Rob is responsible for estimating a work package that entails considerable uncertainty regarding time and cost. Due to this uncertainty, he will make low, average, and high estimates. Which estimating approach is Rob using?

Rob is using the Three-Point Estimating approach. This technique involves making three different estimates to define an approximate range for an activity’s cost or duration. The three estimates reflect different levels of optimism:

1. The Optimistic estimate (O) - This is the best-case scenario where everything goes as well as it possibly can, with minimal costs and time required. 2. The Most Likely estimate (M) - This is the estimate based on a realistic assessment of the resources, dependencies, and challenges that the work package might entail. It is regarded as the most probable outcome. 3. The Pessimistic estimate (P) - This is the worst-case scenario, considering potential difficulties and unforeseen obstacles that could inflate costs and delay completion.

These three estimates can then be used to calculate an expected value or an average estimate that gives a weighted account of all three scenarios. This could be done simply by averaging the three estimates or by using a formula such as the PERT (Program Evaluation and Review Technique) estimate, which weights the Most Likely estimate more heavily: Expected Time = (O + 4M + P) / 6.

Three-point estimating helps to provide a more nuanced and comprehensive evaluation of uncertain tasks compared to a single-point estimate, allowing better risk management and planning.

Extra: When estimating tasks, especially in project management, it’s important to consider the variability and uncertainty inherent in the tasks. Single-point estimates can be overly simplistic and may not adequately capture the risks associated with a task or project. Three-point estimating addresses this by providing a range that can be used to understand the potential variability and to perform risk analysis.

Moreover, the three-point estimating approach acknowledges that estimates are predictive models of the future, which naturally involve uncertainty. By preparing for different scenarios, project managers can plan for contingencies and develop more robust schedules and budgets. The approach also encourages thorough analysis by prompting estimators to think through the best-case, most likely, and worst-case scenarios, leading to more informed decision making.