Unlike most project management tools which focus on automating features or workflow, parametric, predictive modeling tools help organizations model and optimize project feasibility and ensure that projects meet established delivery guidelines. Parametric modeling takes its name from the project parameters or variables that are modified during the project simulation process.
Parametric models are built from a set of mathematical equations. These may be standard equations found in reference books, proprietary equations developed by consultants or vendors, or some combination of the two. In order for parametric models to have any validity they must be based on or proven using actual project data. It is the sophistication of the data analysis methods and the extensiveness of the underlying project data which determines the effectiveness of a modeling solution.
Parametric methods are very useful for subjecting uncertain situations to the rigors of a pre-defined and proven mathematical model. They can usefully embody a great deal of prior experience and are less biased than human thought processes alone.
Commercial parametric modeling solutions typically offer extensive graphical feedback, thus making them easier to use. Commercial models also offer other benefits, including support for risk-based inputs, sizing “wizards” and numerous assessment mechanisms to improve the accuracy of estimates.
Want to know more about parametrics? Software Sizing, Estimation, and Risk Management, a 541-page hardcopy reference book by Daniel Galorath and Michael Evans is available at Amazon.com.
Galorath Incorporated has worked for over two decades to help organizations better plan for and control project risks, costs, duration and quality. In developing the SEER line of project management tools, they have leveraged modeling technology and project-applicable knowledge bases to replicate actual project outcomes.
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