Module 4: Decision Lab - Break-Even and Pricing Decisions
Learning Objective: Calculate target-return prices, break-even units, a direct break-even price, and a markup-based service quote; then interpret those results in order to recommend a sound pricing action.
Background (modified real consulting client; all numbers have been changed):
PeakGuard Athletics, a small sporting goods company, was preparing to launch a new athletic mouth guard for school and recreational athletes. Management believed the market opportunity was promising because the United States has an estimated 18 million athletes, and the company hoped to capture about 1 percent of that market in its first year. Before launch, however, the team needed to decide whether the product could be priced in a way that would both attract buyers and meet the firm’s financial goals.
The company had already invested $500,000 in development, production setup, and launch preparation, and the estimated unit cost was $15 per mouth guard. Senior management wanted the product to earn a 30 percent return on investment, but there was concern that a price set too high would reduce sales volume and make the product less competitive. To make a sound decision, management asked the marketing team to work through several pricing approaches, including target-return pricing, break-even analysis, break-even price, and markup pricing.
Instructions:
Download the Module 4 Decision Lab Excel template and complete all required sections of the workbook. This workbook is the only file you should upload for this assignment.
Work through the workbook from left to right. The case data are already provided and should not be changed. You will enter formulas in the designated yellow cells and type your written responses in the larger yellow response boxes. The workbook is organized so that the calculations build toward a final managerial recommendation.
Complete the following tabs in the Excel file:
The Instructions tab explains the purpose and structure of the workbook. No student edits are necessary on this tab.
The Target_Return_Pricing tab asks you to complete two target-return pricing scenarios for the same mouth guard case by comparing a base sales forecast and a more cautious sales forecast. You will then briefly explain how expected sales volume affects the required target-return price.
The Break_Even_Analysis tab asks you to use the same mouth guard case in two ways. First, you will calculate the break-even volume at a proposed wholesale price of $18.00. Second, you will calculate the break-even price required if the company expects to sell 180,000 units. You will then explain what these results suggest about contribution margin and launch risk.
The Markup_and_Summary tab asks you to complete a markup-pricing scenario and review the linked summary of the major pricing outputs from earlier tabs.
The Recommendation tab asks you to answer short managerial questions in complete sentences (limit of 200-300 words) using evidence from your calculations.
The AI_CPM tab must also be completed. If you used an approved AI tool, disclose the tool, prompts, sample output, and how you verified or corrected the output. If you did not use AI, type “No AI used” in the final box
INSERT YOUR ANSWERS TO THE FOLLOWING QUESTIONS INSIDE THE WORKSHEET
Submission Instructions:
Submit the completed Excel workbook only. Do not upload a separate Word file, PDF, screenshot, or photo unless specifically instructed otherwise. Your workbook must show formulas in the designated calculation cells. Answers that include only final numbers without formulas may receive reduced credit. Written responses should be concise, specific, and grounded in the pricing results from the workbook. You must submit your response by typing directly into the template provided; it will expand as you type. Upload your file as Yourlastname_Module4DecisionLab.xlsx.
Grading Rubric: Total 80 points
Question 1 calculation and work shown (15 pts)
Question 2 calculation and work shown (15 pts)
Question 3 calculation and work shown (15 pts)
Question 4 calculation and work shown (15 pts)
Managerial recommendation that interprets the numbers and identifies the key strategic risk (20 pts)
Note: Writing quality is built into every section. Strong work is clear, specific, well organized, and professional. Generic statements should not receive full credit.
Grading Philosophy: Decision Labs are short managerial papers. They are not full reports and they are not just summaries of course terms. Completing all parts of the assignment makes a student eligible for an average grade. Stronger papers will show clear evidence that the student can move from external segment data to realistic personas and then to a strategic business recommendation. The best papers will demonstrate good judgment about how AI can help generate possibilities while also showing why managers should not treat AI-generated personas as substitutes for real market evidence.