Project Task Estimation Techniques

Hi all,

As far as we talk about project management, it’s important to remember task estimation. Estimating tasks accurately is key for effective project management. Different estimation techniques provide various approaches to gauge the time and resources required for completing project tasks. Let’s discuss the most popular estimation techniques, that should be in your arsenal.

Top-Down Estimation

Top-down estimation involves evaluating the overall project scope and then breaking it down into smaller components. This technique relies on the experience and historical data from similar projects to provide a high-level estimate. Use top-down estimation when you have a general understanding of the project’s scope and need a quick, high-level estimate.

It’s ideal during the initial phases of a project when detailed information is not yet available. This method is beneficial for projects with a lot of uncertainty or when quick decision-making is required.

For example, you’re tasked with estimating the development effort for a new mobile app. Based on previous experience with similar projects, you might estimate that the app will take approximately 6 months to complete. 6 months are 100%. Divide these 100% between the tasks based on their complexity.

Bottom-Up Estimation

Bottom-up estimation starts with a detailed breakdown of the project into specific tasks. Each task is estimated individually, and the total estimate is derived by summing the estimates of all tasks. This technique leads to more accurate estimates. It is most useful when detailed information about the project is available. It is ideal for complex projects where each task can be broken down and estimated individually.

For example, for the same mobile app project, you break down the tasks into UI design, back-end development, API integration, testing, and deployment. You estimate each task separately: UI design (2 weeks), back-end development (4 weeks), API integration (2 weeks), testing (2 weeks), and deployment (1 week). Summing these estimates gives a total of 11 weeks for the project.

Analogous Estimation

Analogous estimation uses historical data from similar projects to estimate the current project. This method is particularly useful when there is limited information about the new project but sufficient data from past projects.

Employ analogous estimation when you have historical data from similar projects and need a quick estimate based on past experiences. It is particularly useful in the early stages of a project when detailed planning is not yet complete but similar projects can provide a reliable reference point.

In case, you are working on a CRM system upgrade and have data from a previous, similar upgrade project that took 3 months. Given the similarities between the projects, you estimate that the new CRM upgrade will also take approximately 3 months.

Parametric Estimation

Parametric estimation involves using statistical relationships between historical data and project variables. This method applies mathematical models to estimate effort based on parameters such as size or complexity. It is effective when you have quantifiable data and can use statistical relationships to estimate effort. It is useful for projects with well-defined parameters where historical data or industry benchmarks provide a basis for estimation. This technique is often used for tasks or components with predictable patterns based on previous experiences.

If developing a software module typically requires 40 hours per feature, and the new module needs 10 features, you use parametric estimation to calculate the total effort. The estimate is 40 hours per feature multiplied by 10 features, resulting in 400 hours.

Three-Point Estimates

Three-point estimation uses three estimates to account for uncertainty: the best-case scenario, worst-case scenario, and most likely scenario. This technique provides a more nuanced estimate by considering different potential outcomes.

Three-point estimates are beneficial when you want to account for uncertainty and variability in your estimates. Use this technique when you have some historical data or expert judgment to provide optimistic, pessimistic, and most likely scenarios. This method helps in situations where the project or task is complex, and a single estimate may not fully capture potential risks.

For example: To estimate the time required for a complex software feature, you determine:

? Best Case: 20 hours

? Worst Case: 60 hours

? Most Likely Case: 35 hours

Using the simple average formula:

Estimate = (20 + 60 + 35)/3 = 38.33 hours

PERT (Program Evaluation and Review Technique)

PERT is a probabilistic technique that calculates an estimate by considering the optimistic, most likely, and pessimistic durations. It provides a weighted average to accommodate variability in task durations. PERT is particularly useful for projects with high uncertainty and variability.

Use it when you need to consider different possible outcomes and want a weighted average estimate that accounts for uncertainty. This technique is ideal for complex projects where precise durations are difficult to predict and variability needs to be incorporated into the estimate.

For a website design phase, you estimate:

? Optimistic Time: 10 days

? Most Likely Time: 15 days

? Pessimistic Time: 25 days

Using the PERT formula:

PERT Estimate = (10 + 4 * 15 + 25)/6 = 17.5 days

What-If Analysis

What-if analysis explores different scenarios to understand their potential impact on the project. By considering various possibilities, you can better prepare for uncertainties and make informed decisions.

Use this technique when there are significant uncertainties or potential changes in project scope, resources, or timelines. It helps in preparing for different scenarios and understanding how changes might affect project outcomes.

In a project with a tight deadline, you might conduct a what-if analysis to address:

? Scenario 1: What if the project scope increases by 20%? Analyze how this change could affect your timeline and resources.

? Scenario 2: What if a key team member is unavailable for two weeks? Estimate the impact on the project schedule and develop mitigation strategies.

Benchmarks and Historical Data

Benchmarks and historical data involve comparing current project tasks with similar tasks from past projects. This technique uses empirical data to provide a realistic estimate based on proven outcomes. Use benchmarks and historical data when you have access to data from similar past projects and want to base your estimates on proven outcomes. This technique is most effective when historical data is reliable and relevant to the current project.

When estimating the development time for a new feature, you review data from similar features developed in past projects. If those features typically took 3 weeks, you estimate that the new feature will also require around 3 weeks, adjusting for any specific differences.

Application of these estimation techniques can help you enhance the accuracy of your project planning and manage resources, timelines, and project outcomes better.

Thanks! Share your thoughts in the comments :-)

Best, Olha