Case Study: Locating New Pam and Susan's Stores

Pam and Susan's is a chain of discount department stores. There are currently 250 stores, mostly located throughout the South. Expansion has been incremental, growing from its Southern base into the Border States and increasingly into the Southwest. Identification of the most appropriate sites for new stores is becoming an issue of increasing strategic importance.

Store location decisions are based upon estimates of sales potential. The traditional process leading to estimates of sales potential starts with demographic analyses, site visits and studies by the company's real estate experts (augmented by input from local experts). The demographic data judged relevant for a given store location is that for people within a store's estimated "trading zone," usually defined as consisting of those census tracts within a 15 minute drive of the store. Planners in the real estate department consider current and expected future competition, ease of highway access, costs of the site, planned square footage of the store and estimates of average sales per square foot based on data from all existing stores. They judgmentally combine demographic information, site information and overall sales rates to come up with an estimate of sales for a new store.

Increasingly, actual store sales at new locations have deviated from estimates provided by the real estate department. There is interest in developing better methods for estimating sales potential. You have been hired as a consultant to explore the possibility of using the wealth of census data in stores' trading zones, along with data on individual stores, to predict sales potential.

To explore this option, variables derived from the most recent census were compiled for the trading zone of each of the 250 stores (there is no overlap in the trading zones of the 250 stores). For each store there is data gathered on demographics and economics of the trading zones, as well as size, composition and sales of the store. This data is in the file pamsue.xls (an excerpt is in Table 12.6).

Questions

1. How would you describe the type of location sites that are likely to have higher sales?
2. A group within the planning department had previously developed a subjective approach in which potential sites are classified according to an assessment of the "competitive type" of the trading zone. Below in Table A, the 7 "competitive types" are defined. How good is this classification method at predicting sales? How can you quantify this?
3. Two sites, $A$ and B, are currently under consideration for the next new store opening. Characteristics of the two sites are provided below in Table B. Which site would you recommend? Justify your choice and give the best sales forecasts you can. You may use the subjective classifications from Question 2 along with any other
   variables you think will give the best forecast. Give some estimate of the accuracy of the forecasting method you use and any other limitations of the forecasting method.
4. Two of the variables in the data base are under managerial control: the size of the store (square feet of selling area) and the percentage hard goods stocked in the store. Margins on hard goods (house wares, appliances, stationery, drugs) are different from margins on soft goods (clothing, for example). Do either of these factors appear linked to sales? If so, describe the link you observe and the managerial implications.
5. TECHNICAL: After developing your regression model, check to make sure the technical assumptions are satisfied. Comment on any points that would concern you based on the diagnostics.

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