Applying the Learning Curve to Mario??™s Pizzeria
University of Phoenix
Mario??™s Pizzeria is a family owned establishment that needs to make several changes to its operational process in order to attain a greater level of success and stability. A quick overview of the current process at Mario??™s Pizzeria shows that there are: four servers, two kitchen staff, four manual ovens, 14 tables that seat four, zero tables that seat two and a wait time with an upper tolerance level of nine minutes that is on average exceeded by three minutes (12 minutes). This combination is causing a loss in sales both through potential customers leaving before (balking) and after (reneging) placing their order. The changes presented below will reduce the number of customers balking or reneging as well as streamline the pizzeria??™s process. The bulk of the new data collected from the changes/alternatives, which will reflect the learning curve, depends on the initial process data being accurate in order to show an accurate learning curve. The initial process data seems to be good, but not as fleshed out as it could be. Through running the process/simulation several times, a better set of data is obtained.
The most effective alternatives found through the simulation: keeping the same number of servers and kitchen staff, getting rid of all four manual ovens and replacing them with one Plax oven, decreasing the number of tables that seat four to ten while increasing the number of tables that seat two to eight and adding on the cream puff rental to compensate for his increased business. All of these changes/alternatives allow the pizzeria to consistently stay below their upper level tolerance for wait times (nine minutes) but avoid the issue of over optimization/under utilization. Another alternative that can be implemented is the concept of ???pizza by the slice??™. This would allow those customers who don??™t need an entire ???made to order pizza??™ to get in and out quickly. With the new Plax oven, these types of pizzas can be produced faster since they don??™t necessarily depend on customers being present when the pizza is made, cutting down the numbers of those who have to order a new pizza during peak times. The learning curve comes into play with this alternative in two main ways: the kitchen workers learning to figure out when a new ???by the slice??™ pizza needs to be slipped in/made along with the ???by order??™ pizzas and the wait staff learning to recommend the ???by the slice??™ option to the guests who appear to be ready to balk/renege due to wait times/lines. This can be tested against the current method by comparing the figures of those who balk/renege now versus the numbers who do so under the ???by the slice??™ alternative. The weekly sales and sales lost are also two effective comparison points.
University of Phoenix. Operations and Management, Process Control and Problem Solving. Unknown. [https://ecampus.phoenix.edu/secure/aapd/vendors/tata/sims/operations/operations_simulation1.html]. 5/14/10.
* Submit five to ten points of process performance data for the performance metrics identified in the Pizza Store Layout simulation.
* the average wait time
* the average queue length
* the number of tables
* the number of wait staff
* the number of ovens
* The type of ovens (plex vs. man