What is Parametric Estimating?
Parametric estimating is a technique used to estimate project parameters (such as cost, duration, or effort) based on known variables or parameters derived from historical data. The key concept behind parametric estimating is to use a mathematical model or formula that links a specific parameter (e.g., cost, time) to measurable variables (e.g., cost per unit, time per task).
🔹 Key Objective: Use known parameters and relationships to predict the cost, duration, or effort for a project based on measurable factors or historical data.
How Parametric Estimating Works
Parametric estimating uses formulas or algorithms to calculate project estimates. These formulas are developed based on historical data and relationships between different project variables. For example, cost can be predicted based on the cost per unit of a specific resource, or time can be estimated based on the size of the project.
Steps Involved in Parametric Estimating:
1. Identify Key Variables
Identify the key parameters or variables that drive project costs, duration, or effort. For example:
- Cost: Cost per unit, labor rates, material costs, etc.
- Duration: Time per task, number of tasks, team velocity, etc.
- Effort: Effort per task, complexity, number of team members.
2. Use Historical Data
Gather data from similar past projects that show the relationship between the key variables and the project parameters. For example, if you know that 50 units of product cost $10,000 in a previous project, you can calculate a cost per unit.
3. Apply the Parametric Formula
Apply the formula or relationship between the variables to estimate the parameters for the current project.
đź“Ś Example Formula for Cost:
If the cost per unit is $200 and the project involves producing 100 units, the total cost can be estimated as: Estimated Cost=Cost per unit X Number of units
Estimated Cost=200 X 100=20,000
4. Refine and Adjust Estimates
Make adjustments based on specific project factors or constraints (e.g., inflation, labor rates). Also, consider factors like project complexity and uncertainty, which may affect the accuracy of the estimates.
5. Validate the Estimate
Cross-check the parametric estimates with other estimation techniques (e.g., analogous estimating or expert judgment) for consistency and to ensure the estimate is realistic.
Advantages of Parametric Estimating
âś” Accuracy: If the right historical data is available, parametric estimating can yield highly accurate estimates.
✔ Efficiency: It’s a fast method once the formula is set up, especially when reliable data and clear relationships are available.
âś” Data-Driven: Uses empirical data and real-world parameters, making it more reliable than judgment-based approaches.
âś” Scalability: The method works well for projects of varying sizes and complexities, as long as you have the right parameters to base the estimates on.
âś” Repeatable: Once the formula is established, it can be used for similar future projects, saving time in the estimation process.
Disadvantages of Parametric Estimating
❌ Data Dependency: It requires reliable historical data and a clear relationship between parameters for accurate estimates.
❌ Limited Applicability: It’s most effective for projects with well-defined and repetitive tasks. For unique or highly complex projects, it may not be suitable.
❌ Oversimplification: The estimates can be too simplistic if the parameters used don’t account for all the factors influencing the project’s cost or duration (e.g., unforeseen complexities).
❌ Requires Expertise: Formulating the correct mathematical model or formula requires domain-specific knowledge and expertise.
Common Examples of Parametric Estimating
1. Estimating Cost
- Formula:
Estimated Cost=Cost per Unit X Number of Units
đź“Ś Example:
If you know that the cost to produce 1 unit of a product is $1,000, and your project requires 200 units, the estimated cost will be: Estimated Cost=1000 X 200=200,000
2. Estimating Duration
- Formula:
Estimated Duration=Time per Unit X Number of Units
đź“Ś Example:
If a similar project required 5 hours to complete 1 module, and your project requires 10 modules, the estimated duration will be: Estimated Duration=5×10=50hours
3. Estimating Effort
- Formula:
Effort=Effort per Unit×Number of Units
đź“Ś Example:
If you know that developing one feature in the past took 40 hours, and your project requires 15 features, the total effort required will be: Effort=40Ă—15=600hours
Applications of Parametric Estimating
1. Construction Projects
In construction, parametric estimating is often used to estimate costs based on factors such as square footage, building type, and materials cost. For example:
- Cost per square foot = $200
- Building size = 1,000 sq. ft.
- Total cost = 1,000 sq. ft. Ă— $200 = $200,000
2. Software Development
In software development, parametric estimating can be applied to estimate effort based on the lines of code or function points.
- Cost per line of code = $10
- Number of lines of code = 5,000
- Total cost = 5,000 Ă— $10 = $50,000
3. Manufacturing Projects
Parametric estimation can be applied to estimate production costs based on unit production cost, the number of units, and time per unit.
- Cost per unit = $500
- Number of units = 200
- Total cost = $500 Ă— 200 = $100,000
4. Research & Development (R&D)
In R&D projects, time and effort can be estimated based on the effort per experiment or the number of iterations required.
Parametric Estimating Formula Example in Action
Let’s say you are estimating the cost of developing a new mobile app.
Historical Data:
From previous projects, you know that:
- Developing one mobile feature takes 120 hours of development time.
- The hourly labor rate is $100/hour.
You need to develop 15 features for the new app.
Step 1: Calculate Effort per Feature
Each feature will take 120 hours.
Step 2: Calculate Total Effort for 15 Features
Total Effort=120×15=1800hours
Step 3: Calculate Cost
Since the labor rate is $100 per hour: Total Cost=1800hours X 100per hour=180,000
Thus, the estimated cost for developing 15 features for the app would be $180,000.
Benefits of Parametric Estimating
âś” Accuracy: When the formula is based on solid data and well-established relationships, parametric estimates can be highly accurate.
âś” Quick to Apply: Once the formula and parameters are known, the process is fast and requires little additional work.
âś” Data-Driven: Relies on historical data, making it grounded in real-world performance.
âś” Scalable: Works for projects of varying sizes and complexities, as long as the appropriate parameters are available.
Challenges of Parametric Estimating
❌ Data Dependency: Requires accurate and reliable historical data to produce accurate estimates.
❌ Changes in Technology: If the new project uses new technology or methods that differ from historical data, the estimate might not be accurate.
❌ Over-Simplification: The relationship between parameters may be too simplistic for highly complex or novel projects.
❌ Requires Domain Expertise: Formulating the correct parametric model requires knowledge of the domain and accurate variables.
Conclusion
Parametric estimating is a powerful and efficient tool for making project estimates based on historical data and well-understood relationships between key parameters. It is particularly useful for projects with clear, measurable variables and when reliable historical data is available. However, the method relies heavily on the accuracy and relevance of the data and may not be suitable for highly complex or unique projects.
