LP_min
Linear, Integer and Mixed Integer Programming
Signs
<
=
>
less than or equal to
equals (You need to enter an apostrophe first.)
greater than or equal to
Data
x1
Minimize
10 AM-1 PM
1:00 PM - 4:00 PM
4:00 PM- 7:00 PM
7:00 PM- 10:00 PM
10:00 PM- 1:00 AM
Results
Variables
Objective
x2
1
0
x3
1
x4
1
x5
1
1 sign
>
>
>
>
>
RHS
3
4
6
7
4
0
0
Page 1
LP_min
Results
LHS
Problem setup area
Slack/Surplus
0
0
0
0
0
0
3
4
6
7
4
< constraints
0
0
0
0
0
0
0
0
0
0
> constraints
0
0
0
0
0
Page 2
3
4
6
7
4
Forecasting
Moving averages - 4 period moving average
Data
Period
Period 1
Period 2
Period 3
Period 4
Period 5
Period 6
Period 7
Period 8
Period 9
Period 10
Period 11
Next period
4
Demand
Forecasts and Error Analysis
Forecast Error
Absolute
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
Total
Average
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
Bias
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
MAD
SE
Squared
Abs Pct Err
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
MSE
MAPE
1
#DIV/0!
0,9
Not enough data to compute the standard error
0,8
0,7
Value
Num pds
0,6
0,5
0,4
0,3
0,2
0,1
0
1
Forecasting
1
0,9
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
1
2
3
4
5
6
7
Time
Demand
Forecast
8
9
10
11
Forecasting
Data
Period
Period 1
Period 2
Period 3
Period 4
Period 5
Period 6
Period 7
Period 8
Period 9
Period 10
Period 11
Weighted moving averages - 2 period moving average
Demand
Weights
0,15
0,3
Forecasts and Error Analysis
Forecast Error
Absolute
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Total
Average
Bias
Next period
0
Squared
0
0
0
0
0
0
0
0
0
0
0
MAD
SE
Abs Pct Err
0
0
0
0
0
0
0
0
0
0
0
MSE
0
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
MAPE
Forecasting
1
0,9
0,8
Value
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
1
2
3
4
5
6
7
Time
Demand
Forecast
8
9
10
11
Forecasting
Next period
0,05
Forecasts and Error Analysis
Forecast Error
Absolute Squared
Abs Pct Err
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
0
0
0
0 #DIV/0!
Total
0
0
0 #DIV/0!
Average
0
0
0 #DIV/0!
Bias
MAD
MSE
MAPE
SE
0
Demand
1
0,9
0
0,8
0,7
Value
Alpha
Data
Period
Period 1
Period 2
Period 3
Period 4
Period 5
Period 6
Period 7
Period 8
Period 9
Period 10
Period 11
Exponential smoothing
0,6
0,5
0,4
0,3
0,2
0,1
0
1
Forecasting
1
0,9
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
1
2
3
4
5
6
Time
0
7
8
9
10
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
hurt.
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.
MONTH
January
February
March
April
May
June
July
August
September
October
# OF CUSTOMERS
650
725
850
825
865
915
900
930
950
899
© 2019. Grand Canyon University. All Rights Reserved.
November
December
935
?
Which method should the business owner use to yield the lowest amount of error and what
would be the forecast for December? Refer to the Excel spreadsheet “Benchmark Assignment Data Analysis Case Study Template.”
Third Evaluation
The third evaluation concerns staff scheduling. Some of the customers have complained that
service is slow. The restaurant is open from 11:00 a.m. to midnight every day of the week. Tony
divided the workday into five shifts. The table below shows the minimum number of workers
needed during the five shifts of time into which the workday is divided.
Shift
1
2
3
4
5
Time
10:00 a.m. – 1:00 p.m.
1:00 p.m. – 4:00 p.m.
4:00 p.m. – 7:00 p.m.
7:00 p.m. – 10:00 p.m.
10:00 p.m. – 1:00 a.m.
# of Staff
Required
3
4
6
7
4
The owners must find the right number of staff to report at each start time to ensure that there is
sufficient coverage. The organization is trying to keep costs low and balance the number of staff
with the size of the restaurant, so the total number of workers is constrained to 15.
Based on these factors, recommend the staff for each shift to accommodate the minimum
requirements for customer service. Refer to the Excel spreadsheet “Benchmark Assignment Data Analysis Case Study Linear Programming Template.”
2
Dine In (1)/Take Out (2)
1
1
1
1
2
2
2
1
2
1
2
2
1
1
1
1
1
2
2
1
2
1
2
2
1
2
2
1
2
1
2
2
1
2
2
1
1
1
2
2
1
2
2
1
2
1
Satisfaction with Service Satisfaction with Food
4
2
3
5
3
2
3
4
3
2
1
2
5
4
4
3
4
3
3
4
4
2
3
3
3
4
3
4
3
4
2
2
4
3
3
3
3
4
3
3
4
3
2
3
4
2
Overall Satisfaction
4
3
3
5
4
4
4
3
3
3
3
2
4
5
5
4
3
4
4
5
5
3
5
4
4
5
3
4
4
5
3
2
4
2
3
3
3
5
3
4
4
3
3
3
4
3
4
3
3
5
3
3
3
3
3
2
2
2
4
4
4
3
4
3
3
4
4
3
4
3
3
4
3
4
4
4
2
2
4
3
3
3
3
4
3
3
4
3
2
3
4
2
2
1
1
4
4
5
5
5
5
4
4
5
Driving Distance to Restaurant
5
5
10
12
10
15
10
16
2
10
15
10
12
16
18
20
18
20
16
7
9
10
6
10
9
8
10
6
10
10
15
16
18
16
14
20
16
17
16
5
10
6
10
6
7
6
Total Bill
10
15
10
15
25
25
26
27
25
26
20
20
20
20
20
27
28
28
28
12
20
24
26
28
27
24
22
23
25
20
20
20
20
20
25
22
23
28
23
15
28
24
27
26
28
24
8
6
8
22
23
20
Review "Benchmark Assignment - Data Analysis Case Study" and "Benchmark Assignment - Data Analysis Case Study Data" for this topic's case study,
evaluating operations for a local restaurant.
Although your friend and restauranteur Michael Tanaglia offered to go over your findings in person, you believe it would be appropriate to also prepare
a report and document your findings in writing. In a 1,000-1,250-word report, explain your approach for each evaluation and the rationale for the
methods you used. Include any recommendations based on customer satisfaction, forecasting, and staff scheduling data.
Use an Excel spreadsheet file for the calculations and explanations. Cells should contain the formulas (i.e., if a formula was used to calculate the entry
in that cell). Students are highly encouraged to use the "Benchmark Assignment - Data Analysis Case Study Template" and "Benchmark Assignment - Data
Analysis Case Study Linear Programming Template" to complete this assignment.
Mac users can use StatPlus:mac LE, free of charge, from AnalystSoft.
Prepare the assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful
completion.
You are required to submit this assignment to LopesWrite. Please refer to the directions in the Student Success Center.
Attachments
BUS-660-RS-T7BenchmarkDataAnalysisCaseStudy Template.xlsx
BUS-660-RS-T7BenchmarkDataAnalysis Case Study.docx
BUS-660-RS-T7BenchmarkData AnalysisCase StudyData.xlsx
BUS-660-RS-T7BenchmarkDataAnalysis Case StudyLinear Programming Template.xlsx
Attempt Start Date: 11-Jul-2019 at 12:00:00 AM
RUBRIC
Due Date: 17-Jul-2019 at 11:59:59 PM
Maximum Points: 110.0
Purchase answer to see full
attachment