Mastering Estimation: The Key to Balancing Accuracy and Precision in Project Management

In the early stages of a project manager's career, it’s easy to think that detailed planning for every possible outcome will guarantee success. However, overplanning can actually slow down progress, waste time, and create complexity. Projects often change, and sticking too tightly to a plan that no longer fits can lead to frustration and delays. This is where the concept of the Last Responsible Moment comes in. The "Last Responsible Moment" means waiting until the latest possible time to make a decision, while still ensuring you don’t miss any important deadlines. By delaying decisions until you have the most information, you avoid unnecessary changes or rework, making the project more efficient. It’s about being responsive rather than reactive, allowing you to make better, more informed choices at the right time.

When planning a project, it's essential to consider the following variables:

1. Development Approach (Predictive, Adaptive, Hybrid): This determines how the project will be managed and delivered. A predictive approach plans everything upfront, while an adaptive approach allows for flexibility. A hybrid approach combines both methods.

2. Project Deliverables: Deliverables are the tangible results or products the project must provide. Defining these early ensures clear scope and avoids uncontrolled growth.

3. Compliance/Regulatory Boundaries: Projects must adhere to legal and regulatory requirements to avoid potential legal or financial risks.

4. Organizational Process Assets (OPAs) and Enterprise Environmental Factors (EEFs): OPAs refer to internal processes and resources that support the project, while EEFs are external factors like market conditions or regulations that impact the project.

5. Market Conditions: Market conditions influence the project’s relevance, success, and demand, especially if launching a product or service.

6. Team Skills: The skills of the project team directly affect the project's efficiency and ability to meet goals. A well-trained and capable team is crucial to success.

7. Stakeholders' Attitude and Requirements: Understanding the expectations and influence of stakeholders ensures the project aligns with their needs and that relationships are managed effectively.

Planning and estimating are closely connected, as accurate estimates provide the foundation for a realistic project plan. Estimating helps determine the time, cost, and resources needed, while planning organizes these estimates into actionable steps to achieve project goals.

What are the key terms to know when dealing with estimations ?

1. Range: Range refers to the span of possible outcomes in an estimate, indicating the degree of uncertainty or flexibility in the prediction.

• Deterministic Estimating: Involves a single-point estimate where there’s little or no uncertainty (e.g., estimating a task will take exactly 5 days).
• Probabilistic Estimating: Incorporates uncertainty by providing a range (e.g., the task might take between 3 and 7 days).
• Absolute Estimating: Gives a specific value or duration (e.g., 10 hours for a task).
• Relative Estimating: Compares tasks or components by estimating them in relation to each other (e.g., task A is twice as long as task B).

2. Accuracy: Accuracy reflects how close the estimate is to the actual result once the task is completed. Higher accuracy means less deviation from the real outcome.

3. Precision: Precision refers to the level of detail and consistency in the estimate. Even if estimates are very precise (e.g., to the decimal point), they may not always be accurate if based on incorrect assumptions.

4. Confidence: Confidence is the level of certainty in the estimate, often influenced by the amount of data or experience supporting it. Higher confidence means you trust that the estimate is likely to be accurate.

The difference between accuracy and precision is crucial in fields like project management, statistics, and data analysis. Both terms relate to how close estimates or measurements are to the true value, but they refer to different aspects of this closeness.

Accuracy measures how close an estimate or measurement is to the actual or true value. It reflects the correctness of the result. The closer the result is to the actual value, the more accurate it is.

In mathematical terms, accuracy can be expressed as the mean absolute error (MAE) or mean squared error (MSE):

• Mean Absolute Error (MAE):

Where:

- Xi is each individual estimate or measurement.

- Xtrue is the actual or true value.

- n is the number of observations.

• Mean Squared Error (MSE):

The smaller the MAE or MSE, the more accurate the result.

Precision measures how consistently estimates or measurements are close to each other, regardless of whether they are close to the actual value. High precision means the results are very close together but not necessarily close to the true value.

Precision can be expressed mathematically as the standard deviation of the estimates or measurements:

Where:

• Xi is each estimate or measurement.
• Xˉ is the mean of the estimates.
• n is the number of estimates.

A lower standard deviation or variance indicates higher precision because the estimates are close together.

To recap it briefly:

• Accuracy tells you how close your measurements are to the true value.
• Precision tells you how close your measurements are to each other.

And if you like numbers:

When accuracy increases, precision improves as well because both concepts relate to how close your estimates or measurements are to a target. As your results get closer to the true value (higher accuracy), they naturally become closer to each other (higher precision). For example, if all your estimates are accurate, they're also grouped tightly around the target, which means they're more precise too.