Analogous vs Parametric Estimating: A Comprehensive Guide for Project Managers

What’s the best way to determine the project cost and duration when time and data are short?

When we talk about project management, there are many techniques, but the two most commonly used are Analogous Estimating and Parametric Estimating. This blog offers deep insights into the definitions, procedures, advantages, disadvantages, and key points of both methods, presenting a thorough comparison between the two: Analogous vs Parametric Estimating.

What is Analogous Estimating?

Analogous Estimating, which is also referred to as top-down estimating, utilizes historical data obtained from similar past projects to come up with an estimate of the cost or duration of the present project. Such estimation means are usually taken into consideration when very little is known about the ongoing project, and this approach relies heavily on the judgment of experts.

Key Things to Remember About Analogous Estimating

Quick and Cheap:

Due to the reliance on existing information, analogous estimating is relatively fast and cheap. It is not expensive because no complicated computation or acquisition of new and/or different information is required. It is fast because similar projects have already been conducted and all of the prior work has already been done. This method of estimating is of particular interest to organizations working with limited resources and/or deadlines.

Expert Judgment:

Selecting  relevant historical data by subject matter experts is very crucial. Their experience  ensures that appropriate analogues are selected and adjustments are made appropriately. Without being guided by the experts, there is a higher divergence between the past and the present-day project realities.

Low Level of Detail:

Early estimates are high-level, generally low details, and are useful during the infancy stages of projects. They give you a ballpark figure and not a granular level with breakdowns. This is useful for taking big decisions to get underway before detailed planning is carried out.

Depending on variabilities in accuracy:

Estimation depends highly on the degree of similarity of the past with the current project. If the compared projects vary very much either in scope, complexity, or environment, some misleading estimate might be generated. In such a case, keeping the reference data up to date, will enhance its reliability over a period of time.

Useful for Initial Planning:

It is one of the first points in a study to be considered for scoping an idea or a project. It helps the stakeholders to get an early feeling of whether the project is actually worth pursuing, so that the more detailed forecasting effort may not be wasted on something that might possibly never come to fruition. It also serves a useful intermediate step to support the next level of more detailed uncertainty following estimation as the project evolves.

What Information Would the Project Manager Get from Analogous Estimating?

• Rough Cost Estimates: Helps in setting preliminary budgets.
• Time Estimates: Gives the best idea of how long similar projects have taken.
• Resource Estimates: Gives an approximate number for men and material.
• Benchmarking: Provides for a comparison of project performance to historic data.

What is Parametric Estimating?

Parametric estimating relies upon statistical relationships amongst historical records and other variables (sometimes referred to as parameters) to create estimates regarding costs and durations. Parametric estimating is typically a more quantitative and data-driven process when compared to analogous estimating.

Key Things to Remember About Analogous Estimating

Data-Driven:

Parametric estimating uses the rules of mathematics and historical data to create costs and time estimates. Parametric estimating uses parameters such as cost per unit, time per feature or productivity estimates to produce estimates. As more records are used over time to develop and validate the estimate model, the estimate model will improve in its accuracy.

Scalable:

Parametric estimating can be scaled to more (or less) depending on the project size and complexity. The method is done using the same equations on a different numbers or parts which allows for a standard approach to be used across different sizes. This makes it particularly useful for organizations that deal with a lot of similar projects.

Higher Accuracy:

When historical data that are reliable and relevant are available for parametric estimates, these tend to be the most accurate. The mathematics behind the models decrease subjectivity, and as a result will limit estimate bias. Nevertheless, the limiters of accuracy in the estimates will depend on how well the specific parameters selected align with the project context at that present time.

Time consuming:

Estimation model development and validation takes a great deal of time and energy, as do the collection clean, consistent, and detailed historical data, and in general, collecting data can be daunting task. It has previously been pointed out that doing this is probably easiest within a mature organization, one that has developed the processes to track their performance.

Applicable at Different Levels:

Parametric estimating provides different levels of granularity, enabling uses for macro-level project forecasting as well micro-level task estimates. The “zooming” ability is useful during different stages of a project and for different needs of the project. Providing this duality makes parametric estimating a useful tool for strategic planning and operational execution.

What Information Would the Project Manager Get from Analogous Estimating?

• Cost Estimating: Accurate numbers based on unit rates.
• Time Estimates: Time estimates customized to specific project details, and work conditions.
• Expected Inputs: Accurate numbers regarding labor hours, materials, and equipment.
• Viewpoint of Cost and Time History: Recognizes trends in cost and time for types of work.

