. 

Virtually nobody would be surprised if told that the highest data demand in the U.K. mobile services market comes from areas such as London, Manchester or Glasgow, which are major population centers. 

What might be more surprising is that cell site data demand is about as disparate as the population data would suggest. According to Ofcom, the U.K. communications regulatory body, the largest 20 cities, containing 32 percent of the total U.K. population, cover about 2.4 percent of the surface area. 

source: Ofcom 

In fact, cell locations and data usage tend to show a Pareto distribution. Pareto would suggest that about 80 percent of mobile data usage is generated by 20 percent of the locations. 

source: Medium 

Pareto applies to most aspects of the connectivity, data center or computing businesses. It even applies to revenue generated by mobile cell sites. Half of mobile revenue is driven from traffic on about 10 percent of sites. Fully 80 percent of revenue is driven by activity on just 30 percent of cell sites. 

source: Ericsson 

Pareto also applies to mobile operator and telco revenue, profits, accounts and cost.  

source: Telco Strategies

That is clear in the distribution of customer accounts, ranked by revenue potential.

source: B2B International

source: Ofcom 

That Pareto distribution of data usage also shows where and why millimeter wave spectrum will prove useful. The skewing of data demand in a relatively small number of dense, urban areas suggests millimeter wave’s capacity advantages will prove most valuable there, as Verizon has argued. 

source: Verizon 

Don't Let Any "Good" Be the Enemy of the "Greatest Good"

source: Rype

The Pareto distribution can be seen in one’s personal or business life, in business strategy or business performance. The fundamental principle is that effort and outcomes are non-linear. A small number of inputs or instances drive most of the outputs or results.

The practical implication for communications or app providers is that a relatively small number of decisions and priorities actually matter, where it comes to making a transition from legacy to next generation business models.

The corollary is that there are a many “good” or “useful” or “helpful” things any service or app provider can do, but which should not be done, to concentrate on the few areas where breakthroughs are possible.

In other words, the temptation to “do” any number of helpful things actually can be detrimental to strategic success, which requires intense concentration on a relative handful of decisions, investments and effort.

There are always lots of useful or helpful things a company might do, to support its business. Many of those things actually will deliver a measurable result. But most will fail to help a company make a strategic breakthrough.

So saying “no” to most of those helpful things can be a prerequisite for focusing effort on a few matters that can decisively change a company’s future.

The areas in which Pareto applies are rather large. The Pareto theorem is the underlying principle of the “long tail” approach to freemium pricing, for example, where basic versions of a product are free, and users then pay incrementally more for additional features.

The Pareto rule can guide resource allocation, the principle being that there is some allocation or resources that makes a person or an organization better off, while not harming existing persons or the organization itself.

The principle is popularly understand as the 80/20 rule, which stipulates that about 20 percent of effort produces 80 percent of results.

The Gini coefficient essentially follows Pareto distribution patterns as well, and describes national income inequality patterns as well.

In the United States, the number of homes without a broadband connection follows a Pareto distribution.

It illustrates the law of diminishing returns. The cost of building access loops generally follow Pareto rules, for example. The inverse of the Pareto distribution is that a small number of instances produce most of the “per-line” access cost.

In other words, a small number of remote locations represent a disproportionate share of network cost, based on cost per mile.

source: National Broadband Plan

source: National Broadband Plan

80/20 Has Many Implications

One should not underestimate the importance of the Pareto theorem, commonly known as the “80/20 rule,” where 80 percent of results come from 20 percent of instances.  

One example are financial returns from the Standard and Poors 500 index, over the period 1989 to 2015, when just 20 percent of stocks accounted for 100 percent of index gains.

Put another way, 80 percent of stocks in the index actually had a collective return of zero percent.

source: A Wealth of Common Sense

In communication or other markets, the Pareto theorem matters because it tends to describe the broad structure of markets, as well as the generation of revenue and profits within each market.

In the Indian mobile services business, just 17 percent of customers generate 60 percent of revenues, for example.

The fundamental principle is that effort and outcomes are non-linear. A small number of inputs or instances drive most of the outputs or results.

The practical implication for communications or app providers is that a relatively small number of decisions and priorities actually matter, where it comes to making a transition from legacy to next generation business models.

The corollary is that there are a many “good” or “useful” or “helpful” things any service or app provider can do, but which should not be done, to concentrate on the few areas where breakthroughs are possible.

source: Rype

The Pareto rule can guide resource allocation, the principle being that there is some allocation or resources that makes a person or an organization better off, while not harming existing persons or the organization itself.

In other words, at some point, additional effort will produce diminishing returns.

The Gini coefficient essentially follows Pareto distribution patterns as well, and describes national income inequality patterns as well.

In the United States, the number of homes without a broadband connection follows a Pareto distribution.

It illustrates the law of diminishing returns. The cost of building access loops generally follow Pareto rules, for example. The inverse of the Pareto distribution is that a small number of instances produce most of the “per-line” access cost.

In other words, a small number of remote locations represent a disproportionate share of network cost, based on cost per mile.

source: National Broadband Plan

source: National Broadband Plan

In practical sense, the Pareto theorem suggests that a small number of actions actually drive most of the actual organization results. 

In other words, the temptation to “do” any number of helpful things actually can be detrimental to strategic success, which requires intense concentration on a relative handful of decisions, investments and effort.

There are always lots of useful or helpful things a company might do, to support its business. Many of those things actually will deliver a measurable result. But most will fail to help a company make a strategic breakthrough.

So saying “no” to most of those helpful things can be a prerequisite for focusing effort on a few matters that can decisively change a company’s future.

80% of Results from 20% of Actions, Firms, Products, Services

Only 20 percent of actions lead to 80 percent of results, in business, life or telecom.

