Choosing an optimal location may be a critical issue for numerous businesses including businesses involved in retail, manufacturing, franchising, and housing. Numerous factors may contribute to the choice of the eventual location of a business location. These factors include, traffic flow, parking, real estate availability, cost, appearance, customer demographics, location of competitors, location of anchor businesses (i.e., businesses that attract customers that would be suitable for one's own business), barriers to traffic flow, and zoning. Currently, most companies use human insight and experience to combine these heterogeneous factors into a prediction regarding optimal business locations. Tables, spreadsheets, and experts are typically used to support the determination. However, even sophisticated retailers and fast-food companies may find that business location selection remains primarily a human endeavor.
There are a number of drawbacks to relying on traditional methods of business location selection. First, some businesses desire to have a clearly an articulated method to select their numerous business locations. The method is ideally applied uniformly so that methodology errors can be uniformly corrected.
Second, even with carefully articulated methods, human bias can introduce uncertainty and problems surrounding location selection. Biased, in this sense, means decisions are based in some measure on individual opinion and perception instead of actual data.
Third, since volumes of data is available, the process of analyzing data and choosing optimal locations based on the available data can be arduous and time consuming, which limits a decision-maker's ability to choose numerous optimal business locations within a short period.
Fourth, even where useful information is analyzed, it must be conveyed to a decision-maker. Sometimes the conclusions resulting from human efforts to analyze heterogeneous data is presented in a format where relationships between various pieces of data can be missed, resulting in less than optimal decision making.
A web site hosted at by Zillow, Inc. uses a spatial grid with an overlying heat map to present residential housing values. This presents home value data to a user in a simple and easily understood way. Varied colors indicate the average value for regions having a same color. Particular locations under investigation may be indicated with an icon. Clicking on the icon divulges more detailed information about the particular location. Real estate experts as well as casual information seekers can use this site. Although a wealth of data is presented in a user-friendly format, the data does not make any predictions.
A better way of choosing business locations is desired. Particularly, a way of choosing business locations, which is fast, utilizes numerous heterogeneous data sources, and consistently facilitates the making of useful business location choices is desired. It is also desired to have a decision support system that helps people select and otherwise make decisions about particular business locations. It is further desired to have a system that is easy to use.