As a project manager, you’re constantly under pressure to manage time, cost, and scope — otherwise known as the project’s triple constraint. The most challenging aspect of the three is accurately estimating the project’s cost.
Poor estimates can lead to project delays, budget overruns, unhappy stakeholders, and damage to your reputation. That’s why it’s best to avoid them at all costs (no pun intended). Fortunately, there are a few proven techniques to help you maximize your success with number crunching.
Analogous estimating is a powerful technique that enables you to determine a project’s cost by comparing it to similar projects from the past. It’s a tried-and-true approach that can save you time, money, and headaches. So let’s dive in and explore how it works!
What is analogous estimating?
Analogous estimating (also known as ‘top-down’ estimating) is a technique used in project management to estimate a project’s cost, duration, or other attributes based on past project characteristics.
It involves looking back at projects similar in scope, complexity, and other relevant factors and using that information to derive figures for your new endeavor.
The four types of analogous estimates
There are four ways to approach this.
Single-point or absolute value estimate
This type involves selecting a single value that represents the estimate for the project. For example, if you’re estimating the cost of a software development project, you might look at a similar project that costs $100,000 and use that as your single-point estimate.
This type involves using a ratio to compare the current project to a similar completed project. For example, if you’re estimating the duration of a construction project, you might look at a similar project that took 12 months to complete and use a ratio of 1:2 to estimate that your project will take 24 months because it’s twice as big.
This type involves providing a range of possible values for the estimate based on the range of values from past projects. For example, if you’re estimating the cost of a marketing campaign, you might look at similar campaigns that cost between $50,000 and $100,000 and provide a range estimate of $75,000 to $90,000.
This type involves providing three estimates: an optimistic estimate, a pessimistic estimate, and a most likely estimate. The “optimistic estimate” represents the best-case scenario. The “pessimistic estimate” represents the worst-case scenario. And the “most likely estimate” represents the most likely to occur. For example, if you’re estimating the duration of a software development project, you might provide an optimistic estimate of 6 months, a pessimistic estimate of 12 months, and a most likely estimate of 9 months.
Benefits of analogous estimating
There are many benefits to this type of estimate, like:
- Saves time and effort: Analogous estimating can be a relatively quick and easy way to estimate project factors. Instead of starting from scratch, project managers can use information already available from past projects.
- Improves accuracy: By looking at past projects, project managers can better understand the factors that may impact their current project. More accurate estimates ultimately lead to better project outcomes. It’s also an excellent technique to use alongside other estimation methods because it’s relatively quick.
- Increases stakeholder confidence: When project managers can provide accurate estimates for project costs and back this up with tangible evidence using past projects, stakeholders are more likely to have confidence in the project, improving overall project buy-in and support.
Disadvantages of analogous estimating
As with all estimation techniques, there are limitations to consider, such as:
- Limited accuracy: Analogous estimating assumes that the current project is similar enough to past projects to make accurate comparisons. However, no two projects are exactly alike, which may make direct comparisons difficult.
- Lack of detail: Analogous estimating typically relies on high-level project characteristics, such as scope and complexity, which sometimes results in estimates lacking detail or specificity, making it difficult to plan.
- Dependence on historical data: Analogous estimating relies on historical data from past projects. If this data isn’t readily available or relevant to the current project, then you won’t be able to use this technique.
When to use analogous estimating (and when not to)
Here are some factors to consider:
When to use analogous estimating
- When there are similar past projects that provide transferrable information
- When there is a need for quick and relatively simple estimates without the need for detailed analysis or complex mathematical models
- When there is limited data available for making estimates, and you can use historical data to supplement or validate other estimation methods
- When there is a need for a baseline estimate for comparison to other estimation methods
When not to use analogous estimating
- When the current project is significantly different from any past project or when there is no relevant historical data available
- When accuracy is critical, and you need detailed and precise estimates
- When you need high confidence in the accuracy of estimates, such as for regulatory compliance or financial reporting (in these cases, analogous estimating is fine, but you might want to pair it with another technique rather than use it as the standalone approach)
- When you need a rigorous, data-driven approach to estimation, such as for complex engineering or scientific projects
The four estimating techniques: where analogous estimating fits in
Parametric estimating involves using statistical models to estimate project parameters based on historical data and project characteristics. Bottom-up estimating involves estimating the time and cost required for each task or component of a project and then aggregating those estimates to arrive at an overall estimate. And three-point estimating involves making three estimates for each task or activity: a best-case estimate, a worst-case estimate, and a most-likely estimate.
Analogous estimating is similar to parametric estimating in that it relies on historical data to make estimates. However, while parametric estimating relies on statistical models to estimate specific project parameters, analogous estimating is a more high-level approach that involves comparing the current project to past projects to make estimates minus the statistical calculations.
How to do analogous estimation: a step-by-step guide
Here’s how to apply this helpful estimation technique.
