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Introduction

Competitive bidding has become an integral part of the project management responsibility in many industries. If the bid is too low, the company may have to incur the cost of the overrun out of its own pocket. For a small firm, this overrun could lead to financial disaster (Kerzner, 2006). Perhaps the most difficult projects to estimate are those that involve the development and manufacturing of an important quantity of units. Experience curves are based on the old adage that practice makes perfect. A product can always be manufactured better and in a shorter time period not only the second time, but each succeeding time (Kerzner, 2006).
Organizations have often used learning curves to predict the improvement in productivity that can occur as experience is gained of a process. Thus learning curves can give an organization a method of measuring continuous improvement activities. If a firm can estimate the rate at which an operation time will decrease then it can predict the impact on cost and increase in effective capacity over time (Greasley, 2009).
Learning curve theory is based on three assumptions. First of all, the amount of time required to complete a given task or unit of a product will be less each time the task is undertaken. A second assumption says that the unit time will decrease at a decreasing rate, and finally the reduction in time will follow a predictable pattern (Jacobs, 2009).

Application of Learning Curves
The table for process performance data for the metric identified in the Pizza Store Layout Simulation is as follows
Table 1
Process performance data for the metric identified in the Pizza Store Layout Simulation
S. No. |Weeks |No of Customers for Group of 2 |No of Customers for Group of 4 |Avg. Wait Time(Min) |Avg. Queue Length |Profit ($) | |1 |0 |70 |106 |11.32 |3.04 |1,054 | |2 |1-2 |73 |103 |4.93 |2.52 |1,327 | |3 |3-4 |71 |105 |5.51 |2.68 |1,439 | |4 |5-6 |70 |106 |5.35 |2.62 |1,539 | |5 |7-8 |97 |142 |3.07 |2.84 |2,008 | |
Learning results can be applied to individuals or organizations. Individual learning focuses on practice. Organizational learning results from practice as well, but it also comes from changes in administration, equipment, and product design. In organizational settings, we expect to see both kinds of learning occurring simultaneously and often describe the combined effect with a single learning curve (Jacobs, 2009). This case shows how by modifying some organizational setting, such as equipment, can produce an enormous effect. We have applied the first assumption described in the introduction: the amount of time required to complete a given task or unit of a product will be less each time the task is undertaken.
A learning curve may be developed from an arithmetic tabulation, by logarithms, or by some other curve-fitting method, depending on the amount and form of the available data (Jacobs, 2009). The following chart shows the learning curve, plotted as week range on X-axis, and Average time, expressed in minutes on Y-axis. Values for the chart are taken from above table.
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As seen from the above table, and after analyzing the data from the simulation, an alternative to the process is totally feasible. An alternative process includes the incorporation of new equipment, such as convey ovens, reorganizing the kitchen and waiters staff, helping them with new technology, such as Menu Point.
Chart above shows how waiting time was reduced from 11.32 minutes to 3.07 minutes. This also means that kitchen staff is able to produce more pizzas in less time. This is totally related to the learning curve theory as this is a relationship between unit production time and the cumulative number of units produced, in this case pizzas.
Initial data showed how waiters and kitchen staffs were underutilized. At the beginning, the tables for four showed the highest utilization at 99.56 percent and 37 groups of four balked or left the restaurant without being served. To tackle this problem, changes to the distribution of tables were made. After this decision, the utilization of tables for four changed to 98.04 and tables for two changed to 85.45 percent.

Conclusion
A Learning curve is a relation between two variables: unit production and number of units produced. This papers shows how Mario??™s Pizzas store is a clear example on how reducing the average waiting time, leads to the conclusion that the staff is able to produce more pizzas in less time, increasing profits and customers satisfaction. This way the store is able to satisfy more customers, by reducing the total amount of time, including table and waiters??™ availability, product production at the kitchen.
References
Greasley, A. (2009). Operations Management, Chapter 9: Job and Work Design, John Wiley & Sons, United States.
Jacob, R. (2009). Operations and Supply Management. McGraw-Hill Company, United States.
Kerzner, H. (2006). Project Management, Chapter 18: Learning Curves, John Wiley & Sons, United States.