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.