WGU C201 TASK 2 MAXIMIZING PROFIT: DECISION TREE
ANALYSIS FOR DRUG STRATEGY| LATEST UPDATE WITH
COMPLETE SOLUTIONS
C201 Task 2
A1. Business Question
What strategic action should Major Pharmaceutical Company (MPC) take to develop a new drug,
exploit the existing drug for new applications, or do nothing, to maximize profit of uncertain
future market conditions (favorable vs. unfavorable)?
Justification for Using Decision Tree Analysis
Decision tree analysis is the best approach because it accounts for uncertainty and multiple
possible outcomes.
The scenario describes two states of nature, a favorable market and an unfavorable market—each
with probabilities for every strategic alternative. Exactly the type of condition of decision trees
was modeled, and decisions followed by uncertain events.
B1. Strategic alternatives have different payoffs depending on the market conditions.
The report provides levels and per-unit profit values for each market state and each alternative.
These values translate directly into payoffs, which decision trees use to calculate expected values
for comparison and evaluation.
The CEO requests a preferred and backup action based on quantitative evaluation.
Decision trees allow the CEO to:
• map each decision path,
• apply probabilities,
• calculate expected payoffs,
• Identify the decision with the highest expected value (EV)—which is what the CEO
wants to see in the report.
Decision trees clarify the relationship between decisions and uncertain outcomes by visually
showing:
• the decision node (the strategic choice),
, • the chance nodes (market conditions),
• The payoffs and expected values
The method ensures clarity for executive decision-making.
Table
Alternative Probability (Low / Demand (Low / Profit per Unit
High) High)
Develop New Drug 0.62
0..72 1,,341
Exploit Existing 0.47
0..64 1,,475
Drug
Do Nothing 0.83
0..82
C.
Decision tree analysis & results
I computed the payoff for each outcome as:
Payoff=(Demand)× (Profit per unit) {Payoff} = {Demand}) times {Profit per unit})
Payoff=(Demand)× (Profit per unit)
and the expected value for each alternative is:
(All payoffs and EVs reported to two decimals.)
Payoffs & expected values
Alternative Payoff (Low) Payoff (High) EV
Develop New Drug 747.10 2,691.42 2,147.01
Exploit Existing 849.29 2,573.25 1,952.62
Drug
Do Nothing 200.03 605.90 532.84
Decision tree diagram
• Decision node (square) with branches for the three actions.
• State-of-nature (chance) nodes (circles) with Low/High branches labeled with
probabilities and calculated payoffs (two decimal places).
ANALYSIS FOR DRUG STRATEGY| LATEST UPDATE WITH
COMPLETE SOLUTIONS
C201 Task 2
A1. Business Question
What strategic action should Major Pharmaceutical Company (MPC) take to develop a new drug,
exploit the existing drug for new applications, or do nothing, to maximize profit of uncertain
future market conditions (favorable vs. unfavorable)?
Justification for Using Decision Tree Analysis
Decision tree analysis is the best approach because it accounts for uncertainty and multiple
possible outcomes.
The scenario describes two states of nature, a favorable market and an unfavorable market—each
with probabilities for every strategic alternative. Exactly the type of condition of decision trees
was modeled, and decisions followed by uncertain events.
B1. Strategic alternatives have different payoffs depending on the market conditions.
The report provides levels and per-unit profit values for each market state and each alternative.
These values translate directly into payoffs, which decision trees use to calculate expected values
for comparison and evaluation.
The CEO requests a preferred and backup action based on quantitative evaluation.
Decision trees allow the CEO to:
• map each decision path,
• apply probabilities,
• calculate expected payoffs,
• Identify the decision with the highest expected value (EV)—which is what the CEO
wants to see in the report.
Decision trees clarify the relationship between decisions and uncertain outcomes by visually
showing:
• the decision node (the strategic choice),
, • the chance nodes (market conditions),
• The payoffs and expected values
The method ensures clarity for executive decision-making.
Table
Alternative Probability (Low / Demand (Low / Profit per Unit
High) High)
Develop New Drug 0.62
0..72 1,,341
Exploit Existing 0.47
0..64 1,,475
Drug
Do Nothing 0.83
0..82
C.
Decision tree analysis & results
I computed the payoff for each outcome as:
Payoff=(Demand)× (Profit per unit) {Payoff} = {Demand}) times {Profit per unit})
Payoff=(Demand)× (Profit per unit)
and the expected value for each alternative is:
(All payoffs and EVs reported to two decimals.)
Payoffs & expected values
Alternative Payoff (Low) Payoff (High) EV
Develop New Drug 747.10 2,691.42 2,147.01
Exploit Existing 849.29 2,573.25 1,952.62
Drug
Do Nothing 200.03 605.90 532.84
Decision tree diagram
• Decision node (square) with branches for the three actions.
• State-of-nature (chance) nodes (circles) with Low/High branches labeled with
probabilities and calculated payoffs (two decimal places).
