PUTNAM RESOURCE ALLOCATION MODEL

 Putnam Resource Allocation Model: Optimizing Time, Effort & Cost

Efficient resource allocation is critical to the success of any software project. One widely recognized approach to understanding and managing this balance is the Putnam Resource Allocation Model, developed by Lawrence Putnam. This model helps estimate the time, effort, and cost involved in completing a software project of a given size.

What Is the Putnam Model?

Putnam's model is built upon the Rayleigh-Norden Curve, a mathematical model that describes how effort is distributed over time in a software project. He observed that staffing patterns in successful software projects closely followed the Rayleigh distribution.

Using this observation, he derived the software equation:

Putnam Software Equation:

L^3 = Ck × K × td^4

Where:

• L = Product size (in KLOC – Thousands of Lines of Code)
• K = Total effort expended (in person-months)
• td = Time to system and integration testing (i.e., development time)
• Ck = Technology constant that reflects development constraints

Understanding the Parameters

• L (Size): The estimated size of the software to be developed.
• K (Effort): The total person-months spent on the project.
• td (Time): The time taken until system/integration testing; often treated as the full development time.
• Ck (Technology Constant): Reflects how advanced and efficient the development environment is.

Typical values of Ck:

• Ck = 2 → Poor environment
• Ck = 8 → Good environment
• Ck = 11 → Excellent environment (with automation and engineering best practices)

Ck values can be fine-tuned using historical project data from the organization.

Rayleigh Curve & Optimal Staffing

Putnam proposed that staffing levels should follow a Rayleigh distribution over the project timeline:

• Initially, a small number of engineers is needed for planning and requirement gathering.
• Staffing levels increase during the design, coding, and testing phases.
• After implementation and unit testing, staffing gradually decreases as fewer resources are needed.

This curve promotes optimal utilization of personnel and avoids burnout or underutilization.

Impact of Schedule Compression on Cost

One of Putnam’s key insights is how compressing the schedule affects the effort and cost:

For the same product size, the total effort (K) is inversely proportional to the fourth power of development time (td).

Mathematically:

Effort ∝ 1 / td^4

This means that:

• A small reduction in schedule results in a large increase in effort and cost.
• Effort and cost rise exponentially with schedule compression.

Example:

Suppose the estimated development time is 1 year, but the project needs to be completed in 6 months (i.e., half the time).

According to Putnam's model:

Effort Increase = (1 / 0.5)^4 = 16x

Result:

Compressing the schedule by half increases the effort and cost 16 times. This demonstrates the high risk and inefficiency of unrealistic deadlines.

Conclusion

The Putnam Resource Allocation Model is a powerful tool in software project planning. It emphasizes:

• The importance of realistic scheduling
• The need for balanced resource allocation
• How technological capability impacts cost and effort