Applying the Learning Curve Theory

Apply the Learning Curve Theory
Carlos Heslop
OPS/571
University of Phoenix
Instructor: Lorinzo Foxworth
November 17, 2010.

This paper will be tackling the issues that Mario Pizza store has as it relates to the average waiting time, the average queue length and how both applies to the learning curve concept. According to Chase et al. (2006), ???a learning curve is a line displaying relationship between unit production time and the cumulative number of units produced.??? The application of the learning curve theory to the Mario Pizza store will be based upon a couple of assumptions that have been used in a major industry. The assumptions include the amount of time required to complete a given task or unit of a product will be less each time task is undertaken; the unit time will decrease at a decreasing rate; the reduction in time will follow a predictable pattern (Chase et al, 2006).
Mario wants to improve the process and solve the problems that are affecting his pizza store. He has to balance the length of time that customers are waiting with the capacity of the store to provide the customers with the service that they require. Managing the length of the queues is also about balancing the demand for the product being offered by the store and the ability to service the demand. Mario has entrusted the improvements of the store to his grandchild who will improve the service by changing one or more elements within the operation. The changes will have to be balanced by looking at the gains that may occur as a result of increased service capacity against the costs that are incurred from improving the process.
There has been an established limit of nine minutes for customers to wait for service and lately that has been causing dissatisfaction with customers with some people leaving without even being served. The first step in attempting to reduce the wait time for customers is to look at the distribution of the tables and establish a priority rule. By increasing the number of tables for two to eight and the number of tables for four to 10, the average waiting time was significantly reduced to 5.83 minutes while the average queue length was reduced to 2.52. The business also earned a profit of $1,519 while only losing $420 in sales. Increasing the utilization of the tables across the board also helped to reduce the number of people who decided to leave because of dissatisfaction with the service. This was done while keeping costs down by not making any changes to the wait staff or the kitchen staff (University of Phoenix, 2010).
The next step in improving the productivity of the store was to replace the manual ovens as they were contributing to the lag in the processing time. A conveyor oven from Plax was bought as they had the capacity to bake eight pizzas in four minutes and this significantly reduced the waiting time. The MenuPoint System was bought, and as a result it reduced the average processing time of the waiters from 13 minutes to eight minutes. The two afore-mentioned items helped to reduce the average waiting time to 4.25 minutes while reducing the average queue length to 2.49 individuals. The improvements had the effect of further reducing the number of people who left the restaurant without being served while generating a profit of $1,643 and only $315 in loss of sales (University of Phoenix, 2010).
As a result of a promotional campaign being run by the mall, Mario expects the demand for pizzas to increase substantially. Mario expects to take full advantage of the opportunity that is being presented to the store, but he also wants to ensure that current trends in waiting time and queue length continues to be at a minimal. The decision was taken to rent Cream Puffs bakery next door to Mario??™s store. It already had a kitchen that could be integrated into Mario??™s store and could accommodate seven tables for four and four tables for two. This decision helped to decrease the waiting time even further while increasing the capacity of Mario??™s business. Although the expansion resulted in additional cost per day for the store, the sales went up and the store made a profit of $1,977 and $705 in loss of sales. The business also managed to keep dissatisfied customers at a proportionally small number (University of Phoenix, 2010).
The initial process was lacking in its ability to provide the service that the customers needed, hence customers were arriving at a faster rate than the business could serve them. Even though parameters were set, it was obvious that there was a difficulty in maintaining a balance between the demand for service and the capacity of the system to provide the service. It was therefore necessary to implement changes to the process that was in place so that operating characteristics such as queue length, number of customers who came to the store, time spent in the store, and the utilization of the store elements could be analyzed against costs (University of Phoenix, 2010).

Reference
Aquilano, N.J.,Chase, R.B., & Jacobs, F.R. (2006). Operations management for competitive advantage (11th ed.). New York: McGraw Hill/Irwin.
University of Phoenix. (2010). Pizza store layout simulation. Retrieved on November 16, 2010 from University of Phoenix, Simulation OPS/571 Operations Management: http://mycampus.phoenix.edu/secure/aapd/vendors/tata/sims/operations/opertions_simulation1.html.