It usually is surprising how often a Pareto distribution occurs in business or nature. Most underlying trends in any business follow a Pareto distribution, commonly known as the “80/20” rule, where 80 percent of results flow from some 20 percent of the instances. That applies for consumer manufacturer warranty claims, for example.

In the telecom and most other businesses, as much as 80 percent of the profit is generated by serving 20 percent of the customers, while 80 percent of the revenue is generated by 20 percent of the products.

Apparently equity market returns also show a Pareto distribution.

source: Longboard Funds

Most workers make tradeoffs between housing costs and commuting time and hassle that show a Pareto distribution.

In  the healthcare domain, the sickest 20 percent generate 79 percent of health care costs.

In the domain of athletic training roughly 20 percent of the exercises and habits have 80 percent of the impact

It is likely that similar Pareto distributions exist for all forms of internet access and communications infrastructure, where 80 percent of the value comes from 20 percent of the decisions or instances.

As a practical matter, Pareto means I have to spend more of my research time on the relatively few connectivity firms that generate 80 percent of the revenue in any particular market, even if much of my work has included managed services providers, distribution partners and others that are part of the 80 percent of firms that generate 20 percent of the revenue.

Fibonacci, Pareto and the Connectivity Business

Some mathematical ratios reoccur so often they are applied in nature and business. Fibonacci provides an example. “The Fibonacci sequence is a famous group of numbers beginning with 0 and 1 in which each number is the sum of the two before it. It begins 0, 1, 1, 2, 3, 5, 8, 13, 21 and continues infinitely,” Smithsonian magazine says.

Fibonacci sequences drive the Golden Ratio which applies to mollusk shells, sunflower florets, and rose petals to the shape of the galaxy. In financial markets Fibonacci is used by technical traders.

“If you divide the female bees by the male bees in any given hive, you will get a number near 1.618,” notes Investopedia.  “The golden ratio also appears in the arts and rectangles whose dimensions are based on the golden ratio appear at the Parthenon in Athens and the Great Pyramid in Giza.” 

Others note Fibonacci sequences also apply to human anatomy. 

source: Smithsonian 

The Pareto theorem also occurs often in life and business. Most of us are familiar with the 80/20 rule, which suggests that roughly 80 percent of value or outcomes are generated by about 20 percent of actions. Formally, it is the Pareto theorem. 

We also tend to see Pareto distributions in global connectivity provider revenue, though the pattern is clearer when looking at net profit rather than gross revenue, for example. As a rule, profits are driven by business accounts rather than consumer accounts, for example; urban areas rather than rural areas; dense parts of cities more than suburbs; some product lines rather than others.  

source: Techeconomy 

The traditional rule for fixed networks is that service providers made money in urban areas; broke even in the suburbs and lost money in rural areas. That arguably remains true for mobile networks as well. 

If usage is a measure of implied profit, then mobile operators might earn as much as half their “revenue” from about 10 percent of sites. Perhaps a total of 30 percent of all cell sites handle 80 percent of traffic, and hence, revenue. 

Another way to think about it is any single user’s usage. For any single user, perhaps half of all usage occurs in just one macrocell. About 80 percent of usage happens in three cells. About 20 percent of usage happens in 28 additional cells. Again, we see a Pareto style distribution: just four cells handle 80 percent of any single user’s traffic. 

source: T-Mobile

One way of possibly using Pareto is ownership of cell sites versus leasing capacity. A competitive supplier--such as a cable operator--might conclude it is best to own the sites where half to 80 percent of usage happens. That might include the home coverage and work site coverage, which are fixed usage locations. 

That is especially true if a cable operator can use its own existing network to support such cell sites. For the 20 percent of usage that happens when people are out and about, it makes sense simply to buy wholesale capacity. 

All service providers essentially try to do this when segmenting their customer bases. If most of the profit comes from  one or just a few customer segments, it makes sense to focus on those segments. The segmentation can be geographic, customer type, customer volume; product line or demographic or psychographic. 

The point is simply that mathematical patterns exist in the business. 

80/20 Rule for Telecom Revenue Sources

This is a good illustration of both the Pareto theorem, which states that 80 percent of instances or outcomes in business or nature come from 20 percent of the cases or effort. The Pareto theorem is popularly known as the 80/20 rule.

The graph shows the percentage of total mobile service revenue generated by cell sites, if one apportions the mobile subscription fee to the sites that actually are used by any customer. 

Pareto accurately describes the actual use of mobile cell sites and radios, as well as the generation of revenue. 

Half of mobile revenue is driven from traffic on about 10 percent of sites. Fully 80 percent of revenue is driven by activity on just 30 percent of cell sites. 

source: Medium 

The theorem also explains why 80 percent of revenue generated by challengers in the telecom business come from about 20 percent of firms. 

In organizational terms, Pareto implies that 80 percent of results are driven by 20 percent of the actions or people. 

A perhaps-obvious question should arise: if 80 percent of results are generated by 30 percent of the instances, sites or actions, why bother with the other 70 percent? In part, the answer is network effect. A mobile operator whose network only covers 30 percent of the land mass where people actually live and work would not be able to compete with a supplier whose network covers nearly all the places people live and work. 

The traditional rule of thumb for a fixed network is that it makes money in urban areas, breaks even in suburban areas and loses money in rural areas. Profit is a Pareto distribution, but what mass market telco could survive if it refused to sell to rural or suburban customers?

What social, voice, messaging or other network would do as well if it connected just 30 percent of people you wanted to reach? In other words, a network often must connect “most” potential nodes to drive value. 

Universal service requirements for public telecom networks exist for that reason.

Pareto also exists because value for any single user depends on the number of other people or entities that specific person might ever wish to connect with. The actual set will be different for each person. But the network has to enable connections in unlimited fashion, so that any specific set can be created.