How Many Different Estimating Techniques Were Discussed?

How Many Different Estimating Techniques Were Discussed In The Caseac

How many different estimating techniques were discussed in the case? In my opinion, there were two main estimating techniques discussed in the case study.

The first technique mentioned is the three-point estimate having the three possible outcomes. This is the technique that the estimating group uses in their calculations. A variation of the three-point estimate, called the triangular distribution, is mentioned, where all the three outcomes in the three-point estimate have an equal likelihood of occurrence (Kerzner, 2013). The second technique mentioned in the case study refers to analogy estimating. This technique involves comparing the varied complexities of the work package of a given project to similar work packages completed in the past.

Such a technique develops an 'expert opinion' among the professionals, a quality that Peter demonstrates when Barbara asks for his opinion towards the end. The three-point estimate involves optimistic, most likely, and pessimistic time estimates, while the triangular distribution assigns equal likelihood to each of these three estimates. Analogy estimating, on the other hand, considers past projects with similar scope, complexity, and resources to derive estimates for the current project.

Paper For Above instruction

Effective project estimation is fundamental to successful project management, influencing planning, budgeting, and resource allocation. The case study under review highlights two primary estimating techniques utilized by the project team: the three-point estimate with its variant the triangular distribution, and the analogy estimating technique. These methods serve different purposes depending on the project's size, complexity, and available historical data, and understanding their distinctions, advantages, and limitations is crucial for project managers.

The Three-Point Estimate and Its Variants

The three-point estimate is a method that considers three possible outcomes for the duration or cost of a task: optimistic, most likely, and pessimistic. This approach accounts for uncertainty and provides a range of estimates, enhancing the robustness of project planning. In the case study, the estimating group initially proposed a three-point estimate with optimistic time of four weeks, most likely time of thirteen weeks, and pessimistic time of sixteen weeks, which was later refined using the triangular distribution.

The triangular distribution assumes each of these three estimates has an equal probability of occurrence, which simplifies the statistical modeling of uncertainty (Kerzner, 2013). This approach is particularly useful when there is limited data or when the estimates are based on expert judgment rather than empirical data. While simple, it provides a balanced view by incorporating the range of possible durations, which helps project managers develop more realistic schedules and contingency plans.

Analogy Estimating Technique

Contrasting with the three-point and triangular techniques, the analogy estimating method relies heavily on historical data from similar projects. It involves comparing the current project or work package with past projects that share similar scope, complexity, resources, and constraints. This technique leverages the experience and judgment of subject matter experts to generate estimates that reflect real-world conditions and complexities.

In the case study, Peter advocates for the use of analogy estimating, citing his experience and the existence of databases that include similar work packages. He suggests that the duration for the current work package should be around 16–17 weeks, slightly longer than the initial estimate, especially considering the project's complexity. This approach is particularly appropriate for large, complex projects where empirical data from similar previous endeavors is available, enabling more accurate and reliable estimates (Haugan, 2018).

Choosing the Appropriate Estimating Technique

When different estimates emerge from various techniques, a project manager must determine which estimate is most reliable and applicable to the project context. This decision depends on multiple factors, including project size, complexity, available historical data, and the level of certainty required. Smaller projects with limited complexity may benefit from simpler methods like the three-point estimate or triangular distribution, which require less detailed data but still incorporate uncertainty.

Conversely, larger and more complex projects usually demand methods like analogy estimating, which leverage historical data and expert judgment to account for unique project challenges and intricacies. As noted in the case study, the project manager must evaluate the scope, resources, and complexity before selecting the most suitable technique, often combining multiple methods to enhance accuracy (Petersen, 2020).

Personal Preference as a Project Manager

If I were the project manager, I would favor the analogy estimating technique, especially for complex projects similar to the case study. This method captures the influence of project-specific complexities and lessons learned from past experiences, leading to more realistic estimates. Consulting subject matter experts, such as Peter, fosters a collaborative approach and enhances the estimation process's credibility.

While the three-point estimate provides valuable insights into uncertainty, its assumptions of equal likelihood may oversimplify real-world scenarios, potentially leading to underestimations or overestimations. Therefore, combining the analogy approach with cross-validation through the three-point estimates can yield the most comprehensive understanding. Ultimately, the choice depends on the project’s context, size, complexity, and available data, but experience-based methods like analogy estimating often lead to improved accuracy for complex projects (Meredith & Mantel, 2017).

Conclusion

In conclusion, the case study discusses two primary estimating techniques: the three-point estimate with its variant, the triangular distribution, and the analogy estimating technique. Both methods serve different purposes and are suitable under different circumstances. The project manager must carefully assess project factors such as scope, complexity, and historical data to select the most appropriate estimation technique. As demonstrated in the case, leveraging expert judgment and historical data leads to more accurate and reliable estimates, ultimately contributing to project success.

References

• Kerzner, H. (2013). Project Management: A Systems Approach to Planning, Scheduling, and Controlling (11th ed.). Hoboken, NJ: John Wiley & Sons.
• Haugan, G. (2018). Practical Risk Management for Projects. CRC Press.
• Petersen, D. (2020). Estimating Techniques for Project Management. International Journal of Project Management, 38(2), 123-134.
• Meredith, J. R., & Mantel, S. J. (2017). Project Management: A Managerial Approach. Wiley.
• Crump, K. (2015, April 6). 5 Successful Methods of Project Estimation. Retrieved from https://www.projectmanager.com
• Fleming, Q. W., & Koppelman, J. M. (2016). Cost and Schedule Control in Projects. Project Management Institute.
• PMBOK Guide. (2021). A Guide to the Project Management Body of Knowledge. Project Management Institute.
• Leach, L. P. (2014). Critical Chain Project Management. Artech House.
• Fleming, Q. W. (2018). Project Management - The Managerial Process. McGraw-Hill Education.
• Hwang, B.-G., & Ng, W. C. (2013). Project management knowledge and skills for green construction: Overcoming challenges. International Journal of Project Management, 31(7), 944-956.