Apply the Learning Curve Theory
OPS/571
University of Phoenix
March 10, 2010 Week Two

Learning curve is a line displaying the relationship between unit production time and the cumulative number of units produced. Learning (or experience) curve theory has a wide range of application in the business world. Learning curves can be applied to individuals or organizations. (Chase, 2006). Learning curve theory is based on three assumptions: (1) The amount of time required to complete a given task or unit of a product will be less each time the task is undertaken (2) The unit time will decrease at a decreasing rate (3) The reduction in time will follow predictable pattern. (Chase, 2006).
In reviewing the simulation for this week’s assignment, this particular Pizza parlor is having difficulties in serving the customers in means of long waiting time and lines. Long wait times may cause customers to eventually leave or stay and not to return based on the learning curve as outlined above. This has been identified as poor customer service and the service is being reviewed to better assist the customers. The simulation showed four tables having the highest utilization at 99.5% and 38 groups of four balked or left the restaurants without being asked. To tackle this problem, the distribution of tables were changed and the distribution of tables and established a priority rule. This decision appears to be a good one. After the decision was made, the utilization of tables for four changed to 93.92 percent and tables for two changed to 92.92%. 13 groups of four and 4 groups of two balked or left the restaurant without being served. The average waiting changed to 5:59 minutes and the average queue length changed to 2.62 and the profits earned were $1,493, but lost sales worth $450. This is the optimum solution as the waiting time has reduced considerably, a reasonable profit and the utilization of all the servers is not very high. The lost sales amount also reduced to $450. Mario is very happy with the performance thus far and is also pleased that no changes were made to the wait staff and the kitchen staff. The servers did not show a very high utilization, and making changes would have only added to the operating costs. Mario’s smile is increasing as is his confidence in the decision making. The decision to replace one manual oven with two conveyor ovens from Plax appears to be a good decision since the mean processing time of the manual ovens had increased to 15 minutes. The mean processing time of the conveyor oven is 4.00 minutes and will have a significant impact on the waiting time. However, buying two ovens was unnecessary and is adding to the daily operating cost increasing losses in the manual oven that was decided in the simulation. The purchase of the MenuPoint System also reduced the mean processing time of the waiters from 13 minutes to 8 minutes and had a significant impact on the waiting time. The average waiting time in the restaurant is now 4.77 minutes and the average queue length is 2:49. This decision has earned a profit of $1,635 but also lost sales worth $330. The restaurant now has too much capacity and Mario now feels that buying two conveyor ovens was unnecessary and has stated that the two manual ovens should have been shut down to obtain better results.
Overall, some of the decision made were done to better assist the organization and thoroughly researched. To meet the increase in demand, opening Mario’s Take Out has served and taken care of most of the customers. The average wait time is now 4:32 minutes and the average queue length was 2:93. The profit earned for this decision was $1,596, but lost sales worth $825. It appears that Mario would have preferred for the customers to have spent time inside of the restaurant versus in and out. Mario feels that customer ordering take out would not spend time in the store which would generate less money for the parlor versus the customers coming in and probably spending more.
In conclusion, after reviewing the simulation several times, learning how service facilities and their utilization affect the customers was an eye opener. Trying to determine the amount of tables and staff was very difficult from only having a two week training period. Waiting lines forms when customers arrive at a faster rate than the service the system can provide.
Having more products available could potentially decrease the wait time; however, the product still have to be cooked which would still delay the service and have customers waiting. Identifying to the customers of the delivery of the product would be helpful as the customers would feel appreciated in knowing that all orders are cooked to order and the quality/freshness of the product.

Reference Page Richard B. Chase.(2006). Operation Management for Competitive Advantage (11th ed.).New York: McGraw Hill Company.