Identification of the ‘Pizza Store Layout Simulation’ Scenario Statistics

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The paper is to identify the ‘Pizza Store Layout Simulation’ scenario statistics and seek out the performance metrics. Also an alternative to the process is developed and discussed on the reasons of substitution. The main feature utilized in the context of studies is learning curve concept. Using it, the performance of ‘Pizza Store Layout Simulation’ as well as alternative to it is analyzed. Study on the topic starts with learning curve concept travels through its utilization on current method performance analysis and alternate one as well.

The notion behind learning curve concept is to the individuals “monitor who perform repetitive tasks exhibit an improvement in performance as the task is repeated a number of times.” The theory of learning curve concept relies on mainly three basic postulations stated below:

“The time required to perform a task decreases as the task is repeated,
The amount of improvement decreases as more units are produced, and
The rate of improvement has sufficient consistency to allow its use as a prediction tool.” (The learning curve, n.d).

It has seen an augmentation in the procedure of efficiency in such an approach so that quantity of goods manufactured is increased to twice the previous production within a shorter period of time due to a considerable time of execution. The same can be reexamined as the pace in which analysis is taken place by giving priority to consistent reduction in delay. The calculations are started with determination of slope of the curve under analysis. It is computed through the calculation of difference between rate of learning and percentage arithmetic cost. “The constant percentage by which the costs of doubled quantities decrease is called the rate of learning.” (The learning curve, n.d). The measurement is in such a way that 90 percent learning curve is said to exist when delay for the units to become twice is lowered by 10 percentage.

The fact to be observed is that quantity of decrease in cost can never be made the same but possibility is only on the turning down of effect of cost by considerable increase in mass. The truth of profit and loss is not fully depicted in cost incurred but on quantities dispersed. Now, to start with the analysis of Pizza Store Layout Simulation the table of process performance is shown below.

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	68	108	11.24	3.12	1,065
2	1-2	71	105	11.06	3.01	1,120
3	3-4	71	105	5.09	2.61	1,427
4	5-6	72	104	4.55	2.67	1,600
5	7-8	94	145	3.14	2.79	2,051

The simulation is being carried out to achieve profit with minimum average waiting time and average queue length. The optimization of resources and managing them with efficient operational management techniques is very much essential in this analysis.

Let us analyze the initial situation and during 1-2 weeks. Initially, we had 14 tables for 8 with 4 wait staff and 2 kitchen staff. The profit was 1,065$ with a wait time averaged to 11.24 minutes accompanied by a sale loss of 1170. The utilization of tables was at maxima with an average queue length of 3.12.

Later as a first stage of optimization, the number of tables to accommodate 2 and 4 are varied in such a way to achieve optimization in that regard. The arrangement is changed to get a different profitable effect. By adding 8 tables for 2 after reducing 4 tables for 8 and keeping wait staff to 5 a real time change in results which were favorable was attained. It was observed that an increase in profit as well as decrease in average waiting time is achieved with no doubt. The average waiting time and queue length was seen as follows:

The result of those at the end of this step of optimization was given as

Profit came upto 1427$ with loss of only 525 sales with average queing length reduced to 2.61 and average wait time to 5.09 minutes. But still optimization is possible through regulating the number of ovens both manual and plax.

Plax ovens have twice the efficiency of manual ovens and even requires shorter delay of usage. Also the option of menu point can be utilized which will bring about tremendous difference in the speed of all activities. After optimizing in these aspects, the result was obtained as follows.

Again the profit was increased to reach 1601$ with average wait time reduced to 4.55 minutes and average queue length to 2.67. The loss of sale reached down to just 405 along with eliminating two manual ovens to take a substitute of just one plax oven. Thus a real time cahnge is experienced when compared to the initial status.

Again there is option of adding space to the Pizza place at congestion times of celebrations and promotion programmes. The annexure of nearby corner with somethings extra like cream puffs can add to sales and space for the place.

The profit is figured to a doubled status after this optimization. The loss of sales is 705, it can be ignored as it is a rushy time anf even the wait time and queue length is very much reduce and reached 3.14 minutes and 2.79 respectively that explains the maximum possible optimization through keen operations management.

Now coming to learning curve conceptual approach for our case analysis. The minimum average wait time is 3.14 minutes and highest is 11.24 miutes. The slope of wait time curve can be determined as the ratio of differences:

(11.24 – 3.14) / (8 – 0) = 1.0125

i.e. there is a decrease in 1.0125 minutes of average wait time. Therefore rate of learning can be calculated as

1.0125 / 11.24 = 0.09008 ~ 0.09 = 9%

That implies, 91% learning curve. Similarly, for increase in profit learning curve has to be determined. The highest and lowest values of profit achieved are 2051$ and 1065$ respectively. So the slope of profit curve is given by

(2051 – 1065) / (8 – 0) = 123.25$

i.e. an increase of 123.25$ occur every week. The rate of learning can be now calculated as

123.25 / 2051 = 0.06009 ~ 0.06 = 6%

Thus a 94% learning curve is exhibited.

The study conducted on Pizza Store Layout Simulation took through the possibilities of improvements in average waiting time and profit with the increase in quantities. The number of tables, staff and equipments like ovens were all adding to the optimization of our case. The strategies of achieving improvement with existing assets and backups with application of a little amount of keen operational supervision in it, better results can be made. The fact which is illuminated among these dug out operational management ideas is that no complete sales or profit is possible, only a balancing among the requirements and availabilities can be achieved; so the same is the goal of an operational manager.

Reference List

The learning curve. (n.d). Federal Aviation Administration. Web.

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Identification of the ‘Pizza Store Layout Simulation’ Scenario Statistics

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