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Analysis of Statistical Trends Between Design and Comfort at Chili’s Restaurant

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

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Analysis of Statistical Trends Between Design and Comfort at Chili’s Restaurant

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  1. 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 DimensionsRestaurant Environment • Atmosphere • Cleanliness • Comfort • Restrooms

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

  8. GSS Question DimensionsStaff • Food served timely • Enthusiasm • Promptness of payment • Servers knowledge

  9. GSS Question DimensionsCompare 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 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

  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

  15. Food served timely 5.A SP 7.X 8.X 5.AX 6.X 8.M

  16. Comfort SP 5.A 7.X 8.X 5.AX 6.X 8.M

  17. Atmosphere SP 5.A 7.X 8.X 5.AX 6.X 8.M

  18. Compare to similar overall SP 5.A 7.X 8.X 5.AX 6.X 8.M

  19. Overall 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?

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