Store24 Case R2
Date: 12/04/2014
From: Jason Chambers, Joost Rietdijk, Barry Dunham
To: Bob Gordon CEO, and Paul Doucette CFO
Subject: Store 24
Store 24 Case
Introduction:
Store 24 is a convenience store located in the New England area. They are currently operating in a highly competitive market and as a result are in need of further differentiation. The old differentiation method was called “Cause You Just Can’t Wait” (CYJCW) which focused on customer convenience with regards to locating products and getting in and out of the store quickly. The newest differentiation strategy is dubbed “Ban Boredom” and is tailored towards whom they believe is their current target market, urban youth and young adults aged 14 – 29. They feel this group is bored easily and that ensuring that their customers are entertained while at the store will be a beneficial differentiation strategy. Senior leadership wants to know if the Ban Boredom initiative is a good determinant of store financial performance.
Statistical Analyses
For the Store 24 case a dataset of 30 convenience stores was given. For each of these stores a future controllable contribution was given which is the margin less controllable expenses one period into the future, in this case the period ending April 2000. The data for the stores are from a previous period ending January 2000. It is expected that the data from the period be utilized via a multivariate of regression analysis to predict the stores Future Controllable Contribution (hereinafter “profit”).
Univariate Analysis
Figure 1 To start the analysis we loaded the dataset and observed some descriptive statistics to better understand the basics of the dataset. From the descriptive statistics (Appendix A), we learn that the average of profit for each store is about $32,554 and the standard deviation is $11,580; this would imply that the difference in profit between the stores profit is quite large. Figure 1 above illustrates the store’s profit in a graph. It
From: Jason Chambers, Joost Rietdijk, Barry Dunham
To: Bob Gordon CEO, and Paul Doucette CFO
Subject: Store 24
Store 24 Case
Introduction:
Store 24 is a convenience store located in the New England area. They are currently operating in a highly competitive market and as a result are in need of further differentiation. The old differentiation method was called “Cause You Just Can’t Wait” (CYJCW) which focused on customer convenience with regards to locating products and getting in and out of the store quickly. The newest differentiation strategy is dubbed “Ban Boredom” and is tailored towards whom they believe is their current target market, urban youth and young adults aged 14 – 29. They feel this group is bored easily and that ensuring that their customers are entertained while at the store will be a beneficial differentiation strategy. Senior leadership wants to know if the Ban Boredom initiative is a good determinant of store financial performance.
Statistical Analyses
For the Store 24 case a dataset of 30 convenience stores was given. For each of these stores a future controllable contribution was given which is the margin less controllable expenses one period into the future, in this case the period ending April 2000. The data for the stores are from a previous period ending January 2000. It is expected that the data from the period be utilized via a multivariate of regression analysis to predict the stores Future Controllable Contribution (hereinafter “profit”).
Univariate Analysis
Figure 1 To start the analysis we loaded the dataset and observed some descriptive statistics to better understand the basics of the dataset. From the descriptive statistics (Appendix A), we learn that the average of profit for each store is about $32,554 and the standard deviation is $11,580; this would imply that the difference in profit between the stores profit is quite large. Figure 1 above illustrates the store’s profit in a graph. It