| DECISION MAKING USING DATA/INFORMATION – Microsoft Excel Assignment 100 points
Students will be given a new small business idea selling specific products to customers. Using Microsoft Excel, students will develop data models to simulate an application that provides business information through data for decision making. Students will build the Excel to model the business operation, formulate the data into information, utilize the information to analyze scenarios, and draw conclusions for the business concept.
Your final Microsoft Excel project workbook (file) will include the following worksheets (tabs). Specific instructions, concepts, expectations, and demo will be provided during scheduled class hours (or via a video for online students). It is highly recommended you attend all classes (or review the video) to obtain the skills and understanding to complete this assignment.
The Business Idea:
• You are planning to open a small electronic store selling three electronic products.
You will be provided an Excel Template as a starting point. The Excel Template will contain the following sheets (Tabs) which you are to make functional as instructed in class:
• Configuration
• Marketing Model
• HR Model
• Accounting Model
• Graph & Charts |
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Instructions:
• For each sheet, the cell colored in yellow are decision variable cells. Within these cells, users of your excel data model will be able to change the values contained within it. Decision variables are decision points that a decision maker, as a potential owner of this simulated business, may decide and/or test so the model will generate calculated results to help determine how this business can be viable or profitable.
• For each sheet, the cell colored in gray are calculated values. Within these cells, you are expected to develop formulas so the sheet can yield correct calculated results based on the decision values entered into the decision variable cells.
• For all decision variables and calculated value cells, you are to make sure the formatting of the cell is correct. Example: if the cell represents a percentage, it should be formatted to %.
• You are not to rearrange and/or reformat the layout within each sheet. The one exception is you are free to design your graphs in the last sheet as long as it meets the requirement stated in the template. |
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Grading:
Configuration Tab (10 Points) – Application Setting
• 1 point deduction for every cell not formatted correctly
• 2 points deduction for each missing value
Marketing Model Tab (25 Points) – Objective: Model, Revenue, COGS, and Gross Profit Monthly Projection
• 1 point deduction for every cell not formatted correctly
• 2 points deduction for every ‘data referencing’ error
• 4 points deduction for every calculation error
HR Model Tab (25 Points) – Objective: Model, Salary Expense, and Employer Tax Expense Monthly Projection
• 1 point deduction for every cell not formatted correctly
• 2 points deduction for every ‘data referencing’ error
• 4 points deduction for every calculation error
Accounting Model Tab (25 Points) – Objective: Model and Cash Flow Monthly Projection
• 1 point deduction for every cell not formatted correctly
• 2 points deduction for every ‘data referencing’ error
• 4 points deduction for every calculation error
Graph & Charts Tab (15 Points) – Objective: Executive Graphical Presentation
• 1 point deduction for each missing label to the data presented on the graph
• 2 points deduction for every ‘data referencing’ error |
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Outcomes of your completed Excel project file will be a tool for users to:
Model – framing of decision variables, presenting calculated data/information, and relationships between data variables for analysis
What-if analysis – checks the impact to the bottom line based on assumptions and changing of decision variables
Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model (decision variables) have on other parts of the model
Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output
Optimization analysis - An extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints. |
gang.uncx
Spring2018StudentTemplate1.xlsx
