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Case Study: Locating New Pam and Susan’s Stores – Need help with this case study

Situation
Pam and Susan’s is a chain of discount department stores.* The original store was opened in the South in the mid-1950s by Pam and Susan’s father. About 10 years ago,Pam and Susan took over operational control of the stores, working together under a joint power sharing arrangement. The unusual management arrangement and consensusdecision making by the two women, for which they have received a great deal of publicity, have contributed in part to sales growth and to the recent upsurge in newstore openings. Fundamentally, however, their success is based on an uncanny ability to appropriately stock stores and underprice competitors. State-of-the-artbusiness processes are at the core of their low price structure.

There are currently 250 Pam and Susan’s stores, mostly located throughout the South. Expansion has been incremental, growing from its Southern base into the BorderStates 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 locationis that for people within a store’s estimated “trading zone,” usually operationalized 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 thestore, and estimates of average sales per square foot, based on data from all existing stores. They judgmentally combine the demographic information, site informationand overall sales rates to come up with an estimate of sales for a new store. Pam and Susan’s stores have primarily targeted lower-middle class to poorerneighborhoods/trading zones.

Increasingly, actual store sales at new locations have deviated from estimates provided by the real estate department. Pam and Susan want to develop better methods forestimating sales potential. A consultant (you) has been hired to explore the possibility of using the census data in stores’ trading zones, along with data onindividual stores, to construct regression models to help make the location decisions..

To explore this option, a number of variables derived from the most recent census were compiled for the trading zone of each of the 250 stores (there is no overlap inthe trading zones of the 250 stores).

Demographic Variables:
• population: % black
• population: % Spanish speaking
% in each of the following family income categories (000s): 0-10; 10+-14; 14+-20;
• 20+-30; 30+-50; 50+-100; >100
• median yearly family income
• median rent per month
• median home value
• % home owners
• % with no cars
• % with one car
• % households with TV
• % households with washer
• % households with dryer
• % households with dishwasher
• % households with air conditioner
• % households with freezer
• % households with second home
• % adults (over age 25) with the following years of education: 0-8; 9-11; 12+
• total population
• average family size

Store Data (collected on each store)
• square feet of selling area (000s)
• annual sales (000s of $)
• % hard goods

Competitive Types
• Type 1: Densely populated areas, particularly good store sites with relatively little direct competition
• Type 2: Good locations in relatively high-income areas, with little direct competition
• Type 3: Locations near major shopping centers
• Type 4: Stores in downtown areas of suburbs
• Type 5: Stores with competition from discounters only (not from department stores)
• Type 6: Stores in shopping centers
• Type 7: Old stores located along the sides of major roads.

Proposed New Site Locations

Site A Site B
Store size:
gross square feet 170,000 160,000
selling square feet 125,000 120,000

Competitive group 1 5
Population
black 40.0% 13.8%
Spanish speaking 10.8% 6.6%

Family income (000)
0-10 26.6% 19.2%
10+-14 14.0% 13.0%
14+-20 19.9% 22.2%
20+-30 23.9% 27.1%
30+-50 13.3% 15.7%
50+-100 2.0% 2.5%
> 100 0.3% 0.3%

Median yearly income $16,838 $18,802
Median rent per month $160 $166
Median home value $46,790 $36,058

% homeowners 10.1 10.7
% no cars 57.0 44.0
% 1 car 36.6 45.7
% TV 90.0 93.6
% washer 41.8 53.6
% dryer 9.0 12.2
% dishwasher 6.0 4.6
% air conditioner 17.9 39.3
% freezer 6.1 5.0
% second home 1.6 4.6

Education: %
0-8 37.4 40.1
9-11 24.1 23.5
12 29.0 25.5
13-15 5.6 5.2
16 plus 3.9 5.7

Total population 955,000 431,285
Average family size 3.7 3.5

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