How to use the DMAIC Methodology: 5 Steps + Example

How to use the DMAIC Methodology

DMAIC is a popular Six Sigma process in the world of statistics and business. There’s a good chance you’ve heard the term before, but what exactly is it? Each letter represents a particular part of the methodology. DMAIC stands for Define, Measure, Analyze, Improve, and Control.

Whether the industry is manufacturing, marketing, retail, military, or HR, Six Sigma practitioners can use the DMAIC process for improvement projects. Following the five steps allows businesses to systematically find and fix issues, ultimately boosting productivity and quality. This article will explain the DMAIC process steps and provide a DMAIC process example.

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Why the DMAIC Process is Important

The DMAIC process is important because it allows you to improve your business by creating a systematic approach for identifying problems, creating solutions, and measuring the success of your product or process improvement project.

First, the DMAIC process helps you get an overview of the situation and identify potential problems with your product or service. It’s also important to understand what success looks like in order to know how to measure it.

Second, the DMAIC process helps you look at your resources and see what you have available to tackle the problem. This will help you decide what’s feasible and what isn’t—and that’s especially important if you have a budget or timeline to stick to for improvements.

Third, the DMAIC process gives you a plan for tackling those issues so that when you’re looking at your data and making decisions about moving forward, they’re based on facts rather than feelings or assumptions.

5 Steps in the DMAIC Process


In the DMAIC Define Phase, you will define the problem or opportunity. You’ll define what you want to improve in your process. This involves defining the goal and developing an understanding of what success will look like. You will also identify the current situation and how it compares to your desired outcome. This includes identifying any constraints or limitations and determining if there is adequate support for achieving success.


In the DMAIC Measure Phase, you will measure key aspects of the current process by collecting data to obtain quantitative evidence about its current state. You’ll compare it with the ideal state. You’ll measure defects or other metrics that indicate problems with your process. This evidence helps you identify where improvement opportunities exist to drive future actions.


In the DMAIC Analyze Phase, you will analyze the data to identify root causes. You’ll analyze trends in your data using statistical techniques such as control charts or ANOVA analysis to determine if there are any factors impacting quality that you can eliminate from your process. You may also use decision models such as Pugh charts or cause-and-effect diagrams to evaluate alternatives and select appropriate solutions for implementation.


In the DMAIC Improve Phase, you will improve the process by implementing solutions based on what you learned during the analysis. These solutions require clear specifications so they can be implemented consistently. In addition, you should document these changes in case they need to be replicated later.


In the DMAIC Control Phase, you will control the new process to prevent problems from recurring. You’ll monitor results after making improvements to ensure they are working as planned.

DMAIC Process Example

So how does this all come together in a real-life scenario? Let’s walk through a hypothetical scenario of how a nonprofit organization uses DMAIC methodology.

Let’s say the nonprofit company wants to increase its fundraising success with outbound calls made to clients who signed up for newsletters on their website but chose not to make an online donation.

1. Define Stage:

The company would first need to define what success looks like with outbound calls and how it will be measured.

In this case, the company aimed to increase conversion rates from 45% to 50%. The company used the length of contact and conversion metrics to define successful and unsuccessful calls. They defined a successful call as lasting longer than two minutes. Additionally, they defined conversion as when a donation was made during a call.

2. Measure Stage:

Key aspects of the call experience would then be identified and monitored.

Now that the Six Sigma project team has defined the goal and metrics, they must collect data about the successful and unsuccessful calls. In this case, the company created a process map to understand the current process. They recorded data regarding several factors, such as the script used during the call, the time of day the outbound team made the call, and how much time had passed since the user had signed up for the newsletter before the outbound team made the call.

The project team brainstormed potential explanations for the unsuccessful calls. The conversion rate was the primary metric, so a fishbone diagram was utilized to depict the link between the many factors at play.

3. Analyze Stage

Data would be collected and analyzed to identify any areas where the calls were more likely to lead to a successful call or a conversion.

After gathering information, the next step is to analyze it statistically. The project team devised a preliminary hypothesis testing the call data. This testing revealed that the time of day the outbound team made the call and the time lag between the newsletter sign-up and the outbound call both had a substantial impact on the success of the call and the conversion rate.

Design of experiment (DOE) tools assessed the significant factors from hypothesis testing. The designed experiment optimized critical factors and responses. The DOE results showed how critical factors interacted and affected the main measure, including the time of day and the appropriate sign-up-to-call lag time.

This analysis showed that afternoon calls made within 24 hours of the online sign-up were most effective.

4. Improve Stage

Implement solutions to improve the call experience in those areas.

There was initially at least a 24-hour lag between sign-up and follow-up calls because the outbound team had been using a third-party firm to compile lists of users who had signed up for the newsletter but had not donated. With the help of the newly implemented internal reporting system, the outbound team could generate this list within hours, significantly reducing call times. The outbound team also began prioritizing afternoon calls.

The team documented these changes and updated the process map to reflect the improvements.

5. Control Stage

New processes would be monitored to ensure that successful calls and conversions continue.

The Six Sigma project team completed three months of monitoring after the company implemented the improvement measures. According to an analysis, the project’s conversion rate increased to 52% from 45%, achieving the project goal.


The Six Sigma DMAIC process is an effective tool that can be used in any industry. It gives businesses the ability to analyze and improve their processes, leading to better results. By reviewing the example and following the five steps of the DMAIC Process – Define, Measure, Analyze, Improve and Control – businesses can create meaningful changes in their operations.

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