Which estimating technique uses a statistical relationship between historical data and other variable?

The biggest challenge that an organization faces is determining the efforts and costs associated with a new project. That’s why at least 16% of construction projects exceed the estimated cost. And transparent estimation process is the only key to ensuring the projects are on track and within the budget defined.

Traditional approaches to estimation included studying past projects, identifying the lookalike data, and crunching the numbers to estimate the current project costs and timeline. However, it would also mean you may go overboard with your budget or timeline. So this wasn’t exactly the best estimation technique.

We were basing the estimations at a macro level, whereas it is essential to go slightly to a micro-level before you completely understand.

The parametric estimation technique is a modern formula that allows you to be slightly more accurate about the cost and timeline definitions.

Here we will take you through everything you need to know about parametric estimation.

Parametric Estimation: Introduction

This estimation technique is statistically evolved, wherein an equation governs the results. It is one of the most accurate techniques to calculate the total time, cost, and resources for a particular project.

In this technique, the manager will combine the statistical and historical data to identify a statistical relationship between the variables involved.

For example, in a delivery project, if you are supposed to produce 20 bungalows in a posh area with modern architecture and furnishing. But first, you will check how much time it took for a similar project in the past.

Say it took six months to complete a project with 40 bungalows involved. So, you use a ratio-proportion connect to identify the total time it will take for 20 homes.

The equation used to establish the connection is:

E_parametric = A_old/P old * P curr

Parametric estimate = Historical value of the cost and time/historical value of the parameter * value for the new project.

You can use this equation to log your results whenever you want to calculate the approximate estimate for cost, time, or resources.

Top Advantages of Using Parametric Estimating

If you are still unsure of whether you should go ahead with parametric estimating, here are a few advantages that you should look at.

Accuracy

One of the biggest reasons to incorporate parametric estimating techniques is its accuracy. Considering it establishes a statistical correlation between the different parameters (historical and current), it provides higher accuracy than other techniques. It also ensures that you can reuse models for other projects to gain accurate results. To make the model reliable, you should include as much raw data as possible.

This image showcases how parametric estimating can accurately define the schedule and staffing for large IT projects.

Up-to-speed outcomes

When you use parametric estimation to deliver the estimates, you are on the positive side of accuracy. More people are likely to believe the outcome of this estimation technique. You would notice that stakeholders will be ready to initiate the project based on this value. As a result, it is a very usable and helpful technique. The outcomes use the past data, but the outcome is not a guesswork. It is entirely dependent on the calculations made from the past data.

Reduced efforts

When estimating for a particular project, you need to be up-to-speed with your results. However, the estimation technique can take time and reduce your project manager’s productivity in most cases. That’s why parametric estimation is popular. It is not only quick but quite effective too. You don’t need to build an assessment at a granular level to gain answers. Instead, you need to have a list of all the operational parameters to identify the total estimate for the project.

Flexible

Lastly, parametric estimating is flexible as it allows you to maintain the historical data wherever needed to build your estimate. Therefore, you can pick and choose the information you need. However, it will still identify the relationship between the data within the timeline defined.

How to Improve Parametric Estimating Techniques?

When incorporating this technique to enhance your estimation, it is equally important you establish the best practices. Then, you can improve the outcomes with the proper methods to include.

This image shows how parametric estimating using statistical models is done. It shows how probability methods are used to find the most reliable and successful model.

Incorporating the best practices can help find a reliably interesting model.

Incorporate the correct determinants

This is the first step toward incorporating the right approach for parametric estimating. If the determinants of the statistical equation are not correct, you may not get a proper estimation.

For example, if you consider the number of units from the past project but consider the total area of the project delivered, it will determine the estimate incorrectly.

Sit with your data to identify the exact variables that will fetch you desirable results. Once you are sure of the variables, it becomes easier to track the equation.

Identify sufficient raw data

Raw data is essential for parametric estimation. Your entire calculation is based on the historical data. That’s why you should get enough evidence from past project data.

If you haven’t done enough work but are aware of someone in the market, get the data from those projects. Once you have sufficient data, building statistical co-relations and models becomes more accessible.

You will be able to diversify the scenarios and even identify the variables to define minimal changes in the processes. This will eventually help you create a reliable estimate.

Align estimates to your goal

Before you begin the estimation work, you need to determine the goal of your task. It is possible that you need to identify a cost-efficient model for working on this project. For example, your goal could be to complete the tasks in the said period.

In all these cases, if you work on the parametric estimating technique without focusing on the goal, you won’t get the desired results.

It is essential to determine the goal and then build the estimate around it. Then, you will be able to modify or optimize the models to meet your defined objectives.

This best practice will also help you identify this particular project’s possible opportunities and challenges.

Incorporate it into strategies

When you have created an estimate using the parametric estimating technique, you should also ensure it is part of the management strategies. Then, when you incorporate it into your project strategy, you will notice fewer chances of failing your project.

