Understanding when and how to use strategic decision analysis for better outcomes
This decision analysis tool is designed for anyone facing complex choices with uncertain outcomes. It's particularly valuable when you need to compare multiple options that have different risks, benefits, and probabilities of success.
When the consequences of being wrong are significant and you need to be confident in your choice.
When you can't pursue all options and need to prioritize where to invest time, money, or effort.
When each option could lead to several different results with varying probabilities.
When different stakeholders value different outcomes, and you need to balance their interests.
When you need to decide between "safe bets" and "high-risk, high-reward" options.
When you need to justify decisions to others or get team alignment on the best path forward.
Our tool uses three complementary analysis methods that together give you a complete picture of your decision. Each method answers a different crucial question about your options.
What it answers: "Which option is likely to give me the best results on average?"
Expected Value calculates the weighted average of all possible outcomes for each option. It considers not just what might happen, but how likely each outcome is and how much you care about it. This gives you a single number that represents the "expected" result if you could repeat this decision many times.
Option A - Social Media Campaign:
Option B - TV Advertisement:
Result: Social media campaign has higher expected value, making it the better choice on average.
When to trust Expected Value: When you're making similar decisions repeatedly, when you can afford average outcomes, or when you want to maximize long-term results. Be cautious when you can't afford a bad outcome even if the average is good.
What it answers: "How much uncertainty and variability does each option have?"
Risk Assessment measures how spread out the possible outcomes are for each option. A "low-risk" option has outcomes that are all fairly similar - you know roughly what to expect. A "high-risk" option might lead to either spectacular success or significant failure. This helps you understand the trade-off between predictability and potential upside.
Option A - Government Bonds:
Option B - Startup Investment:
Result: Bonds are predictable but limited upside; startup investment is unpredictable but high potential.
When to prefer low risk: When you have limited resources, can't afford failure, or need predictable outcomes. When to accept high risk: When you can afford to lose, have multiple opportunities, or need breakthrough results.
What it answers: "Which of my assumptions matter most, and what if I'm wrong about them?"
Sensitivity Analysis tests how much your decision would change if your estimates were different. It shows which assumptions are "critical" (small changes flip your decision) versus "robust" (large changes don't matter much). This helps you identify where to spend more time researching and where you can be confident despite uncertainty.
Option A - Quick Launch:
Option B - Delayed Launch with More Features:
Result: Quick launch is more robust to estimation errors; delayed launch depends heavily on your assumptions being correct.
High sensitivity means: Your decision depends heavily on uncertain assumptions - do more research on these factors. Low sensitivity means: Your decision is robust even if your estimates are somewhat wrong - you can proceed with confidence.
The real power comes from using all three methods together. They often tell different parts of the story:
Sometimes the "best" option by expected value is too risky for your situation, or depends too heavily on optimistic assumptions. This comprehensive analysis helps you make decisions that fit your specific context and risk tolerance.