Parametric estimating is a technique that leverages statistical relationships between historical data and current project parameters to derive accurate cost estimates. By understanding the intricacies of this method, project managers can harness its potential for precise budgeting.

Essential Details:

  • Foundation on Parameters: The essence of parametric estimating lies in its direct correlation with specific parameters. For instance, using cost per square foot for construction projects or cost per mile for road construction.
  • Key Assumptions:
    • Direct Cost Relationship: Costs are directly proportional to the chosen parameter.
    • Stable Technology: The underlying technology and its relationship with the cost parameter remain consistent.
    • Scalability: The relationship is scalable, meaning the cost estimate for a 50-mile road would be half of a 100-mile road, assuming all other factors remain constant.
  • Versatility: Parametric estimating can be applied to various project metrics, including effort, time duration, and cost.
  • Mathematical Foundations: This technique thrives on mathematical and statistical relationships between historical data and current project parameters.
  • Cost Estimating Relationships (CERs):
    • Definition: CERs and mathematical algorithms provide the foundation for determining precise costs in parametric estimation.
    • Strengths: CERs offer quick estimates and are excellent predictors when derived from a robust statistical database.
    • Simplicity vs. Detail: While CERs can simplify the estimation process, it’s essential to delve into details when the data is available. Simplifications should be based on historical evidence, like assuming testing costs as a fixed percentage of the total cost.
    • Validation: All CERs should undergo rigorous validation using standard statistical methods to ensure their accuracy and relevance.
  • Industrial Engineering Standards: For specific industries, like manufacturing, precise standards and analyses can help determine costs down to minute details.
  • Quality & Quickness: The strength of parametric estimating lies in its ability to provide rapid yet high-quality estimates. However, it’s crucial to ensure the chosen CER or figure of merit is applicable to the current project.
  • Least Squares Best Fit (LSBF): This statistical method is optimal for deriving a CER that aligns closely with historical data.

Wrap-Up:

With its foundation in statistical relationships and historical data, Parametric estimating offers a structured approach to cost estimation. Project managers can achieve accurate and efficient budgeting by leveraging specific parameters and ensuring the chosen CERs are relevant and validated. As with all estimation techniques, it’s essential to be aware of its assumptions and limitations, ensuring that the derived estimates remain grounded in reality.