Benchmark assignment – data analysis case study

Benchmark Assignment – Data Analysis Case Study
The Cicero Italian Restaurant was founded by Anthony Tanaglia in 1947 in Cicero, Illinois, a
suburb of Chicago. He built the business with his family from a small pizza and pasta restaurant
to 10 locations in the Chicago area. Michael Tanaglia, Anthony’s grandson, moved to Arizona to
escape the cold Chicago winters and opened a restaurant in the Chandler area. The Arizona
restaurant gained momentum thanks to the Chicago-style pizza and quality Italian dishes.
Anthony decided to expand operations in Arizona, adding a second location in Glendale. The
Glendale location was managed by Michael’s son Tony.
After a year of operations, Michael had some concerns with the Glendale location. Michael does
not want his family’s business to fail, and he wants his grandfather’s legacy to last. Michael also
understands how important an operational evaluation can be to identifying the strengths and
weaknesses of a business. Michael confides his concerns to you and asks if you will do him a
favor and use your quantitative analytic expertise to help him evaluate the Glendale location’s
operations in three key areas: customer satisfaction, customer forecasting, and staff scheduling.
As his friend, you agree – though his offer to treat you to the large pizza of your choice did not
First Evaluation
The first evaluation required an understanding of the factors that contribute to customer
satisfaction and spending. Refer to the data Michael provided in the Excel spreadsheet
“Benchmark Assignment – Data Analysis Case Study Data.” Identify which variables are
significant to predicting overall satisfaction. Develop and interpret the prediction equation and
the coefficient of determination. Based upon the data in this evaluation, what areas should
Michael and Tony Tanaglia focus on to improve customer satisfaction?
Second Evaluation
The second evaluation requires a forecast of customers based upon demand. Michael reviewed
data for the previous 11 months in an attempt to better forecast restaurant customer volume.

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