Step 1: Identify the project for estimation
Before you can even think about estimating the costs of a project, get a clear understanding of what the project entails. Define the project’s scope, set the project’s objectives, and determine the key deliverables.
Once you’ve identified the project, take the time to gather all the relevant information you need, including project plans, requirements documents, work breakdown structures, and historical data from similar projects. The more information you have, the more accurate your estimate will be. And remember to involve critical stakeholders in the estimation process, including project managers, subject matter experts, and other team members who deeply understand the project requirements. By involving stakeholders early on, you can ensure everyone is on the same page and that your estimate considers all the necessary factors.
Step 2: Identify a similar project
When we say ‘similar project,’ we don’t necessarily mean identical. It’s unlikely you’ll find a project that is an exact match. Instead, look for projects that have similar features or requirements. For example, if you’re estimating the costs of building a new website, you might look for a similar project involving a website with similar functionality or complexity.
Remember that you must do more than blindly apply the historical data from a similar project to the new project. You need to consider any differences between the two projects, such as differences in scope, team composition, or external factors like market conditions. After all — using the data from a website almost identical to the one you plan to build will be of little help if the technology and market have entirely changed.
Step 3: Collect data from the similar project
This step is about gathering the historical data you identified in step two, including project plans, budgets, timelines, and actuals from the previous project. The goal is to understand how the previous project performed and what went into getting it off the ground. Interview team members who worked on the project to get their insights into how things went and review project documentation like financial records to understand the project’s costs and timelines better.
Once you’ve collected all the relevant data, take the time to analyze it. Look for patterns, trends, and insights that can inform your estimate. For example, you might notice the previous project exceeded the budget in certain areas, leading you to adjust your estimate for the new project accordingly. That brings us to our next step.
Step 4: Adjust the data
This step involves taking the data you collected in step three and adjusting it to account for differences between the similar project and the new project you’re estimating. For example, a similar project might have had a larger team, a longer timeline, or a different budget. Use this information to adjust the data to reflect the unique aspects of the new estimate. These differences can significantly impact your estimate, so give them due attention!
It’s essential to be transparent about your assumptions and adjustments. Document the changes you’re making, and be clear about why you’re making them. It’s also wise to consider the uncertainty and risk associated with the new project. Be sure to factor this into your estimate, and consider including contingency plans or buffers to account for unexpected events.
Step 5: Develop the estimate
Think of this as an extension of step 4 but with a more contextual focus. You’ll want to factor in any external or environmental factors that could impact your estimate. For example, if your project is in a different location or market than the past projects you’ve analyzed, you’ll need to consider how that might affect your estimate. You’ll also want to consider technological changes or other factors impacting things.
Once you’ve considered all of these factors, you can develop your figures. Using a range of values rather than a single, specific number is helpful. For example, you might estimate that your project will cost between $100,000 and $150,000 rather than saying it will cost exactly $125,000. This range gives you some flexibility and helps you account for any uncertainties or variables that could impact your estimate.
Step 6: Validate the estimate
Congratulations on reaching the final step! Now it’s time to validate it to ensure it’s accurate and realistic. This step helps you avoid potential problems down the line, so don’t skip it!
To validate your estimate, you’ll need to compare it to actual data from past projects or other sources. Delve into project reports, industry benchmarks, or expert opinions for information. The goal is to find relevant data for your project and use it to validate your estimate.
You’ll want to look for any significant discrepancies when comparing your estimate to the actual data. If your estimate is significantly higher or lower than the real data, you must dig deeper to understand why. Look for factors you didn’t consider and assess whether your estimate was too optimistic or pessimistic.
One way to validate your estimate is to create a sensitivity analysis, which involves varying some of your estimate’s key assumptions or inputs and seeing how the results change. For example, you might vary the materials cost or the time required for specific tasks. By doing this, you can better understand how sensitive your estimate is to different factors and make any necessary adjustments.
Project management software and analogous estimating
Using project management software — like Backlog — makes collecting and organizing data from similar projects a breeze. The software allows you to search and filter through past projects efficiently, saving time and effort that you would otherwise spend manually sifting through project reports and documents.
Once you have found a similar project, the software can help you collect data on various aspects of the project, such as duration, effort, and cost. With just a few clicks, you can even calculate key performance indicators (KPIs) for the project, such as the earned value or schedule performance index. This is just one way that project management tools can do the heavy lifting for you.
Another advantage of using project management software is that it can help you adjust the data for your current project. For instance, if a similar project was developed using a different technology stack, the software can account for the learning curve associated with the new technology. This may involve adding extra time to the estimate for training and familiarization with the new technology.
Finally, project management software can help you validate the estimate by tracking actual data as the project progresses. You can easily compare the estimated values with actual data, track any differences or discrepancies, and adjust future estimates accordingly. This helps improve accuracy and stay on top of things as the project progresses, two essential things every project manager wants.