Six Sigma Success

Six Sigma emphasizes a data driven, process approach known as the DMAIC (define, measure, analyze, improve, control) roadmap.
But what really makes a particular project successful?
Was it the DMAIC process itself?
Was it the leadership qualities of the Black Belt running the project?
Was it one piece of information that had been buried?
If so, was it an embarrassingly simple discovery or the result of an intense and sophisticated investigation?

Based on projects that have had some measure of success, here are seven main observations.

1. The DMAIC order works.
It makes logical sense, but that is not why it works. It provides a detailed roadmap as to what tool to apply when in a project.
How it works can best be seen by looking at problems encountered when it is not followed.

2. Good leadership may be critical.
The leader must demonstrate a serious and overriding commitment to the process and team members. His/her goal must be to make the project successful.

3. First-order scientific or engineering principles usually don’t solve the problem.
If they did, the problem would probably not have reached the Six Sigma project stage.

4. Tools like VSM, process mapping and FMEA can be valuable, but not when the work is done in a meeting room.
According to Bill Murray in the movie What About Bob? “There are two types of people in this world: those who like Neil Diamond and those who don’t.” In that statement, Murray gave us an analogy for the two types of engineers in this world: those who like to sit in a meeting room to theorize what’s going on and those who like to go to the workplace and find out.

5. There is little connection between formal education and the ability to come up with good ideas.
Those closest to the action often know more about the process than many of the people above them on the organizational chart. They frequently have knowledge the process or design engineer may not.

6. The interplay between theory and data is like a chicken and an egg. Which came first?
W. Edwards Deming emphasized the need to have a theory, even a hunch, before starting to solve a problem when he wrote, “Experience without theory teaches nothing.” However, the common phrase “letting the data talk to you” suggests using data first to generate theories.

In some projects, broad based, passive data collection may generate theories where virtually none existed.

7. The Pareto principle wins out.
The uniform principle (if it existed) would say many small parts play a roughly equal role in the improvement.
This would hold true if each of the DMAIC phases contributed between 15 and 25% to the overall success of the project. The Pareto principle often wins out, however, because one of the DMAIC phases generally contributes to most of the project’s success