1. Asif Hussain Kristyn Starr
Analysis of Statistical Trends Between Design and Comfort at Chili’s Restaurant
Asif Hussain
Kristyn Starr

2. Intro To Brinker
Brinker International has 5 divisions of restaurants ranging from casual dining to fine dining
3.7 billion dollar company
Recognized by FORTUNE magazine as one of “America’s most admired companies”

3. Chili’s Grill & Bar
Has an eclectic menu and casual friendly atmosphere
49 states and 23 countries
Recently opened its 1000th restaurant

4. Task At Hand
Does the architecture (prototype) of Chili’s influence a guest’s comfort?
Find trends in data to answer question
Give recommendations for changes to be made at Chili’s

5. Data Source Guest Satisfaction Survey (GSS)
Guests receive survey information on receipt
Chance to win $25,000
About 2 million cases

6. GSS Question Dimensions Restaurant Environment
Atmosphere
Cleanliness
Comfort
Restrooms

7. GSS Question Dimensions Staff
Welcomed upon arrival
Acknowledged quickly upon being seated
Attentiveness of server
Beverage served timely

8. GSS Question Dimensions Staff
Food served timely
Enthusiasm
Promptness of payment
Servers knowledge

9. GSS Question Dimensions Compare to Similar Restaurant
Overall
Atmosphere
Food
Service

10. Software Used SPSS Statistical analysis software
User friendly graphical interface
Compatible with Brinker software

11. Crosstabs Find correlation between comfort and other variables
The best Pearson’s r value found is for correlation of comfort and overall experience
Second best Pearson’s r value is for comfort and cleanliness
Due to lots of data and significance=0 this r value shows a correlation
Make sure you tell what Pearson’s r is

12. Comfort & Overall Experience

13. Comfort & Cleanliness

14. One-Way ANOVA
Compare means of variables using prototype as factor to find significance of differences
Full analysis was done on 19 variables
19 variables listed earlier
17 prototypes

15. Food served timely Prototypes 6 and 8.X did well
Protype 11 did poor in comparision
You will notice in most the graphs there are prototypes better than others but if you look at the values you see it is a small gap. Here for example there is only a max difference of about 0.2
The blue line has no mathematical or numerical value. It was chosen to offset the top 2-3 points and the bottom 2-3 that were significantly different than most
5.A SP
7.X
8.X
5.AX
6.X
8.M

16. Comfort
GOOD 8 9 10 12
7.X
BAD 11
5.A SP
5.A
7.X
8.X
5.AX
6.X
8.M

17. Atmosphere
GOOD 8 9 10 12 14
8.M
BAD 11 SP
5.A
7.X
8.X
5.AX
6.X
8.M

18. Compare to similar overall
GOOD 8 9 12 14
8.X
BAD 11
7.X SP
5.A
7.X
8.X
5.AX
6.X
8.M

19. Overall
GOOD 9 12
BAD 11 SP
5.A
7.X
8.X
8.M
5.AX
6.X

20. Conclusion Prototype 14 consistently scored higher than the rest
Changed exterior and interior
Newer look : Stone and perforated metal exterior accents; cook-off/ event pictures, toys and cars spotlighted inside
7 stores and 4078 entries

21. Conclusion Prototype 11 and 7.X consistently scored low
11 only has one restaurant
7.X is expanded 7; once again only a few
7.X may have scored low because of location and not prototype

22. Suggestion
It appears that the prototype does not affect the comfort much
Benchmarks may help to better separate the strong and weak prototypes
Look at top 2 boxes of ratings instead of means

23. Suggestion
With minor adjustments to staff, air, and table spacing comfort levels could improve
More detailed questions on GSS or focus group may offer more insight

24. Questions?
Comments?