Evaluating Land Investment: A Case Study of West Houser Paper

This case study analyzes the West Houser Paper Company's decision regarding the purchase of a timber forest land. The company faces the dilemma of buying the land immediately for $2.2 million or delaying the purchase in hopes of a price decrease, while also considering the risk of a competitor acquiring the land. The analysis incorporates probabilities of price decreases and competitor actions using a decision tree model built with Precision Tree in Microsoft Excel. The solution suggests that foregoing the land purchase and investing in alternative options is the most beneficial strategy, offering a potential profit of $650,000, as purchasing the land may lead to losses considering additional costs. The study highlights the importance of strategic decision-making in uncertain business environments and the effectiveness of decision tree analysis in evaluating complex scenarios.

Case - West Houser paper company
The West Houser Paper Company located in the state of Washington has ambition of purchasing
a piece of land that has good timber forest on it. The current cost value of the land as dated on 1st
May would be 2.2 million dollars. The company at the moment has not prioritized any activity
that would require it to use the timber on the land until when the month of July would
commence. The West Houser Paper Company top stakeholders fear losing the piece of land to
another competitive company who might also require it during the period between 1st May to
July. According to their analysis there is a 5% chance or 0.05 probability of the competitor
acquiring the land during this period of May. If the chance would not materialize or the
probability fails then there would be a 10% chance or 0.1 probabilities of the competitors
acquiring the land during the month of June. The West Houser Paper Company can take this
chance now or attempt to do so at the start of the month of June or at the start of July if the land
availability holds. The delay of purchasing the land according to West Houser Paper Company’s
finance expert would help to lower the current price either in the first month of June or at the end
of the second month of July. The analyzed the land cost decrease and their probabilities as shown
in table 6.2 and table 6.3. Table 6.2 demonstrates the possible chances or probabilities of the
price decrease during the month of May. Table 6.3 shows the possible chances or conditional
probabilities of the price decrease during the month of June based on the price decrease in the
month of May. For example, it shows that when cost price of the land would decrease in May by
60,000 dollars, then the outcome of the price that would decreases in June would be $0, $30,000,
and $60,000 and their respective probabilities or chances would be 0.6, 0.2, and 0.2. If West
Houser purchases the land, it believes that it can gross $3 million. (This does not count the cost
of purchasing the land.) But if it does not purchase the land, West Houser believes that it can
make $650,000 from alternative investments. What should the company do?
Table 6.2 Distribution of Price Decrease in May
Price Decrease Probability
$0 0.5
$ 60,000 0.3
$120,000 0.2

Table 6.3 Distribution of Price Decrease in June
Price Decrease in May
$0 $60,000 $120,000
June Decrease Probability June Decrease Probability June Decrease Probability
$ 0 0.3 $ 0 0.6 $ 0 0.7
$ 60,000 0.6 $ 30,000 0.2 $ 20,000 0.2
$ 120,000 0.1 $ 60,000 0.2 $ 40,000 0.1
Solution
The inputs values are given below, all values are in thousands
Inputs
Current price 2200
Gross revenue from land 3000
Profit from alternatives 650
Probability of competitor buying the land in
May
0.05
Probability of competitor buying the land in
June
0.1
The price decrease distribution in May is given as;
Price decrease Probability
0 0.5

60 0.3
120 0.2
The price decrease distribution in June, when there is a decrease in price decrease in May is given as;
Price decrease Probability
0 0.3
60 0.6
120 0.1
The price decrease distribution in June, given $60 price decrease in may is given as;
Price decrease Probability
0 0.6
30 0.2
60 0.2
The price decrease distribution in June, given $120 price decrease in may is given as;
Price decrease Probability
0 0.7
20 0.2
40 0.1
Method used
The tool used in making the right decision would be excel precision tree that would generate decision
tree and help to determine the appropriate method that the company would use.
Precision Tree helps one to easily tackle and solve all types of complex and sequential decision. The
Precision Tree helps one map out, analyze and organize decisions using decision tree that would be
found in Microsoft Excel. The Microsoft Excel decision trees are quantitative diagrams that have nodes
and branches that would show different and possible paths of decision and chance events. Generally it
will help one easily identify and be able to calculate all the values of possible alternative and in long run
be able to choose the best option (Albright, Winston and Zappe, 2010).

Building a decision tree using the following steps (Albright & Winston, 2017).
Step 1: in the precision tree tab, click on the decision tree button and specify the starting cell for the
decision tree as shown on the figure below
Step 2: click Ok. A dialogue box will appear as shown on the diagram below, and give it appropriate
name in Name section and then click OK
Step 3: Click on the end node and let the node be decision type of node. Write the appropriate decision
name that is purchased at the beginning of May
In the branches tab, build 2 branches since they are two possible values no and yes wait. In the column
of value for the yes branch enter the difference between the gross revenue and current price as shown
on the figure below and click OK

For the branch of no wait in the tree do the following steps
Step 4: click on the end node of no wait branch and make the node type as Chance and let there be two
branches. Provide the appropriate names to the nodes and outcomes as yes and no. The value and
probability is obtain with the formula shown on the figure below and click OK

Now for ‘no wait’ branch, follow the steps provide below
Step 5: click on the end node of ‘no branch’ and make the node type as Chance and let there be three
branches. Give the appropriate name to the nodes and the outcome as 0, 60 and 120. The probability
for each branch would be obtained with the formula shown in the figure below then click OK button

For the branch ‘0’ follow the steps
Step 6: Click on the end node of ‘0 branch’.. Since a decision is needed to be specified for the problem,
let the node be the decision type of node. Write the appropriate decision name for the purchase at the
beginning of June

In branches tab, build 2 branches since there are two possible value yes and no wait. In the value
column for yes branch enter the difference between gross revenue, current price and price decrease as
shown on the figure below and click OK button
Step 7: click on the end node of the ‘no wait’ branch of the decision node, and make the node type as
Chance and let there be two branches. Give the appropriate names of the nodes and outcome as yes

and no. the value and probabilities are obtained with formula that is shown on the figure below and
then click OK button
Step 8: Click on the end nodes the ‘no’ branch that was obtained on step 7, make the node type as
Chance and let there be three branches. Give the appropriate names to the nodes and outcome as 0, 60,
and 120 each probability as provided in the distribution table of price decrease in June, when the price
decreases in May. The value would be obtained with the formula shown on the figure below and then
click OK button.

Step 9: click on the end node of ‘0’ branch obtained on step 8. Since we need to specify the decision for
the problem, let the node be decision type of node. Write the appropriate decision name like purchase
at the start of June.
In the branches tab, build 2 branches that is no and yes wait. In the column of value enter the formula as
shown in the diagram below and then click OK button

Step 10: Right click the decision node that was built in step 9 and choose Copy Subtree option. Click on
the end node of 60 and 120 of step 8. Choose Paste Subtree by right clicking. On doing this all subtrees
would be obtained. The updated values are shown on the figure below.
For branch of 60

For branch of 120