Crusty Dough Pizza Company – Maximizing Monthly Profits
Introduction
This paper provides a summary of our analysis of the data obtained for 60 Crusty Dough Pizza Company restaurants. We compared 16 pizza store characteristics to monthly profit in order to determine the best indicators of success. The results of this analysis may be used to determine the store services and attributes that have the most bearing on profitably.
In our analysis, we compared the profits earned by 60 Crusty Dough Pizza Company restaurants to factors associated to their menu, amenities, services, and statistics regarding the restaurant communities. The factors that we analyzed are listed in Table 1.
Table 1. List of Factors
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The coefficient of variation is in the “fair” range for data consistency, for all quartiles except the top quartile which is in the “good” range. (Gardner, 2012)
Table 4. Store Profitability Compared by Store Size
Factor 3. Student Population and Profit.
Through analysis of the mean and median values for student populations near store locations, we determined that student population is a significant factor in determining pizza restaurant profitability (Table 5.). On average, the larger the student population near Crusty stores, the more potential there is for earning higher monthly profit. When sorted by amount of monthly profit, the highest earning stores have student populations that are, on average, nearly twice as large as the populations by the lowest earning stores. Data consistency is in question for all quartiles for this factor , except the top quartile which is in the “good” consistency range. (Gardner, 2012).
Table 5. Store Profitability Compared by Student Population
Factor 4. Delivery and Profit.
In order to analyze the delivery factor, we divided the stores into those that had the service and those that did not. We then compared the profitability of the stores with and without delivery service (Table 6.) On average, the stores with delivery earned more profit than stores without delivery – this is true whether making comparisons using the means or medians for profit. There is
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The coefficient of variation (CV) represents a percentage of standard deviation to the mean and can be calculated by dividing the standard deviation calculated using Equation 2 by the expected value. The equation can be calculated by:
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