This study covers the latent demand outlook for data processing and network services across the states and cities of the United States. Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given across some 12,900 cities in the United States. For each city in question, the percent share the city is of it’s state and of the United States is reported. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others. This statistical approach can prove very useful to distribution and/or sales force strategies. Using econometric models which project fundamental economic dynamics within each state and city, latent demand estimates are created for data processing and network services. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.
This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the cities in the United States). This study gives, however, my estimates for the latent demand, or the P.I.E., for data processing and network services in the United States. It also shows how the P.I.E. is divided and concentrated across the cities and regional markets of the United States. For each state, I also show my estimates of how the P.I.E. grows over time. In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on strategic planning at graduate schools of business.
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