Parametric Estimating is an estimating technique that uses algorithms or mathematical models to calculate cost or duration based on historical data and project parameters. This approach relies on established relationships between variables, such as cost per unit or duration per task, to produce consistent and scalable estimates.
It is particularly effective when historical data is reliable and project elements are repetitive or measurable.
Key Characteristics
- Data-Driven – Based on historical metrics and actual performance
- Scalable – Adjusts estimates based on size, quantity, or complexity
- Efficient – Reduces time spent on manual estimation
- Repeatable – Produces consistent results across similar projects
Example Scenarios
- Estimating software development time using hours per story point
- Calculating construction costs using cost per square foot
- Forecasting documentation effort based on pages per hour from past projects
Why Parametric Estimating Matters
- Improves Accuracy – Enhances reliability of estimates through data modeling
- Supports Planning – Enables precise resource and budget forecasting
- Reduces Bias – Minimizes subjectivity in estimation
- Enhances Predictability – Strengthens consistency across project estimates
See also: Analogous Estimating, Bottom-Up Estimating, Program Evaluation and Review Technique (PERT), Multipoint Estimating, Three-Point Estimating.