Mario’s Pizzeria in the process of a managerial transition from Mariao, the owner, to his grandson, a MBA graduate, which will last for the duration of two months in order to see if he can permanently handle the business. The University of Phoenix simulation (2002) mentioned problems regarding the waiting line, utilization of staff & ovens, and an increased customer demand to maintain a balance between the services system capacity and the service demand. It is five to ten points of process performance data for the identified performance metrics in the simulation and the learning curve theory application to the alternatives presented in the process that will be analyzed.

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Process Performance Data Points & Learning Curve Theory Application
The analyzed process performance data points included the number of customer balks, the total amounts of variable costs and daily costs, total sales, total profit, and total lost sales. When customers balk it causes profit loss, which does not incur a good way for the pizzeria to maximize their profits. Mario’s Pizzeria doubles their lost sales when a group of four balks ($30 for four pizzas) when compared to groups of two balk ($15 for two pizzas) (University of Phoenix, 2002).

Mario’s Pizzeria has tried to apply a priority seating system for groups of two and groups of four (University of Phoenix, 2002). The Scenario One has a designed priority seating system requiring the addition of more tables for groups of two in addition to groups of four, and changing the number of wait & kitchen staff. The grandson determined the number of tables for two to be increased from zero to eight and the number of tables for four to be decreased from fourteen to ten while keeping the wait & kitchen staffs the same Mario optimized the number of tables for groups of two and four to reflect the 60:40 ratio mentioned in the University of Phoenix simulation (2002).

When assessing the utilization of staff & ovens, the pizzeria should certainly minimize the extra variable costs, which increase total daily costs and decrease profits. Sales and profits are conditional on the successful management of operational costs and serviced customers. More customers can be serviced without customer balks, more money the pizzeria can make. The pizzeria can maximize profits by controlling fixed and variable costs up to the point to increase productivity without adding to operational costs.

In Scenario Two, the alternative included ordering the MenuPoint automated ordering system, ordering a Plax oven, and changing the number of Manual ovens. Due to malfunction problems with the Manual ovens with two being completely shut down, the grandson decided to replace one Manual oven and ordered two Plax ovens as well as the MenuPoint system to help control the average waiting times and queue lengths. Mario optimized the number of Plax ovens to one, as buying two unnecessary ovens due to added oven operational costs. In Scenario Three, the grandson chose to rent the Cream Puffs building to provide more seating for groups of four and groups of two, since they were at the max utilization percentage directly relating to the learning curve theory. Each scenario results in decreased average wait times and queue lengths, due to operational repetition. Each scenario also resulted in a new set of challenges before choosing the alternative for the next scenario, which relates to a new alternative process commencing; as a new process commences, it is likely that maximum efficiency will not be achieved. This is evident after the alternatives were chosen for Scenario One and Scenario Two when Mario optimized the alternatives. The process performance data points help illustrate the learning curve theory application of the process alternatives available for the pizzeria.

Conclusion
The University of Phoenix Simulation (2002) introduced the elements for all waiting line problems: the customer population, waiting line, service system, and priority rule for determining which customer is to be serviced first; balancing the service system capacity and service demand turn on relating the characteristics of each to their associated costs. As each characteristic and cost is compared over time, there is a set of process data points that can help to achieve optimum operational productivity through the learning curve theory. There are always new challenges presented to business after addressing problems, no matter whether the choices proved to be optimal or not.

    References
  • University of Phoenix. (N.A). Pizza Store Layout Simulation [Multimedia]. Retrieved from University of Phoenix, OPS 571 website.