Decision Trees: A Visual Tool for Analyzing Decisions
- Imagine you're a business owner deciding whether to launch a new product.
- You have options, but each comes with risks and potential rewards.
How do you choose the best path?
Definition
Decision tree
A decision tree is a visual tool that helps businesses analyze different decision options by considering potential outcomes and risks.
Key Components of a Decision Tree
1. Nodes
Nodes represent decision points, chance events, or outcomes.
- Decision Nodes (Squares/Rectangles): Points where a choice must be made.
- Chance Nodes (Circles): Points where an outcome depends on probability.
- Outcome Nodes (Triangles): End points showing the result of a decision path.
Use different shapes for each node to avoid confusion.
2. Branches
Branches show possible choices and associated probabilities.
- Decision Branches: Connect decision nodes to possible actions.
- Chance Branches: Connect chance nodes to potential outcomes, each with a probability.
A decision node might have branches for "Launch Product" or "Do Not Launch".
3. Expected Value
Expected value is used to calculate potential financial outcomes by weighing each outcome by its probability.Note
Expected Value (EV) = (Probability of Outcome 1 × Value of Outcome 1) + (Probability of Outcome 2 × Value of Outcome 2) + ...
NoteExpected value helps quantify the average outcome but doesn't guarantee a specific result.
Building a Decision Tree
Step 1: Define the Decision
- Start with a clear decision question.
- Example: "Should we invest in a new marketing campaign?"
