Emerson Motor Company (EM), founded in 1900, operates in the year 2019 within a dynamic business simulation environment

 Many business activities generate data that can be thought of as random.  


Emerson Motor Company (EM), founded in 1900, operates in the year 2019 within a dynamic business simulation environment. Each simulation turn represents a period of 28 to 31 days, depending on the month. The company generates detailed reports—monthly, quarterly, and annual—that provide insights into various departments and financial metrics. Among these is the Summary Expense Report, which tracks both historical profits and current operational activities.


A key section within these reports is Warranty Expense, which informs the CEO about the financial impact of vehicle-related service events. Vehicles requiring repairs or subject to recalls under warranty contribute to negative values in this section, while those with fewer issues may positively affect net income.


The Warranty Expense
is associated with a commitment to repair or replace a product for a specified period of time, reported on the income statement at the time that the sale of the product is reported in order to comply, Warranty Payable or Warranty Liability is also established at the time of the sale (Averkamp, 2025).


As Seward notes, “setup time is time that is not used to manufacture the product,” and variations in setup time can indicate either random noise or meaningful changes in process efficiency (Seward, n.d.). For example, when testing new technology to reduce setup time in EM’s manufacturing plant, fluctuations in setup time may reflect either natural variability or the impact of the new system (Sigma Six, 2025).


These warranty expenses are treated as a random experiment within the simulation. Each event—whether a repair or recall—is unpredictable and varies in cost, making this data crucial for understanding product reliability and financial risk. The randomness of these events reflects real-world uncertainty and is essential for strategic planning, cost forecasting, and quality control.



References 


Averkamp. H. (2025). Warranty Expense. https://www.accountingcoach.com/terms/W/warranty-expense#:~:text=The%20expense%20associated%20with%20a,the%20time%20of%20the%20sale.

Davila, E. (June 5, 2025). Statistics Foundations2: Probability Discrete vs. Continuous. https://www.linkedin.com/learning/statistics-foundations-2-probability/discrete-vs-continuous?leis=LTI13&u=74653506

Doane, D., & Seward, L. E. (2022). Applied statistics in business and economics (7th ed.). McGraw-Hill. 

Microsoft. (2025). Copilot. 

Seward, L. (n.d.). Logic of Hypothesis Testing. https://multimedia.phoenix.edu/video/?v=673285066

Six Sigma. (2025). Helping People Find Solutions. https://www.6sigma.us/2025

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