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20 T E C H N I C A L F E A T U R E Site Selection Methods Can Help Businesses with Expansion By Felipe Calderon and Danny Heuman During a business’ lifetime, owners and managers are faced with the decision of whether or not to expand. With expansion, the business is usually confronted with a significant number of alternatives to be evaluated, from which only one (or, at most, a few) will be selected. Site screening models help businesses evaluate hundreds of locations using a set of criteria selected by the business in conjunction with MapInfo’s custom research experts. Business representatives offer their past experience on the criteria they understand contribute most to the success of the overall business, while MapInfo experts, based in MapInfo Canada, assist by offering knowledge of business trade areas classification, usage of demographic and socioeconomic data in analysis and methods of measuring spatial relationships. The main goal of a site screening model is the evaluation of many site alternatives, with each assigned a score. A site screening model sweeps across the market study area evaluating the degree to which the selected criteria match the actual trade area statistics. The score represents how close a prospective candidate’s points match the criteria used to develop the ranking. The final output is a set of ranked areas, taking into account the combined efforts of business analysts and MapInfo experts. SPRING 2001 MAPINFO MAGAZINE www.mapinfo.com/magazine IDENTIFYING AND SELECTING NEW LOCATIONS FOR EXPANSION IS COMPLEX, WITH MANY FACTORS REQUIRING EVALUATION AND MEASUREMENT. MAPINFO, THROUGH ITS CANADIAN-BASED CUSTOM RESEARCH GROUP, PREPARES SITE EVALUATION MODELS FOR BUSINESSES INCLUDING FINANCIAL INSTITUTIONS, RESTAURANTS, TELECOMMUNICATIONS AND INSURANCE COMPANIES. A SITE SCREENING MODEL IS A FIRST STEP IN THE SITE SELECTION PROBLEM. Final Score Distribution showing areas of potential expansion There are three main components required for the analysis: a list of candidate locations, identification of factors that influence location and the weights applied to the factors. Candidate points do not represent specific locations, but the general neighborhood in which a new outlet could be located (see map on page 21). An average sized market could have as many as 500 neighborhoods or candidate points evaluated, representing each and every census block group or major street intersection. The area may be as small as a city block in larger urban areas or something larger in more rural areas. Some businesses choose to restrict potential locations to areas identified as strip retailing, shopping centers or commercial areas. Typical factors included in the model include demographics, current customers and spending habits, daytime population and competitor locations. Income, age of people in neighborhood, occupations and family status are often incorporated in the model. This is where the business analyst’s and MapInfo’s expertise on the subject are leveraged. The third input in the model is a set of weights that rank the importance of factors as they contribute to the final score.
Distribution of Candidate Points—Tucson Area Spreadsheet containing Site identifiers and key demographic and socioeconomic factors These weights sum to 100 in absolute value, can be positive or negative, and are allocated across the selected factors. For example, a high average household income may be allocated 15 points and be positive, indicating that the presence of high income in and around the neighborhood is good. On the other hand, locating close to competitors may be negative and not desirable and be allocated 12 points. After all the required information is collected and an agreement is set in determining final factors to be used in the analysis, the data processing takes place. A standardization of the data eliminates differences among factors due to different units of measurement (e.g., number of people vs. dollars spent). Once the data are all represented in the same scale, the selected weighting scheme is applied. The last step is the calculation of the final score by adding the weighted factor scores obtained for every potential neighborhood. There is some flexibility with the final score; users may try different weighting schemes and check corresponding results. The results of a site screening model are usually expressed through two different but complementary types of output— a spreadsheet and a map. The spreadsheet contains a neighborhood point identifier, the raw and standardized data for the neighborhoods and the final score obtained through the analysis (see spreadsheet on left). The table is sorted on the score column in descending order with the best matching areas at the top. These are the neighborhoods that should be investigated further as potential new locations for the business. The map adds a spatial dimension to the results, showing where the most attractive areas (and the unattractive areas) are. Some areas are too close to be considered separated, and it is common to use a smoothing algorithm to merge some of the closest areas to be considered as one. The map shows every neighborhood point in one of five colors or shading according to the score obtained in the analysis (see map on page 20). The map shows not only the most attractive areas, but also their spatial context and gives direction where to look for a specific site in a more informed way. Whether in the financial, retail, manufacturing or communications industry, there is still a requirement to have an established network of locations to offer services. In looking to making an informed decision, a site screening model can help businesses focus their attention to the main issues of new locations: Who are my customers? What types of areas must I consider? What factors contribute to a successful store and how important are they? With MapInfo Canada’s data modeling knowledge and MapInfo software, these location questions can be intelligently considered. Felipe Calderon is senior research analyst and Danny Heuman is director, custom research with MapInfo Canada. I N D U S T R Y F O C U S : DATA By Jon Winslow A Wicked Cool Bonus— 2000 Census Data When the U.S. Census Bureau started releasing its 2000 data it was a delight to marketers around the country. The 2000 Census data provides an intimate look at population swings, demographic groups, regional migrations and changing family structures, helping marketers to better target customers, perform market analysis and pinpoint new site locations. Companies use the Census to track today’s most carefully watched trends and forecast tomorrow’s. A few years ago, everyone was asking about senior citizens and looking to design health-care programs and assistedliving facilities. Now, the focus has shifted to requests about well-to-do teenagers. Today’s teenagers are wealthier than any teenage group in the history of the country. Every business has a special niche, a specific age, economic or ethnic segment of the population that it is especially interested in locating. It is not just the Fortune 1000 companies, it is Internet start-ups, real estate developers, and anyone marketing to consumers using Census information to enhance its market and customer analysis. The 2000 Census data enables MapInfo to validate estimates and set a base line for future analysis. MapInfo ® TargetPro ® v3.6 is the first MapInfo solution to utilize input from the newly released Census data, further enhancing this powerful market analysis and demographic segmentation solution. MapInfo adds tremendous value to the Census data through annual updates, the creation of additional modeled databases and the integration of data into MapInfo’s powerful, easy-to-use solutions—ultimately helping marketing professionals to make critical business decisions. MapInfo’s ability to clarify and interpret the data and supplement it with additional demographic information enables our customers to easily identify market trends, reach target markets and provides them with an important competitive advantage. MapInfo’s release of TargetPro v3.6 this Spring contains demographic estimates and projections on items such as population, households, median income and age, which are influenced by the Census 2000 information. This data packaged with a variety of other Census-based marketing databases provides a robust market and customer analysis solution for marketing organizations around the world. Jon Winslow is market director of CRM with MapInfo Corporation. SPRING 2001 MAPINFO MAGAZINE www.mapinfo.com/magazine 21
Page 1 and 2: 6 MapInfo Delivers Today’s ‘Kil
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