Crusty Pizza Company: Forecasting with Regression

Crusty Pizza Company: Forecasting With Regression

Crusty Pizza Company has 60 restaurants ranging from very large to small, and is considering opening 20 new restaurants. Of the new potential restaurants, there are 10 very large, 4 large, 3 medium, and 3 small stores. According to the previous data collected (available upon request), the very large stores make up 45% of the total store sizes and have the highest profits, $573,710.36, of all the stores. The company already has eighteen large restaurants and is planning to add 4 more to the count. The company’s existing large restaurants currently have the second largest overall profits of $261,079.11. The medium stores’ monthly profits were $127,485.87, and the small stores’ profits were $11,611.48.

In determining which stores, if not all, Crusty Pizza should open, the data of their 60 stores was broken down by store size and analyzed. The main variables to be considered are advertising expenses, competitors with in a 15 miles radius, parking spots, pizza varieties, and student population in relation to monthly profits.

Before analyzing the restaurants by size, we found that there are a few variables that affect monthly profits overall. There appears to be fairly strong positive linear relationship (.815) between the amount spent on advertising and the monthly profits among the 60 Crusty Pizza restaurants. When advertising expenses increase, so do the monthly overall profits. With advertising expenses accounting for 66.4% of the total variation in overall monthly profits, there is a strong relationship between the two variables. Among all restaurant sizes, there are positive linear relationships between student population (.598), the number of parking spots (.451), and population within 20 miles (.083) and monthly profits. There is a negative linear relationship of .070 between the number of competitors within 15 miles and monthly profits. The number of pizza varieties each restaurant offers has a very minimal positive linear relationship (.003) to monthly profits.

Small Restaurants

Our analyzing and forecasting of the restaurant sizes will begin with the small restaurants. Performing a linear regression test on the company’s previous data shows that there is a strong negative linear relationship of -.916 between the amount of monthly advertising and monthly profits. Every time the small restaurants have an advertisement expense, there is a steady decrease in their profits. This can be concerning because about 83.4% of the total variation in the small restaurant’s profits can be explained by advertising.

The linear regression also shows a moderate relationship of .59 between the amounts of competitors it has within 15 miles. All three of the projected small restaurants have less than 10 competitors within 15 miles. According to the regression, all small stores are expected