Cabinet Accessory Company: Sales, Cost, and Gross Profit Analysis (Financial Accounting)

Learning objectives

1. Find and correct errors in a data set (clean the data)
2. Add columns containing formulas to a data set
3. Create a pivot table in Excel
4. Create a pivot chart in Excel
5. Analyze sales data using a pivot table and a pivot chart
6. Determine the net impact on retained earnings using data from a pivot table
7. Create a calculated field in a pivot table
8. Sort a pivot table by stated criteria
9. Filter a pivot table
10. Interpret findings from a pivot table

Data set background

This dataset represents sales and cost data for a fictitious company, Cabinet Accessory Company (CAC), covering the four-year period from 2014 to 2018. CAC sells cabinet hardware including knobs and pulls. In the project, the student is asked to calculate the net impact on retained earnings each year from the sales and cost data. The project also focuses on the calculation of gross profit from a set of sales data and how that sales and cost data can be viewed from the perspective of the region, product line, etc.

Data dictionary

• customer_number: Description
• region: There are eight regions: Central, East coast, Midwest, Northeast, Northwest, South, West, and International.
• date_of_sale: Description
• item: Description
• brand: Description
• collection: Description
• description: Description
• list_price: Description
• cost: Description
• quantity_sold: Description

Specific requirements

1. Create three columns in the Data worksheet that calculate sales revenue, cost, and gross profit for each sales record (each row.) Use the columns already named in the Data worksheet sales revenue, total cost, and gross profit, respectively. Format numbers in the three columns as Accounting with two decimal places.
2. Create a pivot table that shows sales revenue by region for each of the four years and quarters. Correct any errors in the original dataset in the worksheet that are revealed in this initial pivot table. Once you have corrected the errors in the original data set, refresh the pivot table to reflect the corrected data. Insert a pivot chart that shows the sales revenue trend by region over the four-year period. In the pivot chart, the x-axis should be years and the y-axis should be sales revenue. What trends do you see in the pivot table and pivot chart?
3. Create a pivot table that shows sales revenue, total cost, and gross profit for each year. What would have been the net impact on retained earnings in each of these years from the transactions listed in the data set? Ignore any tax effects.
4. Create a pivot table to answer the question What was the most profitable brand in each year, as measured by gross profit?
5. Create a pivot table to answer the questions: Within each brand, what was the most profitable collection in 2018, as measured by the gross profit percentage? The least most profitable collection for each brand? Use the field years to filter the data to include just the year of 2018. You will need to add a calculated field to the pivot table to calculate the gross profit percentage. Within each brand, sort the collections by gross profit percentage, from the largest to the smallest. Interpret your findings.
6. Create a pivot table to answer the question Which region was the most profitable in 2018, as measured by the gross profit percentage? Include gross profit (dollars) in the pivot table. Use a filter to include only sales from 2018 in this pivot table. You should be able to select the calculated field you created in Requirement 5 rather than calculating a new gross profit percentage. Sort the regions by gross profit percentage, from largest to smallest.