Module 3 - SLP PIVOT TABLE AND MULTI-ATTRIBUTE DECISION ANALYSIS

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Module 3 - SLP

PIVOT TABLE AND MULTI-ATTRIBUTE DECISION ANALYSIS

Assumed Certainty: Multi-Attribute Decision Making (MADM)

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

Assignment

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:

Discuss the process used to put together Tables 1–4 above.

Provide the rationale you used for choosing for each of the weights you used in Table 4.

Give your recommendation of which location the company should choose (based on results of Table 4).

SLP Assignment Expectations

Excel Analysis

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).

Written Report

Length requirements: 2–3 pages minimum (not including Cover and Reference pages). NOTE: You must submit 2–3 pages of written discussion and analysis. This means that you should avoid use of tables and charts as “space fillers.”

Provide a brief introduction to/background of the problem.

Discuss the steps you used to compile the Excel analysis (i.e., the four tables).

Discuss the assumptions used to assign weights to each variable of your sensitivity analysis (Table 4). That is, provide the rationale for your choice of weights for each variable.

Provide a complete and meaningful recommendation related to the location that should be chosen as a new site.

Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size.

Have an introduction at the beginning to introduce the topics and use keywords as headings to organize the report.

Avoid redundancy and general statements such as "All organizations exist to make a profit." Make every sentence count.

Paraphrase the facts using your own words and ideas, employing quotes sparingly. Quotes, if absolutely necessary, should rarely exceed five words.

Upload both your Excel file and written Word report to the SLP 3 Dropbox by the assignment due date.

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attachments

calculation-module-3-slp.xlsx (13.48 KB)
Preview of calculation-module-3-slp.xlsx
(subjective)Table     DataTraffic   (average thousands/day)Building     ft    
solution-module-3-slp.docx (30.22 KB)
Preview of solution-module-3-slp.docx
minimum     chosen   on the     the       a   value for     considered       and   the other     lower       Costs   considered for     After       weights   applied to     values       important   the various     different       significance   this case,     and       have   assigned the     of       since   attributes add     economic       location   terms of     customers       On   lines, a     at       will   in a     capacity,       larger   to serve     Hence       next   weightage (at     Insurance       Parking   are given     weightage       their   significance in     Table       derived   factoring in     and       applying   sum of     (sum       by   utility values)     (average       Lease   Taxes ($000/year)Building     ft       (maximum   of customer
solution-module-3-slp-updated.docx (34.07 KB)
Preview of solution-module-3-slp-updated.docx
of     year)Ease   Access(subjective evaluation)Total     000       700   648Stuttgart0 000     620       401   000 000     557Pine       520   000 330     321       000   2: Utility     the       sensitivity   has been     applying       7%)   these attributes     the       once   Table 3     results       Weights16   7%16 7%16     7%100%LocationTraffic       /   Lease &     Size       thousands)Parking   (maximum #     parking)InsuranceCosts($000/       evaluation)Total   Rock1 000     380       000   300 620     290Daisy0       000   000 495Pine     740       330   700 321     000       Sensitivity   with similar     this       Table   Little Rock     highest       locations   Traffic Count     of       a   weightage As     3,       score   equal weightage     while       next   2nd position     round       carried   where Traffic     is       weightage,   all the     attributes       equal   The rationale     a       Traffic   is due     fact       a   potential customer     footfall,       impact   business by     getting       this   (reflected in     below),       again   the highest     to       Count   thousands /     &