Uncertainty is an ever-present part of life, whether in personal decisions or managing complex IT projects. Clear and transparent decision-making is essential—but often difficult—when navigating system migrations, deploying new applications, or addressing security risks.
Howard Marks famously said, “There’s a big difference between probability and outcome. Probable things fail to happen—and improbable things happen—all the time.” This insight underscores the importance of thinking in probabilities rather than relying solely on expectations of certainty.
By adopting a probability-based mindset, we can make more informed choices, manage risks effectively, and communicate with greater clarity. I’ve begun exploring this approach myself, refining my understanding through reading and listening to insightful podcasts. Here’s what I’m learning about applying probability thinking in both personal and professional contexts.
Why Think in Probabilities?
Traditional decision-making often relies on binary thinking: “Will it work, or won’t it?” This black-and-white approach oversimplifies complex scenarios, leading to poor decisions. On the other hand, probability thinking introduces nuance by evaluating the likelihood and impact of different outcomes. It’s not about being 100% certain—it’s about being better prepared.
Understanding Probability Levels
Here’s a simple framework to express probabilities clearly:
Probability RangeDescriptive TermExample
| Probability Range | Descriptive Term | Example |
| 0% – 5% | Very Unlikely | “A meteor strike is very unlikely.” |
| 5% – 20% | Unlikely | “Rain is unlikely tomorrow.” |
| 20% – 40% | Possible | “There’s a possible chance of delays.” |
| 40% – 60% | About Even | “We have a 50/50 shot at winning.” |
| 60% – 80% | Likely | “The project is likely to succeed.” |
| 80% – 95% | Very Likely | “The product launch will very likely go well.” |
| 95% – 100% | Almost Certain | “It’s almost certain we’ll meet the deadline.” |
Using these terms can help you communicate more clearly and avoid misunderstandings.
Conveying Probabilities Precisely
Instead of vague terms like “maybe” or “definitely possible,” use straightforward language to highlight the likelihood:
- Direct Probability Language:
60% Probability:
- “There is a 60% chance of [event].”
- “[Event] is more likely than not, with a 60% probability.”
- “The likelihood of [event] occurring is moderate to high, around 60%.”
Less than 20% Probability:
- “There is less than a 20% chance of [event].”
- “[Event] is unlikely, with a probability below 20%.”
- “The chances of [event] happening are low, at under 20%.”
2. Comparative Language:
- “The probability of [event A] (60%) is significantly higher than that of [event B] (less than 20%).”
- “[Event A] is three times more likely than [event B].”
3. Descriptive Probability Ranges:
- “This scenario falls in the ‘likely’ range.”
- “There’s a moderate-to-high probability (60%) of this happening.”
- “With a probability below 20%, it’s considered a low-likelihood event.”
4. Visual Comparisons:
Use a probability spectrum:
0% ————— 20% ————— 60% ————— 100%
Unlikely Possible Likely Certain
- “On this scale, [event] falls near the 60% mark, while [other event] is closer to the 20% range.”
5. Professional Tone for Reports:
- “Based on our analysis, the probability of [X] is estimated at 60%, suggesting it is more probable than not.”
- “In contrast, [Y] has a probability below 20%, indicating a low likelihood of occurrence.”
Using precise language avoids ambiguity, enhances credibility, and improves decision-making.
Practical Examples
Investing:
Instead of thinking, “This stock will go up,” assess the likelihood:
- 60% chance it rises 10%
- 30% chance it stays flat
- 10% chance it drops 5%
This approach gives a balanced view of risk and reward, helping you make better investment decisions based on expected outcomes rather than hope.
Project Management:
If a project has a 50% chance of finishing on time, don’t plan around the best-case scenario. Prepare for potential delays:
- Develop contingency plans
- Allocate extra resources
- Set realistic expectations with stakeholders
This mindset reduces surprises and ensures smoother project execution.
Daily Life:
Should you carry an umbrella? If there’s a 30% chance of rain and you’ll be out for hours, it might be worth it. Instead of waiting for certainty, this small precaution could save you from discomfort.
Practical Example: Cloud Migration Project
Scenario:
Your organization plans to migrate legacy systems to the cloud. As the project lead, you must assess and communicate potential risks to stakeholders.
Step 1: Identify Possible Outcomes:
- Successful migration with no issues
- Minor issues causing slight delays
- Major issues requiring rollback
- Critical failure leading to extended downtime
Step 2: Assign Probabilities:
- Successful migration: 60% probability (Likely)
- Minor issues: 25% probability (Possible)
- Major issues: 10% probability (Unlikely)
- Critical failure: 5% probability (Very Unlikely)
Step 3: Communicate with Confidence:
Instead of vague statements like, “We might face some issues,” present your findings clearly:
- “There’s a 60% chance of a smooth migration, a 25% chance of minor issues, and only a 5% risk of critical failure. Our analysis shows a positive expected outcome overall.”
Conclusion
Thinking in probabilities transforms uncertainty from a challenge into a tool for better decisions. Whether planning a cloud migration, deploying new software, or addressing security threats, this approach ensures you’re prepared for various outcomes—not just the one you hope for.
By applying probability thinking, you can navigate complexity more confidently and clearly, setting your projects up for success.