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

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”

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

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

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

GSS Question Dimensions Restaurant Environment Atmosphere Cleanliness Comfort Restrooms

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

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

GSS Question Dimensions Compare to Similar Restaurant Overall Atmosphere Food Service

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

Crosstabs Find correlation between comfort and other variables The best Pearson’s r value found is 0.620 for correlation of comfort and overall experience Second best Pearson’s r value is 0.605 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

Comfort & Overall Experience

Comfort & Cleanliness

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

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

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

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

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

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

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

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

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

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

Questions? Comments?