MANAGERIAL DECISION MAKING–BUSINESS FORECASTING INDIVIDUAL COURSEWORK
In April 2010, Mitchell Grant purchased JavaJobe, a company that manufactures and sells luxury coffee machines. In April 2013 JavaJobe expanded their product offering to making coffee capsules to fit into pod-style coffee machines. Sales data (in number of units sold) for each product is available on JavaJobe Data.xlsx; six years of quarterly data for the coffee machines and three years of monthly data for the capsules. Mitchell Grant has asked you to analyse the sales data by addressing the tasks listed below. From a retail perspective, he is concerned about falling and/or stagnant sales levels. From an operational perspective, he is aware that space is at a premium and is concerned about storage costs associated with excess supply.
WHAT YOU ARE REQUIRED TO DO:
Write up your answers to the tasks below using the JavaJobe Data and submit your quantitative analysis on a supporting spreadsheet. The aim of this assignment is to model and analyse the JavaJobe data appropriately and interpret your output to provide recommendations to Mitchell Grant on how to manage his business going forward.
Coffee Capsule Data
Task 1:
Carry out diagnostic analysis on the coffee capsule data to determine what time series components the data exhibits, if any. Remember to present a body of evidence to support your conclusions.
Task 2:
Build a single forecast model using the mean as the estimator. Next, apply the following updating schemes, making sure you justify any values that you introduce as the decision maker (eg: k, weights, alpha). Generate a forecast for next month for each scheme and include this in your report.
• Naïve Forecasting
• Updating the Mean
• Moving average of length k
• Weighted Moving Average of length k OR Simple Exponential Smoothing
Task 3:
Fully evaluate each updating scheme used in task 2 using statistical and graphical analysis and any other information you feel is appropriate to recommend which one updating model should be used to forecast next month’s sales value. In your discussion make sure you explain why you have selected your chosen scheme over the other methods.
Coffee Machine Data
Task 4: Build an appropriate model to forecast the coffee machine data by diagnosing which time series components you think are present in the data and modelling them clearly. Forecast the number of coffee machines you predict JavaJobe will sell next quarter.
Task 5: Fully evaluate your model in task 4 and discuss any factors that the manager should consider when forecasting this type of data.
JavaJobe Sales Data
Task 6: Given your analysis of JavaJobe’s historical sales data for both the coffee machines and capsules, what factors should Mitchell Grant consider for the future?
MARKING CRITERIA
The marking criteria guidelines are published in advance so you know how you will be judged for this piece of work and are available on Studyspace.
HOW YOUR WORK SHOULD BE PRESENTED AND SUBMITTED
You need to submit two files for this piece of coursework:
1. Written Report
You are required to submit a written report with a word limit of 1250 words. Any text over and above 1250 words will not be marked. There is no penalty for going under the work limit provided you cover the tasks required above. As this is not a formal management report, you are not required to do a summary, introduction etc. Rather, your report should be laid out into sub-sections to reflect the tasks above, although the sections will not be of equal size. The report is for the manager, so keep the audience in mind when you write up your analysis. You should be to the point, supplementing any statements, conclusions or comments with statistics and/or graphs where appropriate. Any graphs or tables should be included in the main body of your report, labelled clearly and referenced within the text.
The written report should be submitted online via Turnitn on Studyspace in one document.
2. Supporting Spreadsheet
All of the quantitative analysis eg: diagnostic analysis, application and evaluation of the models, graphs and/or tables you generate, should be included in a separate spreadsheet file organised appropriately. The work in this file will be reviewed alongside your written report so it should be clear what you have done. This means that tables and charts should have headings (especially if you use them in the written report), and tabs in the worksheet named accordingly.
This supporting spreadsheet should be submitted on Studyspace under ‘Spreadsheet Submission’ in the Individual Assignment tab.
In April 2010, Mitchell Grant purchased JavaJobe, a company that manufactures and sells luxury coffee machines. In April 2013 JavaJobe expanded their product offering to making coffee capsules to fit into pod-style coffee machines. Sales data (in number of units sold) for each product is available on JavaJobe Data.xlsx; six years of quarterly data for the coffee machines and three years of monthly data for the capsules. Mitchell Grant has asked you to analyse the sales data by addressing the tasks listed below. From a retail perspective, he is concerned about falling and/or stagnant sales levels. From an operational perspective, he is aware that space is at a premium and is concerned about storage costs associated with excess supply.
WHAT YOU ARE REQUIRED TO DO:
Write up your answers to the tasks below using the JavaJobe Data and submit your quantitative analysis on a supporting spreadsheet. The aim of this assignment is to model and analyse the JavaJobe data appropriately and interpret your output to provide recommendations to Mitchell Grant on how to manage his business going forward.
Coffee Capsule Data
Task 1:
Carry out diagnostic analysis on the coffee capsule data to determine what time series components the data exhibits, if any. Remember to present a body of evidence to support your conclusions.
Task 2:
Build a single forecast model using the mean as the estimator. Next, apply the following updating schemes, making sure you justify any values that you introduce as the decision maker (eg: k, weights, alpha). Generate a forecast for next month for each scheme and include this in your report.
• Naïve Forecasting
• Updating the Mean
• Moving average of length k
• Weighted Moving Average of length k OR Simple Exponential Smoothing
Task 3:
Fully evaluate each updating scheme used in task 2 using statistical and graphical analysis and any other information you feel is appropriate to recommend which one updating model should be used to forecast next month’s sales value. In your discussion make sure you explain why you have selected your chosen scheme over the other methods.
Coffee Machine Data
Task 4: Build an appropriate model to forecast the coffee machine data by diagnosing which time series components you think are present in the data and modelling them clearly. Forecast the number of coffee machines you predict JavaJobe will sell next quarter.
Task 5: Fully evaluate your model in task 4 and discuss any factors that the manager should consider when forecasting this type of data.
JavaJobe Sales Data
Task 6: Given your analysis of JavaJobe’s historical sales data for both the coffee machines and capsules, what factors should Mitchell Grant consider for the future?
MARKING CRITERIA
The marking criteria guidelines are published in advance so you know how you will be judged for this piece of work and are available on Studyspace.
HOW YOUR WORK SHOULD BE PRESENTED AND SUBMITTED
You need to submit two files for this piece of coursework:
1. Written Report
You are required to submit a written report with a word limit of 1250 words. Any text over and above 1250 words will not be marked. There is no penalty for going under the work limit provided you cover the tasks required above. As this is not a formal management report, you are not required to do a summary, introduction etc. Rather, your report should be laid out into sub-sections to reflect the tasks above, although the sections will not be of equal size. The report is for the manager, so keep the audience in mind when you write up your analysis. You should be to the point, supplementing any statements, conclusions or comments with statistics and/or graphs where appropriate. Any graphs or tables should be included in the main body of your report, labelled clearly and referenced within the text.
The written report should be submitted online via Turnitn on Studyspace in one document.
2. Supporting Spreadsheet
All of the quantitative analysis eg: diagnostic analysis, application and evaluation of the models, graphs and/or tables you generate, should be included in a separate spreadsheet file organised appropriately. The work in this file will be reviewed alongside your written report so it should be clear what you have done. This means that tables and charts should have headings (especially if you use them in the written report), and tabs in the worksheet named accordingly.
This supporting spreadsheet should be submitted on Studyspace under ‘Spreadsheet Submission’ in the Individual Assignment tab.
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