Scenario: You are the Vice President of Franchise Services for the Lucky restaurant chain. You have been assigned the task of evaluating the best location for a new Lucky restaurant. The CFO has provided you with a template that includes 6 criteria (attributes) that you are required to use in your evaluation of 5 recommended locations. Following are the 6 criteria that you will use to evaluate this decision:
Traffic counts (avg. thousands/day)—the more traffic, the more customers, and the greater the potential sales.
Building lease and taxes (thousands $ per year)—the lower the building lease and taxes, the better.
Size of building (square feet in thousands)—a larger building is more preferable.
Parking spaces (max number of customers parking)—more customer parking is preferable.
Insurance costs (thousands $ per year)—lower insurance costs are preferable.
Ease of access (subjective evaluation from observation)—you will need to “code” the subjective data. Use Excellent = 4, Good = 3, Fair = 2, and Poor = 1.
Now that you have collected the data from various sources (your CFO and COO, local real estate listings, personal observation, etc.), you have all the data you need to complete an analysis for choosing the best location. Download the raw data for the 5 locations in this Word document: BUS520 Module 3 SLP.docx
Review the information and data regarding the different alternatives for a new restaurant location. Then do the following in Excel:
Table 1: Develop an MADM table with the raw data.
Table 2: Convert the raw data to utilities (scaled on 0 to 1). Show the utility weights in a second table.
Table 3: Develop a third table with even weights (16.7%) for each variable.
Evaluate Table 3 for the best alternative.
Table 4: Complete a sensitivity analysis by assigning weights to each variable.
In a Word document, do the following:
Complete Excel analysis using MADM (all four tables noted above must be included).
Accurate Excel analysis (Excel file includes working formulas showing your calculations; all calculations and results must be accurate).
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