Module 1 - SLP
Assumed Certainty: Pivot Tables and Multi-Attribute Decision Making
Scenario: You are the VP of Franchise services for the Happy Buns Restaurant. You have been assigned the task of evaluation the best location for the next HB that a prospective franchisee has suggested in the Columbus, Ohio, area. You are using the standard template that provides for which criteria (attributes) you should evaluate. But the specific weights for these are open to adjustment depending on the specific area. These are the six criteria that you will use to evaluate this decision.
Close to drive through traffic – traffic counts (avg. thousands/day)
Property cost/investment and taxes = NPV of investment ($$)
Size of building (square feet in thousands)
Size of parking (max number of customers parking)
Insurance costs (thousands $ per year)
Ease of access from streets (subjective evaluation from observation)
There are five possible locations. You have collected the data from various sources including your VP Finance, Real estate agents, etc. This document summarizes the raw data for each of the five locations: Abberton, Bellview, Casstown, Denton, and Eddington, all suburbs of Columbus. See Data Below.
Review the information and data regarding the different alternatives for restaurant location. Develop a MADM table with the raw data. Convert the raw data to utilities (scaled on 0 to 1). Determine the relative weights of each criteria. Evaluate the Decision Table for the best alternative. Do a sensitivity analysis.
Write a report to your boss, Executive VP. Explain your analysis and your recommendation. Provide a rationale for your decision including the logic you used to determine your weights.
Download this Word doc with the data: Happy Buns Raw Data.docxUpload both your written report and Excel file to the SLP 1 Dropbox.
SLP Assignment Expectations
Accurate, complete analysis (in Excel and Word) using the MADM model and theory.
Length requirements = 2–3 pages minimum (not including Cover and Reference pages)
Provide a brief introduction/ background of the problem.
Complete and accurate Excel analysis.
Written analysis that supports Excel analysis, and provides thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).