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

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Question Description

Review "Benchmark Assignment - Data Analysis Case Study" (ATTACHED)and "Benchmark Assignment - Data Analysis Case Study Data" (ATTACHED)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 required to use the "Benchmark Assignment - Data Analysis Case Study Template" (ATTACHED)and "Benchmark Assignment - Data Analysis Case Study Linear Programming Template"(ATTACHED)

to complete this assignment (Use the provided template( please do not modify template) to complete assignment).

Prepare the assignment according to the guidelines found in the APA Style Guide.

This assignment uses a rubric (ATTACHED). Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. All sections of rubric must be included in the answer.

This assignment required to submit this assignment to Turnitin so please make sure to so assignment accordingly

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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 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 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 - Data Analysis Case Study 2 1 Less than Unsatisfactory Satisfactory 0.00% 74.00% 70.0 %Content 10.0 %Variables The for Predicting identification Satisfaction of variables for predicting satisfaction is not included or is incomprehensi ble. 3 Satisfactory 79.00% 4 Good 87.00% 5 Excellent 100.00% The The The The identification identification identification identification of variables for of variables for of variables for of variables for predicting predicting predicting predicting satisfaction is satisfaction is satisfaction is satisfaction is included, but present and clearly thoroughly lacks detail or reasonable. provided and developed is incomplete. wellwith developed. supporting details. 10.0 %Prediction The The The The The Equation and development development development development development Coefficient of and and and and and Determination interpretation interpretation interpretation interpretation interpretation (Benchmark prediction prediction prediction prediction prediction Competency 2.3) equation and equation and equation and equation and equation and coefficient of coefficient of coefficient of coefficient of coefficient of determination determination determination determination determination are not are included, are are wellare thoroughly included or are but lack detail appropriate. developed. developed incomprehensi or are with ble. incomplete. supporting details. 15.0 %Areas of Recommended Recommended Recommended Recommended Recommended Focus to Improve areas of focus areas of focus areas of focus areas of focus areas of focus Customer to improve to improve to improve to improve to improve Satisfaction customer customer customer customer customer satisfaction are satisfaction are satisfaction are satisfaction are satisfaction are not included or included, but adequate. appropriate rational and are illogical. lack detail or and wellthoroughly are developed. developed incomplete. with supporting details. 15.0 The The The The The %Recommended recommended recommended recommended recommended recommended Method and method to yield method to method to method to method to December the lowest error yield the yield the yield the yield the Forecast and the lowest error lowest error lowest error lowest error December and the and the and the and the forecast are not December December December December included or are forecast are forecast are forecast are forecast are incomprehensi included, but relevant. appropriate. purposeful and ble. lack detail or clever. are incomplete. 15.0 The The The The The %Recommendati recommendatio recommendati recommendati recommendati recommendati ons of Staff for ns of staff for ons of staff for ons of staff for ons of staff for ons of staff for Each Shift each shift to each shift to each shift to each shift to each shift to accommodate accommodate accommodate accommodate accommodate the minimum the minimum the minimum the minimum the minimum requirements requirements requirements requirements requirements for customer for customer for customer for customer for customer service are not service are service are service are service are included. illogical or fairly appropriate. smartly incomplete. reasonable. chosen. 5.0 %Excel The Excel The Excel The Excel The Excel The Excel Spreadsheet spreadsheet is spreadsheet is spreadsheet is spreadsheet is spreadsheet is not included. incomplete. understandable accurate. accurate and . appropriately organized. 20.0 %Organization and Effectiveness 7.0 %Thesis Paper lacks any Thesis is Thesis is Thesis is clear Thesis is Development and discernible insufficiently apparent and and forecasts comprehensive Purpose overall purpose developed or appropriate to the and contains or organizing vague. Purpose purpose. development the essence of claim. is not clear. of the paper. the paper. Thesis is Thesis descriptive and statement reflective of makes the the arguments purpose of the and paper clear. appropriate to the purpose. 8.0 %Argument Statement of Sufficient Argument is Argument Clear and Logic and purpose is not justification of orderly, but shows logical convincing Construction justified by the claims is may have a progressions. argument that conclusion. lacking. few Techniques of presents a The conclusion Argument inconsistencies argumentation persuasive does not lacks . The argument are evident. claim in a support the consistent presents There is a distinctive and claim made. unity. There minimal smooth compelling Argument is are obvious justification of progression of manner. All incoherent and uses noncredible sources. flaws in the logic. Some sources have questionable credibility. claims. claims from sources are Argument introduction to authoritative. logically, but conclusion. not Most sources thoroughly, are supports the authoritative. purpose. Sources used are credible. Introduction and conclusion bracket the thesis. 5.0 %Mechanics Surface errors Frequent and Some Prose is Writer is of Writing are pervasive repetitive mechanical largely free of clearly in (includes spelling, enough that mechanical errors or typos mechanical command of punctuation, they impede errors distract are present, errors, standard, grammar, communication the reader. but they are although a few written, language use) of meaning. Inconsistencies not overly may be academic Inappropriate in language distracting to present. The English. word choice or choice the reader. writer uses a sentence (register) or Correct and variety of construction is word choice varied effective used. are present. sentence sentence Sentence structure and structures and structure is audiencefigures of correct but not appropriate speech. varied. language are employed. 10.0 %Format 5.0 %Paper Template is not Appropriate Appropriate Appropriate All format Format (use of used template is template is template is elements are appropriate style appropriately used, but some used. fully used. correct. for the major and or elements are Formatting is There are assignment) documentation missing or correct, virtually no format is rarely mistaken. A although some errors in followed lack of control minor errors formatting correctly. with may be style. formatting is present. apparent. 5.0 Sources are not Documentatio Sources are Sources are Sources are %Documentation documented. n of sources is documented, documented, completely of Sources inconsistent or as appropriate as appropriate and correctly (citations, incorrect, as to assignment to assignment documented, footnotes, appropriate to and style, and style, and as appropriate references, assignment although some to assignment bibliography, etc., as appropriate to assignment and style) 100 %Total Weightage and style, with formatting format is and style, and numerous errors may be mostly correct. format is free formatting present. of error. errors. ...
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Tutor Answer