Analogous vs Parametric Estimating: A Side-by-Side Comparison

Feature	Analogous Estimating	Parametric Estimating
Approach	Top-down: Based on comparing with similar past projects.	Data-driven: Uses formulas and historical metrics.
Accuracy	Lower: Depends on how similar past projects are.	Higher: Relies on quality and relevance of data.
Time to Estimate	Quick to generate estimates.	Need time to gather and analyze data
Data Requirement	Minimal: Needs only basic historical info	Extensive: Requires detailed and structured data.
Cost of Estimation	Inexpensive and simple to apply	Higher: Involves more effort and resources.
Best Used In	Early project phases: For rough, initial estimates	Planning stages: For more precise budgeting and scheduling.
Flexibility	Hard to adjust once the analogy is chosen	Easily scalable based on project scope.
Level of Detail	Broad estimates without task specifics.	Breaks down estimates to specific components or units.

When to Use Analogous Estimating

Generally speaking, analogous estimating is most effective for:

• Projects are in their conceptual or initiation phases.
• Situations needing a rapid, high-level estimate.
• Organizations that either do not have a plethora of historical data or that do not have the resources to explore in depth what is entailed with a given scope of work.
• Projects that are very similar in scope and scale from past projects.

When to Use Parametric Estimating

Ultimately, parametric estimating is most effective for:

• Projects that have a rich pool of detailed historical data.
• Tasks that can be broken down and measured for every unit.
• Organizations that have sophisticated data analytics capabilities.
• Projects that require precise estimates of budget and time and scale.
  

Real-World Examples

Analogous Estimating Example: Retail Store Construction

A project manager is assigned to construct a new retail store on behalf of a national brand. In developing the project budget and schedule, she looks back to a recent similar project she completed in a nearby city the previous year.

Although this method is reasonable and provides an adequate basis for developing a budget and schedule, this approach assumes that market rates, material prices, conditions on the site, and other project variations did not change significantly from the last time she built. If any of these variables has changed, then her estimate would be inaccurate.

Parametric Estimating Example: Mobile App Development

A team of software developers is creating a new mobile application for a healthcare startup. Instead of making an educated guess on development totals, the team goes to their project database, where they have stored the total effort to create a variety of features of mobile applications in their previous project(s).

The team can further improve the estimate by scaling for screens with more or less complexity. This data driven approach helps with resource allocation, budgeting and setting appropriate deadlines.

Best Practices for Implementing Estimating Techniques

For Analogous Estimating:

• Use Acceptable Comparisons: Use previous projects that are similar in scope, complexity, and environment.
• Record Your Assumptions: Document all assumptions so that everyone is clear and can go back and check if needed.
• Use Experts: Take advantage of skilled members of your team to verify the relevance and to modify the estimates if needed.
• Document your Review and Update: Make adjustments to your estimates as new design detail becomes available or a change in scope occurs during the process of a project life-cycle.

For Parametric Estimating:

• Create Valid Data: Use validated, clean, reliable data to create a reliable estimate.
• Create Reusable Models: Create formulas or templates for all parts of similar purchases or recurring project parts.
• Use Tools and Software: Utilize estimating software to automatically create project estimates or utilize project management software for a more accurate estimation.
• Improve Estimating: Regularly update models based off of actual data performance to improve future estimates.

Combining Analogous and Parametric Estimation

Many organizations find success using a hybrid approach to project estimation that is broad using analogous estimating and refining with parametric as more knowledge becomes available. This allows them to pick up momentum for a project early on without later sacrificing accuracy.

First, start with  analogous estimating  to leverage similar projects from the past to get a quick high-level overview. It is a great way to check feasibility and get buy-in from stakeholders. Once you have a better sense of scope, the team can switch their estimate to  parametric estimating  where they will also apply the historical data and formulas to specific units (i.e., cost hour, hours task). This approach will allow teams to shift to parametric estimates as project details start to become clearer, while also improving accuracy without sacrificing speed during project planning.

✔️ The end result? A layered estimation process that allows you to have some speed and flexibility which is important for a complex project or one where things are changing!

Final Thoughts

It is important for project managers who want to have successful outcomes to understand the advantages and disadvantages of both Analogous Estimating and Parametric Estimating. While will frequently find Analogous Estimating vs Parametric Estimating to be a question of one or the other, the best project managers understand when and how to use each technique, or even both at the same time.

Regardless of whether your projects are in the construction, IT, manufacturing, or any other project-oriented industry, becoming proficient in these estimating techniques can greatly enhance your ability to develop effective planning and forecasting. Ultimately, the goal is not only to generate more accurate estimating, but also to provide a better starting point for project success.