For example, you will know where you had overestimated the timeline and can optimize the resources on the go.

It will also give you a chance to learn from your mistakes in this project while working on another similar project.

Maintain transparency

This is a prominent practice but seldom used when you begin working on the project or the estimate. Various teams collaborate to identify and offer a suitable parametric estimating output. You will have a research team employing the best practices to get desired variables and determinants.

It is essential to collaborate and ensure everyone understands how you are planning the project and what are some of the things you will consider when scaling the project.

Asking for feedback from the execution teams while building the project estimate can help you. They can tell you the realistic timeline and what things to consider.

It will help you build a more capable and efficient estimate that will help complete the project within the budget and timelines.

Don’t estimate on assumptions

There are two things to consider here – don’t estimate on assumptions and don’t assume your estimates.

When you get data, you should also get a complete understanding of how the data works. Ask your teams to explain the data that you don’t understand so that you can estimate with a thorough understanding of how things work.

Secondly, when you have defined an estimate, don’t allow people to assume what it means. Instead, sit with your team and explain how you worked on the estimate and its meaning.

Assumptions can kill even the most accurate parametric estimating results from being executed.

Manage within the budget

We have already seen that the budget would be pre-defined in some cases. As the manager, you need to work within this defined budget. Once you have estimated using all the available variables, you can now work on optimizing it. Make sure you have defined the parametric estimation around the budget.

It is important to avoid keeping numbers at their lowest. Instead, you should have a realistic and data-backed estimate.

Identify the risks

When estimating a project, you are likely to include the opportunities but miss out on the risks. However, when you start working around the estimate defined, you realize that these risks are pivotal in execution.

That’s why you should also include the risks when planning the estimate. For example, check how you manage the timelines, budget, and resource allocation if it doesn’t meet the prepared figures.

This contingency plan needs to be developed when estimating and calculating the risks involved.

Create a work breakdown structure

It is essential to break down every project into a series of tasks to establish the best outcomes with your parametric estimation techniques. In addition, when estimating using an accurate system, it is essential to evaluate the timeline, cost, and even the total resources taken for each task.

The breakdown structure presented before you helps you manage the tasks better. When you estimate the tasks individually, it helps establish the tasks better.

This will help you identify the exact execution timeline and the methods to workaround.

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Limitations of Parametric Estimation

• Parametric estimating can be quite time-consuming, which is one of the reasons project managers avoid it. It adds to the overall costs. It would help if you also were resource-heavy to build the ideal model.
• You need the ideal data source and reliable data for building the statistical models.
• You cannot use it for the entire project in most cases. You will be using it for parts of the tasks you are managing.
• In case some parameters differ for the current and old projects, you may not be able to rely on the project data completely for parametric estimating.
• Despite the amount spent and resources invested, you may not get reliable results if you get low-quality historical data with parametric estimating.

Analogous vs. Parametric Estimation

Before we dive into analogous versus parametric estimation differences, let’s look at the analogous estimation technique.

So, when you use data from previous similar kinds of projects to deliver an estimate, it is known as an analog estimate. You will base your estimations on the experience of the team or the overall project history.

Let’s understand the difference between these two estimations.

Data-backed estimation

While both the techniques use past project data to build the estimation, there is a minor difference in how they connect.

A. In the analog estimation technique, you will use the historical data and estimate accordingly. So, it would be a rough calculation.

B. On the other hand, with parametric estimating, you will build a statistical equation that will help you calculate the exact timeline and resources for your requirement.

The usage

Analog estimation techniques are primarily used in the early project stages, while the parametric estimation is used when there is a reliably good amount of data available.

Usable

This estimation technique is used only when you get similar data, i.e., from projects akin to yours. However, that is not the case with parametric estimation. You need to get reliable data, and the managers will use it to define an equation or model. This model will be used to calculate and estimate the number of hours and resources.

Accuracy

As analog estimation is dependent on assumptions and is roughly defined, it is less accurate. However, parametric estimating is considered to be more accurate as it evolves from a model and is calculated based on a statistical equation.

Efforts involved

When it comes to the efforts involved, it is higher with a parametric estimating than analog. In addition, you will notice that the costs are higher with parametric as it includes statistical tools and models.

Considering these differences, it is essential to note that you can use both methods as and when required. You should ideally use analog if you want to offer a rough estimate. However, if you build a more reliable estimate, you should go with parametric estimating.

Conclusion

It is important to use the right estimation method at the right time. If your project is in the early stages, parametric estimating may not resolve your issues.

However, if you have enough understanding of the project and can build a good amount of data, you should use parametric estimating. This technique will help accurately identify the total resources needed and the total time you are likely to take.

You should understand the use cases and be clear about the limitations before incorporating the technique.

Which estimating technique uses a statistical relationship between historical data and other variables?

What cost estimating technique uses a statistical relationship between relevant historical data and other variables to calculate a cost estimate for project work?

Which estimating techniques use statistics?

What is analogous estimating in project management?