whgrab
School: Rice University

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Running head: BENCHMARKING

1

Benchmarking assignment
Instructor name
Submitted by
Date

BENCHMARKING

2

It is concerned with staff scheduling, the data provided total five shifts starting from morning 11
am to midnight. The required number of staff as stated are 3, 4, 6, 7, and 4 for shift 1, shift 2,
shift 3, shift 4, and shift 5 respectively. With this, there are some complaints coming up from the
customers about the slow service. The method to know the right number of staff for each shift is
linear programming. The owner must work to reduce the cost of the restaurant. The total
availability of staff for all the shifts is 15. However, the results obtained in the solver depicts the
same results But as per my observation of the entire scenario, I can say that shift 1 requires not
more than 2 employees because the opening time of restaurant is 11 a.m. Two employees are
enough to manage the entire area, as the customers during opening hours are also very less. For
shift 2, it should be 3 because this is the time when the customers start visiting for lunch. The
customers during the shift 2 are mainly businessman who has a meeting with their clients, the
employees of the nearby area who wish to have lunch outside, or the college going students who
plans for the parties outside their college premises. For shift 3, the number of staff should be 4
because these are the hours when the office hour finishes and people plan for dinner outside.
During shift 4, the requirement of staff should be 4, as the shift finishes at 10:00 p.m. This is the
time when people stay out of their home to enjoy outside with friends or fa...

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Anonymous
Tutor went the extra mile to help me with this essay. Citations were a bit shaky but I appreciated how well he handled APA styles and how ok he was to change them even though I didnt specify. Got a B+ which is believable and acceptable.

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