Apply the Learning Curve Theory
OPS 571
University of Phoenix

Apply the Learning Curve Theory In business and academics students, managers, and employees learn tasks at different rates. One employee may grasp a task within the first attempt whereas others may take several tries to achieve efficient production. The average time it takes for a group of people to adjust is the learning curve. This paper will review the learning curve theory as it applies to a simulated pizza store layout.
The learning curve Learning curves can be applied to individuals. Learning improves with repetition generating skill or efficiency. Much of academia is based on this “practice makes perfect” (Chase, Jacobs, Aquilano, 2006) idea. The learning curve in manufacturing and service compares the result of the expected product to the length of time to produce it. As more employees learn a new process, time to produce increases. As employees become efficient, time decreases. At the beginning of the curve, fewer products are produced; at the end of the curve more products are produced in less time than the previous process. Organizational learning comes from combined individual learning, also administration, equipment, and product design changes. A new kitchen staff has high service times as the cooks become familiar with the menu recipes and cook times. If the kitchen adds a new microwave, service times increase again, as cooks learn time and temperatures for the microwave. As cooks become familiar with the menu and recipes, order time decreases. As cooks learn how to use the microwave to reheat pre-prepared dishes, order time falls further. Eventually service times decrease below where the process started increasing customer satisfaction and amount of customers or sales.

Applying the learning curve theory According to Chase, Jacobs, and Aquilano (2006), the learning curve theory has three assumptions. The amount of completion time for a given task will decrease each time the task is completed. The time will decrease at a decreasing rate. The reduction follows a predictable pattern. Individually, the initial time the pizza layout simulation was completed, the solutions chosen were not optimal and the simulation took 20 minutes to complete. The second time, the correct solutions were chosen and the simulation only took five minutes to complete. The final simulation chose the correct answers and took eight minutes to read through the responses and fully complete. The simulation also demonstrated organizational learning in the initial slight increase in service times and structured decrease as the owner added new tables and maintain the staff to allow more and smaller customer groups. This decision led to a decrease in wait time overall from eight minutes to just 5.5 minutes for customers. In the second part of the scenario, the owner chose to upgrade equipment. The upgraded equipment in the order process increased order times initially but overall decreased to 4.25 minutes while maintaining product volume at 2.54. The final decision to increase sales was to expand the store or add in a take-out window. The optimal decision, to expand the store, decreased customer wait time further to 3.3 minutes while only slightly increasing queue to 2.63.
Conclusion
The simulation clearly demonstrates the learning curve theory. The simulation driver themselves learns and adapts to the proper solutions each time the simulation is completed, but the decrease in time was smaller each time. The simulated decrease in wait time was also smaller during each upgrade to the store. The first upgrade was administrative in how to serve different groups of customer. The second was an equipment upgrade. The final change was a product design in how to offer service to customers.

References
Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006) Operations management for competitive advantage
(11th ed). New York: McGraw Hill/Irwin.