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