The organization treats estimates as certain when they are inherently uncertain
What Is False Precision?
| IS | In Practice |
|---|---|
| Expressing uncertain outcomes as exact values | “We will finish on March 18th” |
| Overstating accuracy beyond what data supports | Giving exact numbers from rough estimates |
| Collapsing variability into a single-point estimate | One date, one number |
| Treating estimates as facts | “That’s the plan” becomes “that’s reality” |
| Using precise language without confidence levels | No mention of risk or probability |
| Creating illusion of certainty | Stakeholders believe outcomes are predictable |
| Ignoring or hiding uncertainty and variability | No ranges, no error margins |
| Encouraging commitment to guesses | Plans treated as guarantees |
| Mistaking precision for accuracy | More decimals = “more correct” |
| Simplifying complexity into deterministic outputs | Complex systems reduced to fixed timelines |
What is Not False Precision?
| IS NOT | In Practice |
|---|---|
| Probabilistic forecasting | “85% chance by end of March” |
| Expressing ranges with uncertainty | 20–25 items instead of 23 |
| Explicit acknowledgment of variability | “This depends on X and Y” |
| Confidence-based communication | 50%, 85%, 95% scenarios |
| Rough estimates presented honestly | “This is a rough guess” |
| Scenario planning | Best / likely / worst with rationale |
| Adaptive forecasting | Updating based on new data |
| Separating forecast from commitment | “This is not a promise” |
| Data-limited humility | “We don’t have enough info to be precise” |
| Accuracy over precision | Less exact, more truthful |