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[solved] Determining Production Capacity Needed at Toyota Motor Manufacturing of Canada (TMMC) 

Exercise 3: Determining Production Capacity Needed at Toyota Motor Manufacturing of Canada
(TMMC) 
Decision trees are another important if challenging world-class operations management method which
operations managers should understand and with which other managers should be familiar.
This exercise illustrates how using a decision tree, determination of an "optimal" production capacity
option can be made from among several possible capacity options based on the provided probable
market demand and expected costs/payoffs of events that influence the options.
It is spring 2000, and TMMC has indeed just been chosen to produce the new Lexus RX 330 line, with the
first units deliverable in 2003. Toyota must now determine the amount of annual production capacity it
should build at TMMC.
Toyota's goal is to maximize the profit from the RX 330 line over the five years from 2003-2007. These
vehicles will sell for an average of $37,000 and incur a mean unit production cost of $28,000 (here, $ =
the Canadian dollar). 
10,000 units of annual production capacity can be built for $50M (M=million) with additional blocks of
5,000 units of annual capacity each costing $15M. Each block of 5,000 units of capacity will also cost
$5M per year to maintain, even if the capacity is unused.
Assume that the number of units actually sold each year will be the lesser of the demand and the
production capacity.
 
Marketing has provided three vehicle estimated demand scenarios with associated probabilities as
follows:
Demand 2003 2004 2005 2006 2007 Probability
Low 10,000 10,500 11,000 11,500 12,000 0.25
Moderate 15,000 16,000 17,000 18,000 19,000 0.50
High 20,000 24,000 26,000 28,000 30,000 0.25
 
a. To maximize profit earned during this period, which production capacity should TMMC in 2000
decide to build - 10,000, 15,000, 20,000, 25,000, or 30,000 cars? Justify your choice. 
You may use the following decision tree developed by Toyota operations analysts in Toyota City, Japan -
or your group may choose to vary it in some way based, perhaps, on its presumed better local market
knowledge.
 

 

b. What are the weaknesses or limitations in this analysis? How might they be corrected or at
least reduced?
c. It is now late 2016.  How well has the RX-330/350 actually done in the North American market? 
Is its quality rated as high as if it were made in Japan?  
Do some online research; it's part of improving your attainment of Information Literacy, one of
the UMUC MBA Competencies. Here see the Content/Week 10 references on Grid
Analysis and Decision Trees



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15-06-22 | 02:09:31

TMMC in 2000 should have built 10,000 capacity production units. 10,000 capacities were the
one that could generate much revenue by the end of 2007. The estimated revenue was 65 million.
10k

15k

20k

25k

30k

67m

110m
m

140m

170m

200m
Facility construction
and maintenance
cost for 3 years

0.25, 0.50
and 0.25
probability
After 28000
production
cost

2003 sales

10k

15k

20k

Paula Pal-Kheav
DMBA 620 9044 – Exercise # 3
Other capacity estimation proved to be loss making as at 2007 hence they were unfavorable to
consider. The result of decision tree analysis and calculations are in attached excel.
Despite offering a wide range of possible outcome to analyses, the decision tree has numerous
problems. For example, it is very complex. For our case, there were at least 16 entries to
calculate and without helpful engineering of excel and other available software calculating those
entries can be difficult and time-consuming. Besides that, the decision based on decision tree is
dependent on expectation (Zorman, 1997). Any changes in expectation or any flaw in making
correct expectation can result in large losses in future. Decision tree presentation has also proved
to be unwieldy since even simple categories will lead to large tree hence making it complex in
the presentation. One of the ways to manage decision tree problem is by reducing the
complexity by reducing the use of non-significant or less significant information. Reducing
insignificance means that the size of the tree will be reduced, therefore limit presentation
problem. Reducing the size of the tree will also make it easier to calculate. Usage of modern
advanced software for decision tree analysis will also reduce the complexity (Zorman, 1997).
The software will only require the user to input few needed information, and the rest will be
calculated. An example of such software includes decision tree add-on in excel and tree based
packages in R.
Since 2000 to 2011, Lexus RX brand was the best-selling car in the USA. Again in 2015 and
2016, the brand emerged as the best-selling car in USA (Corporatenews, 2017). Since 2003,
Lexus RX has had more than 1.5% market share in the USA alone. Being the best-selling
vehicle for 11 years means that, the car was very good regarding quality, durability, and
performance (car sales base, 2017). According to Lexus customers review, most of them believe
that there is no difference in quality between Lexus build in Canada and Japan (ClubLexus,

Paula Pal-Kheav
DMBA 620 9044 – Exercise # 3
2017). Most of the customers have owned Lexus build in Japan, and those build in Canada at
different times hence they have a clear understanding of their performances.

References:
Carsalesbase. (2017). Lexus US car sales figures. Carsalesbase.com. Retrieved 18 July 2017,
from http://carsalesbase.com/us-car-sales-data/lexus/
ClubLexus. (2017). Built Quality Difference Between Japan and Canada - ClubLexus - Lexus
Forum Discussion. ClubLexus - Lexus Forum Discussion. Retrieved 18 July 2017, from
https://www.clublexus.com/forums/rx-3rd-gen-2010-2015/598744-built-quality-difference-
between-japan-and-canada-3.html
Corporatenews. (2017). Toyota Motor Sales Reports December 2016 and Year-End Sales |
Corporate. Corporatenews.pressroom.toyota.com. Retrieved 18 July 2017, from
http://corporatenews.pressroom.toyota.com/releases/toyota-lexus-december-2016-sales.htm
Zorman, M. (1997). Limitation of the decision tree. Retrieved 18 July 2017, from
https://link.springer.com/article/10.1023/A:1022876330390


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