Open Educational Resources
Document Type
Case Study
Publication Date
Spring 5-31-2026
Abstract
Labor costs are one of the largest operational costs in the service industry. Overstaffing increases expenses unnecessarily, and understaffing reduces service quality and customer satisfaction. You are a business operations analyst working for Gabriana Cup, a local coffee shop. The owner has observed that certain hours appear significantly busier than others, creating operational pressure during peak times. The owner would like to reduce unnecessary labor costs and optimize Gabriana Cup's staffing practices.
Staffing schedules are currently based on assumptions rather than historical sales patterns, costing the coffee shop owner through wasted inventory, overstaffing, understaffing, and unnecessary labor costs. The coffee shop does not clearly understand its peak and low transaction periods, which has led to inefficient staffing decisions. What staffing decisions can you develop using historical sales data?
To aid your analysis, the coffee shop owner has provided a dataset that includes sales information from March 2024 to March 2025. This data includes the hour of the day, weekday, month, and time that a transaction was made. By analyzing revenue and the number of transactions, what staffing decisions would you develop?
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
CUNY OER Funding
CUNY OER Initiative
dataset
Included in
Business Administration, Management, and Operations Commons, Business Analytics Commons, Business Intelligence Commons
Comments
This OER was funded in part by the CUNY OER Initiative.