Learning Curves: Theory, Models, and Applications by Mohamad Y. Jaber (edt.)
This is Service Design Thinking: Basics, Tools, Cases by Marc Stickdorn, Jakob Schneider
Customers for Life: How to Turn That One-Time Buyer Into a Lifetime Customer by Carl Sewell, Paul B. Brown
Actual application of learning curve theory is strictly related to the process of improving performance of a system by means of repetitive nature over a particular task, operated by an organization or an individual (Ritter & Schooler, 2002). There are three fundamental assumptions followed by the learning curve theory:
a)Total time for completing a task decreases with the increased repetition
b) Improvement percentage decreases with the increased volume of units
c)Improvement rate gets predictable after some time
The learning curve shows an increment in the performance process and that clarifies that production units get doubled in a limited span of time after some implementation activities. The slope of the learning curve is analysed as per the difference calcuated between the rate of learning in reference to numerical value of 100. In the process, if timing estimated between doubling of units get decreased by 10%, the outcome will be 90% learning curve.
In this paper the approach is to understand the formulation of learning curve theory in the process of Pizza Store Layout Simulation at Mario’s Pizza. For the estimation some records from May 2010 to Nov. 2010 has been followed.
Learning Curve Theory to test Pizza Store Layout Simulation
Learning curve can follow many curve fitting methods. These can be logarithmic scale, arithmetic tables or any other methods. The table noted below has got the data of performance process of Mario’s Pizza to identify the metric in the Pizza Store Layout Simulation:
Table 1 Data from Pizza Store Layout Simulation
SN
|
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
|
11.67
|
3.21
|
1,054
|
2
|
2-May
|
71
|
105
|
6.46
|
2.56
|
1,120
|
3
|
4-Jul
|
71
|
105
|
5.53
|
2.67
|
1,380
|
4
|
6-Sep
|
100
|
140
|
4.93
|
2.88
|
1,985
|
5
|
8-Nov
|
92
|
147
|
3.45
|
2.68
|
2,081
|
As per the results collected from past 6 months of Pizza simulation process in Mario’s Pizza; there is a steady improvement in the calculation of customer’s average waiting time from the assessment observed in the first week in comparision to the 8th week of pizza simulation process. In the proces sthere are 5 process performance data for the performance metrics identified in the Pizza Store Layout simulation at Mario’s Pizza.
Firstly, the time span for waiting has decreased from a record of 11.67mins to 3.45mins by the end of optimization strategy. This removes the bottleneck in the entire process of serving pizaa to the customer.
Secondly, the analysis of the curve declares that average in the calculated waiting time decreases to half; that is from 11.67mins to 5.53mins by the end of 4th week. Approximate slope in the respective curve for 8 weeks gets calculated by
(11.67-3.45)/(8-0) = 1.0272; that is avaerage waiting time decreases by 1.0272/11.67 = 0.088 ~0.09.
Here, the rate of learning is a total of 9% representing 91% in the learning curve. Improvement in the waiting time can be thus estimated through the learning rate (Grant and Leavenworth, 1996). This interpretation is also applicable in the calculation of profit gained attanined by improvement in the performance at Mario’s Pizza.
Thirdly, the profit can be seen in terms of the custmers, from the 1st week to the 8th week in the of pizza simulation process at Mario’s Pizza. The improvement is from 1,054USD to 2,081USD by the end of the process and that attain diiferent parameters for meeting optimization strategy and thereby handling entire bottleneck steps in the process (Chase, Jacobs & Aquilano, 2006).
Fourthly, the analysis of the curve shows profit that has increased by double by the end of 8th week. Approximate slope in the learning curve for a span of 8th week gets calculated as
2,081 -1,054)/( 8-0) = 128.375, which offer a profit of 128.375USD per week.
Fifthly, the increased profit percentage is 128.375 /2,081 = 0.061 ~0.06/ week.
Here, the rate of leatrning= 6% , that is 94% in the learning curve. This offers the weekly improvement.
In a way there is a drastic change in average wait time and the profit earned by Mario’s Pizza. Under the influence of learning curve theory the Mario’s Pizza has attained proficiencies in offering better service system and is also taking care of the customers’ demands.
Alternatively, Mario’s Pizza can follow experience curve effects, whereby matters related to experience and levels of efficiency can be assesed as per the investment led over the effort. In this proces sthemanagemen thas to be more stict with the performance of the staff and experienced people will be preferred more for the job.
Conclusion
The responsibilities of the managers at Mario’s Pizza should be in the operating system, which is inclusive of, line length, number of customers involved in the system, customers’ waiting time spent , system’s total time and appropriate use of service facility. This is an effective means for analyzing the problem of waiting in line in proportion to the fixed costs. Since long queue in any kind of favorite restaurant can annoy the customers, that can lead to the loss of customer,; eventually the drastic fall in the sales. Thus to conclude, it is important to note that learning curve concept needs to be applied for estimating cost of Kitchen Staff, Wait Staff, Plax Ovens, Manual Ovens and Tables sizes for 4 and 2, in order to maiximize profit margins at Mario’s Pizza.
Sources
Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006) Operations management for competitive advantage (11th ed). New York: McGraw Hill/Irwin.
Grant, E. L., and Leavenworth, R. S. (1996) Statistical Quality Control. New York: McGraw-Hill.
Ritter, F. E., & Schooler, L. J. (2002), The learning curve. In International Encyclopedia of the Social and Behavioral Sciences 8602-8605. Amsterdam: Pergamon
No comments:
Post a Comment