OMBA 102 · Unit 6 of 7
Decision Analysis
Data, Statistics and Managerial Decisions
Start unit · 5 lessons →Learning objectives
After completing this unit, you will be able to:
- Structure decisions with decision trees and rollback analysis
- Run sensitivity and scenario analysis on key assumptions
- Quantify the value of information before commissioning studies
- Apply multi-criteria decision making when objectives conflict
- Communicate analytical recommendations with explicit tradeoffs
Why this matters
Spreadsheets and models only matter if they change a choice. Unit 6 connects analysis to decisions: trees, scenarios, and structured recommendations that executives can act on.
Unit overview
Work through the five lessons below in order.
| # | Lesson | Core idea |
|---|---|---|
| 1 | Decision Trees | Sequential choices and outcomes |
| 2 | Sensitivity and Scenario Analysis | Which assumptions matter |
| 3 | Value of Information | Pay for data or decide now |
| 4 | Multi-Criteria Decision Making | Weights, tradeoffs, transparency |
| 5 | Communicating Analytical Recommendations | Decision-ready outputs |
Connection to applied work
Build a decision tree or scenario table for your project's main recommendation. State what would change your mind.
Practice
- Draw a decision tree for a launch/delay decision with probabilities and payoffs.
- Identify the three assumptions that swing your project NPV most.
- Estimate whether a survey is worth its cost using value-of-information logic.
- Score three options on two criteria with explicit weights.
Knowledge check
- How do you rollback a decision tree?
- What is a tornado chart used for?
- When is more analysis not worth it?
- Why expose weights in multi-criteria decisions?
- What belongs in an analytical recommendation memo?
Key takeaways
- Decision analysis makes tradeoffs and assumptions visible.
- Scenarios beat false point certainty.
- Communication closes the loop from data to action.
- Finish lessons before assessments.
Unit assessment
Complete each section below. Score 80%+ on the quiz to finish this unit's assessment.
Exercises
Apply what you learned in this unit with structured practice.
Deliverable
300–500 word analysis document saved to your portfolio under OMBA 102.
Rubric
- • Framework applied correctly (not just named)
- • Specific evidence from a real example
- • Clear recommendation with tradeoffs acknowledged
- • Professional writing with source citation
Deliverable
Problem solutions + 150-word reflection in your OMBA 102 workbook.
Rubric
- • Attempted all practice items before checking answers
- • Honest reflection on errors
- • Identifies a specific review action
Model / spreadsheet
Build or extend a spreadsheet model tied to this unit.
Deliverable
Structured model document (2+ pages) · One-paragraph summary of key insight from the model · Screenshot or export saved to portfolio
Rubric
- • Assumptions stated explicitly
- • Logic is auditable (formulas or steps visible)
- • Output answers a specific business question
- • Sensitivity or scenario considered
Knowledge quiz
Check your understanding before marking the unit complete.
1. In decision tree rollback, chance nodes are evaluated using:
2. Launch now: $5M if strong demand (p=0.55), −$2M if weak (p=0.45). EMV(launch) equals:
3. Sensitivity analysis on a tree primarily shows:
4. Value of perfect information (EVPI) is computed as:
5. A market study costs $200k and changes launch EMV from $1.85M to $2.3M. Expected value of sample information (EVSI) before cost is:
6. In a weighted scorecard, criteria weights should sum to:
7. $3M already spent on tooling should appear in a launch-or-delay tree as:
8. A BLUF analytical memo for executives should lead with: