The DMAIC Process of Six Sigma

The DMAIC Process of Six Sigma
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  • 0:00 Six Sigma
  • 0:43 DMAIC
  • 3:13 Advantages
  • 4:20 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

Six Sigma offers a clear, scientific way to solve problems that arise in business. But how, exactly, can it be implemented? In this lesson, we'll examine the most common Six Sigma process, DMAIC, including what it is and its advantages.

Six Sigma

Serena has a big problem. She owns a company that produces motors for airplanes, but every once in a while, their motors stall mid-flight. It only happens in one out of every thousand planes, but that's still too often. After all, every time it happens, people's lives are at risk.

Serena needs to find a solution to this problem as soon as possible. One of her friends has recommended that she try Six Sigma, which is a problem-solving program for businesses. It focuses on identifying problems and using a systematic, scientific approach to solving them.

To help Serena solve the problem of the stalling airplane motors, let's look at the heart of Six Sigma: the DMAIC process.


Serena has to figure out the cause of her stalling airplane motors, and she's heard that Six Sigma might be the solution. But she still doesn't know exactly what the process is for Six Sigma. The Six Sigma process is often abbreviated DMAIC, which stands for define, measure, analyze, improve, and control.


The first step in the process is to define the problem and goals of the intervention. In this case, Serena's problem is that some of her airplane motors stall and she wants to reduce the times this happens. If she can avoid it all together, that would be perfect.


Next, Serena needs to measure the problem. This involves figuring out how often the problem occurs. In Serena's case, this is one in every thousand planes. Serena will also want to gather information on when the problem occurs, for example, what the stalling motors have in common.


After that, Serena will want to analyze the results to find the cause of the problem. She'll want to look at the measurements she took in the previous step and look for patterns through statistical analysis. For example, she might discover that the stalling motors are all made of the same materials, or that they are made with the same construction, or that they are all installed in low temperatures. She will need to look at all the data she has and analyze it to find the most likely cause of the stalling motors.


The fourth step in the DMAIC process is for Serena to improve the process by implementing a change based on research. Whatever Serena identifies as the cause of the problem in the analyze step, she'll want to change in the improve step. For example, if she decides based on her analysis that the materials are a key problem for the airplane motors, she might want to change the material she uses.


Finally, Serena will want to control the outcome by continuing the program. Serena needs to do two things in this step. First, she'll want to keep changes in place. That is, once she changes the materials and finds that the number of stalling motors goes down, she won't want to go back to her old materials. That would cause the stalling problem again!

But there's another part to continuing the program and that is for Serena to try out new solutions. For example, by changing the materials, Serena has managed to reduce the number of stalling motors from one in a thousand to one in two thousand. That's a big improvement, but it's still not perfect, so she'll want to go back to the beginning of the DMAIC process to research and implement another solution. She might find, for example, that the number of stalling motors is improved even more when the motors are installed at a warmer temperature.

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