The Basic Tree
for Projects
Figure 4-3 shows
the basic layout. It is customary, as described by John Schuyler in his book,
Risk and Decision Analysis in Projects, Second Edition, [3] to show the tree laying on its side with
the root to the left. Such an orientation facilitates adding to the tree by
adding paper to the right. We use a somewhat standard notation: the square is
the decision node; the decision node is labeled with the statement of the
decision needed. Circles are summing nodes for quantitative values of
alternatives or of different probabilistic outcomes. Diamonds are the starting
point for random variables, and the triangle is the starting point for
deterministic variables.
In Figure 4-3, the
decision maker is trying to decide between alternative "A" and alternative "B".
There are several components to each decision as illustrated on the far right of the figure. Summing nodes
combine the disparate inputs until there is a value for "A" and a value for "B".
An example of a decision of this character is well known to project managers:
"make or buy a particular deliverable."
Since our objective is to arrive at the decision node with a
quantitative value for "A" and "B" so that the project manager can pick
according to best advantage to the project, we apply values in the following
way:
-
Fixed deterministic values, whether positive or negative,
are usually shown on the connectors between summing nodes or as inputs to a
summing node. We will show them as inputs to the summing node.
-
Random variable values are assigned a value and a
probability, one such value-probability pair on each connector into the summing
node. The summing node then sums the expected value (value * probability) for
all its inputs. Naturally, the probabilities of all random variables leading to
a summing node must sum to 1. Thus, the project manager must be cognizant of the
1-p space as the inputs are arrayed on the decision tree.
Figure 4-4 shows a
simple example of how the summing node works. Alternative "A" is a risky
proposition: it has an upside of $5,000 with 0.8 probability, but it has a
downside potential of -$3,000 with a 0.2 probability. "A" also requires a fixed
procurement of $2,000 in order to complete the scope of "A". The expected value
of the risky components of "A" is $3,400. Combined with the $2,000 fixed
expenditure, "A" has an expected value of $5,400 at this node. The most
pessimistic outcome of "A" at this node is -$1,000: $2,000 - $3,000; the most
optimistic figure is $7,000: $2,000 + $5,000. These figures provide the range of
threat and opportunity that make up the risk characteristics of "A".
Now, let's add in the possibility of event "A4". The situation is shown in Figure 4-5. If the project team
estimates the probability of occurrence of "A4" as 0.4, then the probability of the events
on the other leg coming into the final summing node becomes equal to the "1-p"
of "A4", or 0.6. Adding
risk-weighted values, we come to a final conclusion that the expected value of
"A" is $4,840.
The most pessimistic outcome of "A" at this node remains -$1,000
since if "A2" should occur,
"A1" and "A4" will not; the most optimistic figure
remains $7,000 since if "A1"
occurs, then the other two will not. If "A4" should occur, then "A1" and "A2" will not. However, "A3" is deterministic; "A3" always occurs. So the optimistic value
with "A4" is $6,000: $2,000 +
$4,000. Obviously, $6,000 is less than the outcome with "A1".
If the analysis of "B" done in similar manner to that of "A"
should result in "B" having a value less than $4,840, the decision would be to
pick "A". Of course, the risk tolerance of the business must be accommodated. At
the decision node there will be an expected value for "A" and another of "B".
The project manager can follow the tree branches and determine the most
pessimistic outcomes. If the most
pessimistic outcomes fit within the risk tolerance of the business, then the
outcome, "A" or "B", is decided on the basis of best advantage to the project
and to the business. If the most pessimistic outcomes are not within the risk
tolerance of the business, and if there is not a satisfactory plan for
mitigating the risks to a tolerable level, then the choice of project defaults
to the decision policy element of picking on the basis of the risk to the
business. Risk managing the most pessimistic outcome is a subject unto itself
and beyond the scope of this book.
By now you may have picked up on a couple of key points about
decision trees. First, all the Ais and Bis must be identified in order to have a fair
and complete input set to the methodology. The responsibility for assembling
estimates for the Ais and Bis rests with the project
manager and the project team. Second, there is a need to estimate the
probability of an occurrence for each discrete input. Again, the project team is
left with the task of coming up with these probabilities. The estimating task
may not be straightforward. Delphi techniques [4] applied to bottom-up estimates or other estimating
approaches may be required. Last, the judgment regarding risk tolerance is
subjective. The concept of tolerance itself is subjective, and then the ability
of the project team to adequately mitigate the risk is a judgment as well.