What is statistical planning employed in sales forecasting?

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Quantitative analysis, the use of statistical modeling for the purpose of providing a predictive capability, is often used in sales forecasting for the logical reason that it exists largely for that purpose. By accumulating data on past and current commercial transactions and examining that data for patterns, sales managers and other corporate executives are able to predict future sales activities. While statistical modeling is used for projecting sales, it is not without flaws. Product development is predicated upon current activity and careful assessments of future market trends. In other words, today's product may not be in demand tomorrow. Consumer tastes change, and wholesalers and retailers alike loathe the prospect of ending up with large surpluses or inventories of items no longer in demand. Such surpluses represent wasted resources, including the space occupied by those items, the costs of the raw materials involved in their manufacture, and associated shipping costs. Statistical modeling will always play a role in sales forecasting. It is not, however, an fallible process for projecting into the future. Consumer demand, often dependent upon both current trends and economic considerations, is too fickle. Statistical modeling does not reflect either of these variables, so it is inherently limiting. It remains an important component in forecasting sales, but it is not without its risks.

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Statistical planning entails the collection of data and the analysis of this information. Statistical planning is a direct result of statistical inference, and statistical inference is basically the interpretation of any given data set. In inferential statistics, the analysis is geared toward the larger population of any given data set, and after the properties of this given data set are interpreted, this information is then used to form and test hypotheses that inform subsequent estimates based upon data sampled from a larger population. In sales forecasting, statistical planning would be necessary to form a comprehensive understanding of market supply and demand. By using data from a given population, businesses can better understand the behavior of consumers, and with this understanding, they can develop business models that are tailored to market demand. Statistical planning is just the mode by which businesses collect and interpret data. This information is then used to inform sales forecasting, which is the process of estimating sales within a specific market. Sales forecasting protects businesses from profitless expenditures, and businesses use both of these practices in order to protect their investments and capitalize on economic trends. 

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