Benchmark - Data Analysis Case Study, business and finance homework help

Anonymous
timer Asked: Jul 26th, 2017
account_balance_wallet $45

Question Description

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 Turnitin. Please refer to the directions in the Student Success Center.

____________________________________________________________________________________________________________________

Unsatisfactory
0.00%

2
Less than Satisfactory
74.00%

3
Satisfactory
79.00%

4
Good
87.00%

5
Excellent
100.00%

70.0 %Content

10.0 %Variables for Predicting Satisfaction

The identification of variables for predicting satisfaction is not included or is incomprehensible.

The identification of variables for predicting satisfaction is included, but lacks detail or is incomplete.

The identification of variables for predicting satisfaction is present and reasonable.

The identification of variables for predicting satisfaction is clearly provided and well-developed.

The identification of variables for predicting satisfaction is thoroughly developed with supporting details.

10.0 %Prediction Equation and Coefficient of Determination (Benchmark Competency 2.3)

The development and interpretation prediction equation and coefficient of determination are not included or are incomprehensible.

The development and interpretation prediction equation and coefficient of determination are included, but lack detail or are incomplete.

The development and interpretation prediction equation and coefficient of determination are appropriate.

The development and interpretation prediction equation and coefficient of determination are well-developed.

The development and interpretation prediction equation and coefficient of determination are thoroughly developed with supporting details.

15.0 %Areas of Focus to Improve Customer Satisfaction

Recommended areas of focus to improve customer satisfaction are not included or are illogical.

Recommended areas of focus to improve customer satisfaction are included, but lack detail or are incomplete.

Recommended areas of focus to improve customer satisfaction are adequate.

Recommended areas of focus to improve customer satisfaction are appropriate and well-developed.

Recommended areas of focus to improve customer satisfaction are rational and thoroughly developed with supporting details.

15.0 %Recommended Method and December Forecast

The recommended method to yield the lowest error and the December forecast are not included or are incomprehensible.

The recommended method to yield the lowest error and the December forecast are included, but lack detail or are incomplete.

The recommended method to yield the lowest error and the December forecast are relevant.

The recommended method to yield the lowest error and the December forecast are appropriate.

The recommended method to yield the lowest error and the December forecast are purposeful and clever.

15.0 %Recommendations of Staff for Each Shift

The recommendations of staff for each shift to accommodate the minimum requirements for customer service are not included.

The recommendations of staff for each shift to accommodate the minimum requirements for customer service are illogical or incomplete.

The recommendations of staff for each shift to accommodate the minimum requirements for customer service are fairly reasonable.

The recommendations of staff for each shift to accommodate the minimum requirements for customer service are appropriate.

The recommendations of staff for each shift to accommodate the minimum requirements for customer service are smartly chosen.

5.0 %Excel Spreadsheet

The Excel spreadsheet is not included.

The Excel spreadsheet is incomplete.

The Excel spreadsheet is understandable.

The Excel spreadsheet is accurate.

The Excel spreadsheet is accurate and appropriately organized.

20.0 %Organization and Effectiveness

7.0 %Thesis Development and Purpose

Paper lacks any discernible overall purpose or organizing claim.

Thesis is insufficiently developed or vague. Purpose is not clear.

Thesis is apparent and appropriate to purpose.

Thesis is clear and forecasts the development of the paper. Thesis is descriptive and reflective of the arguments and appropriate to the purpose.

Thesis is comprehensive and contains the essence of the paper. Thesis statement makes the purpose of the paper clear.

8.0 %Argument Logic and Construction

Statement of purpose is not justified by the conclusion. The conclusion does not support the claim made. Argument is incoherent and uses noncredible sources.

Sufficient justification of claims is lacking. Argument lacks consistent unity. There are obvious flaws in the logic. Some sources have questionable credibility.

Argument is orderly, but may have a few inconsistencies. The argument presents minimal justification of claims. Argument logically, but not thoroughly, supports the purpose. Sources used are credible. Introduction and conclusion bracket the thesis.

Argument shows logical progressions. Techniques of argumentation are evident. There is a smooth progression of claims from introduction to conclusion. Most sources are authoritative.

Clear and convincing argument that presents a persuasive claim in a distinctive and compelling manner. All sources are authoritative.

5.0 %Mechanics of Writing (includes spelling, punctuation, grammar, language use)

Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used.

Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied.

Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed.

Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech.

Writer is clearly in command of standard, written, academic English.

10.0 %Format

5.0 %Paper Format (use of appropriate style for the major and assignment)

Template is not used appropriately or documentation format is rarely followed correctly.

Appropriate template is used, but some elements are missing or mistaken. A lack of control with formatting is apparent.

Appropriate template is used. Formatting is correct, although some minor errors may be present.

Appropriate template is fully used. There are virtually no errors in formatting style.

All format elements are correct.

5.0 %Documentation of Sources (citations, footnotes, references, bibliography, etc., as appropriate to assignment and style)

Sources are not documented.

Documentation of sources is inconsistent or incorrect, as appropriate to assignment and style, with numerous formatting errors.

Sources are documented, as appropriate to assignment and style, although some formatting errors may be present.

Sources are documented, as appropriate to assignment and style, and format is mostly correct.

Sources are completely and correctly documented, as appropriate to assignment and style, and format is free of error.

100 %Total Weightage

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
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
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 © 2017. 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
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

Tutor Answer

Robert__F
School: Duke University

I am w...

flag Report DMCA
Review

Anonymous
Top quality work from this guy! I'll be back!

Similar Questions
Hot Questions
Related Tags
Study Guides

Brown University





1271 Tutors

California Institute of Technology




2131 Tutors

Carnegie Mellon University




982 Tutors

Columbia University





1256 Tutors

Dartmouth University





2113 Tutors

Emory University





2279 Tutors

Harvard University





599 Tutors

Massachusetts Institute of Technology



2319 Tutors

New York University





1645 Tutors

Notre Dam University





1911 Tutors

Oklahoma University





2122 Tutors

Pennsylvania State University





932 Tutors

Princeton University





1211 Tutors

Stanford University





983 Tutors

University of California





1282 Tutors

Oxford University





123 Tutors

Yale University





2325 Tutors