Learning Curve Theory

OPS 571
August 22, 2012

Learning Curve Theory
In the required simulation, the owner/operator of Mario’s Pizza is considering transferring operations of the pizzeria to a family member. Mario has elected to supervise the business decisions made by the family member with regard to reductions in customer wait times and lost sales. Three scenarios are simulated: adjusting the number of tables allocated for two and four guests as well as adjustments to wait and kitchen staff, choosing to implement new technologies, and a choice between adding seating space or a takeout option. If Mario sees that the decisions made by the family member are sound, then he will hand over operations of the pizzeria at the end of two months. Because measurement in service industries is subjective (Pati & Reis, 2007), progress will be measured in lost sales, lost customers, and daily operating costs.
Guests typically enter the restaurant in parties of two to four. The decision was made to set the number of tables designated for parties of two to 8, leaving the remaining 10 tables for parties of four. No change was made to the numbers of wait or kitchen staff. Increasing these numbers would have increased daily operating costs, making any possible losses more difficult to bear financially. Decreasing these numbers may have placed extra burden on the staff members, making efficiency difficult. While some sales were lost (see fig. 1), the losses were kept at a minimum. Based on the results indicated in the simulation, Mario was pleased with the numbers, and elected not to make any changes.

Fig. 1:

In the second phase of the simulation, the family member must make a decision as to what (if any) new technologies to implement. The first offering is an improved order taking system, Menupoint. Menupoint is intended to increase efficiency of the order taking system by electronically transmitting orders taken by servers directly to the kitchen. The other technology choice is to whether or not to replace two non functioning manual ovens with conveyor ovens called Plax.
The decision was made to order the Menupoint system and use only one Plax oven, no manual ovens. This was a successful choice, as average customer wait times decreased from 4.25 minutes to 2.5 minutes (Fig 2).

The problem here is that no indication is made as to the level of training required to learn how to operate the new technologies. A metric will need to be generated to measure the complexity of the technology, and the learning curve of the staff. According to Pati and Reis (2007), the dependent variables should be average time in the restaurant per customer and average number of complaints per meal or per customer served, while independent variables are the number of customers and numbers of meals served. Measuring these factors will enable the business manager to determine the effectiveness of the new technology over the longer term. While wait times may decrease initially, if they do not stay at optimum levels, additional training or elimination of the system may be required. Since both technologies were implemented at the same time, the manager will get feedback from employees to determine which system is most likely causing the problem.
The final decision to be made was whether to open a takeout window or rent additional seating space. The choice was made to rent additional seating space, as the business is located in a shopping mall, and takeout business seems less likely. The choice was a wise one, as wait times stayed below the four minute mark (Fig 3).
Fig 3

There are some flaws in the simulation, however. There was no indication in the simulation as to the presence of bussers or janitorial staff. In food service, there may be issues such as spills that will require cleanup. In the absence of additional staff members to control these incidents, efficiency may be affected, and could result in lost customers because of increased wait times. It is stated in the article, The Quality Learning Curve: An Approach to Predicting Quality Improvement in Manufacturing and Services that “…many characteristics of service systems are objectively measurable. … spills in service and dining areas of military dining facilities, in food services and attendant services” (Pati & Reis, 2007 pp. 132).

Reference
Pati, N., & Reis, D. (2007, July 1). The Quality Learning Curve: An Approach to Predicting Quality Improvement in Manufacturing and Services. The Journal of Global Business Issues, 1(2), 129-140.