How much bias
is in your forecast?

Enter three demand scenarios and discover how much bias is silently distorting your forecast.

Most forecasts are wrong not because of math — but because of human bias. The Weighted method gives the Most Likely 4× more influence, pulling the result toward reality.

Enter your three estimates below to see the difference.

Calculate your scenario

Weighted Forecast Calculator

Optimistic + (4 × Most Likely) + Pessimistic

Optimistic Best-case scenario

Most Likely Weighted 4× — highest influence

Pessimistic Worst-case scenario

📌 Example pre-filled — edit values and recalculate

⚠️ Optimistic is lower than Pessimistic — check your scenario order.

Simple Average

—

(O + ML + P) ÷ 3

Weighted Average ⭐

—

(O + 4×ML + P) ÷ 6

↔

Weight Distribution

Optimistic

—

Most Likely

—

Pessimistic

—

Most Likely carries 4/6 ≈ 67% of total weight

The Four Forecasting Methods

📊

Quantitative

Based on historical data. Uses math to identify patterns and project the future.

Data-driven

🔗

Associative

Uses leading indicators — external data that predicts demand before it occurs.

Causal

🧠

Qualitative

Based on judgment and experience. Right tool when historical data is absent or volatile.

Judgment

🔀

Combination Methods

Qualitative judgment adjusts quantitative results — or a similar product serves as proxy. Most real-world forecasts, including the Weighted Average above, are combination methods.

Hybrid

⚠️ Key distinction: Qualitative methods depend more on human judgment and have lower statistical reproducibility — but they are the right tool when historical data is absent, volatility is high, or when launching a new product.