Multipoint Estimating

Multipoint Estimating is a technique used to estimate cost or duration by applying an average or weighted average of three inputs: an optimistic, a most likely, and a pessimistic estimate. This approach accounts for uncertainty and variability, making it more reliable than single-point estimates in environments where outcomes are not guaranteed.

Purpose and Characteristics

• Models Uncertainty – Captures the range of possible outcomes instead of a fixed value.
• Improves Accuracy – Produces more realistic expectations using weighted calculations.
• Inputs Variability – Considers best-case, worst-case, and expected-case scenarios.
• Feeds Risk Analysis – Commonly used in Monte Carlo simulations and contingency planning.

Common Formula (PERT Estimate)

The most common implementation is the Program Evaluation and Review Technique (PERT) estimate:

$$E=\frac{O+4M+P}{6}$$

Where:

• O = Optimistic estimate
• M = Most likely estimate
• P = Pessimistic estimate
• E = Expected estimate

Example Scenario

A task might take 3 days if everything goes well (optimistic), 5 days under normal conditions (most likely), and 10 days if issues arise (pessimistic). The weighted estimate would be:

$$E=\frac{3+4(5)+10}{6}=5.5\text{ days}$$

Mermaid Diagram: Multipoint Estimating Flow

flowchart LR
    A[Optimistic Estimate] --> D[Weighted Formula]
    B[Most Likely Estimate] --> D
    C[Pessimistic Estimate] --> D
    D --> E[Expected Duration or Cost]

This structure shows how three inputs feed into a weighted calculation, resulting in a more reliable output.

Why Multipoint Estimating Matters

• Reduces Risk of Under/Overestimation – By considering a range, it’s harder to be blindsided.
• Builds Confidence – Provides a stronger basis for forecasts and planning decisions.
• Enables Smarter Contingency Planning – Helps determine appropriate buffers or reserves.

See also: Three-Point Estimating, Most Likely Duration, Optimistic Duration, Pessimistic Duration, PERT, Monte Carlo Simulation.