What Makes a Six Sigma project successful

7/27/2019 What Makes a Six Sigma project successful

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3.4What Makes a Six SigmaProject Successful?

by Joseph G. Voelkel

j uppose you just completed aSix Sigma project on which youwere either a Champion, a belt(Master Black Belt, Black Belt or GreenBelt) or a team member. You are nowin a lessons leamed meeting and havebeen asked to give your opinion onthe project. You can be totally honestat this meeting; your voice will beelectronically modified, and yournotes will be transcribed, so flinchingis not a concern. You are asked:1. Do you think the project wassuccessful? Please explain youranswer and include how youdefine "successful."2. If it was successful, what werethe contributors to its success? Ifit wasn't successful, what were

the contributors to its lack ofsuccess?Th e people asking you these ques-tions are very interested in your opin-ion and insight, so they wantcomprehensive answers.Contributors to Success

Six Sigma emphasizes a data driven,process approach known as theDMAIC (define, measure, analyze,improve, control) roadmap. As a pro-fessional statistician, I naturally wantto believe being both data driven andprocess oriented are very important.But what really makes a particularproject successful? Was it the DMAICprocess itself? Was it the leadershipqualities of the Black Belt running theproject? Was it one piece of informa-tion that had been buried? If so, was itan embarrassingly simple discoveryor the result of an intense and sophis-ticated investigation?My experience using project solvingapproaches to make improvementsboth precedes and includes Six Sigmaprojects. My experience with SixSigma projects has largely occurredwith teams working on their first pro-jects, while my experience with otherprojects has primarily occurred in my

ty advisor' or indirectly through theexperiences of my students. Thisexperience has most often taken place

Seven observationsbased on years ofexperience.in the hard sciences, and my terminol-ogy below will reflect that.Seven Observations

Based on projects that have hadsome measure of success, I have gath-ered seven main observations.1. The DMAIC order works. Itmakes logical sense, but that is notwhy it works. How it works can bestbe seen by looking at problemsencountered when it is not followed.Fo r example, one team jumped into aproject and later found out it neveragreed to a definition of the problem

or the boundaries under whichwould work. Frustration and dissention followed. In another examplea team jumped into a designed experment, which could have been a quicand powerful way to solve the problem. But the team discovered none othe factors were active and only laterealized the large noise from the measurement system buried any signthese factors might have been sending2. Good leadership ma y be criticaSuppose a project leader was placein charge of a team whose memberwere also members of the companyunion. At the first meeting, the members sat with folded arms and cynicalooks because they had already beedown many bad roads with the company. By the end of the project, however, the members were totallsupportive of the project leader. WhyBecause he led by example and hadserious and overriding commitmento the process and team members, noto management.3. First-order scientific or engineerin

The Theory-Data CycleState theories basedon current knowledge.

Act and foilow up.

Perform engineering analysis:Why did it happen?

Perform statistical analysis:What happened?

Design data collectioscheme (MSA, SPC,COV and DOE).

Collect data.

MSA = measurement systems analysis.SPC = statistical process control.COV = components of variance (similar to a multi-vari study).

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principles usually don't solve theproblem. If they did, the problemwould probably not have reached theSix Sigma project stage. For example,consider a project that aimed to reducethe squealing of metallic brake pads. Tosolve the problem, metallurgists usedfirst-order principles to recommendchanging the kind of iron used andsome other chemistries and then hold-ing tighter tolerances. While reason-able, the squealing problem remained,only with higher scrap rates. It took adata driven approach to eventuallysolve the problem.4. Soft tools, such as value streammapping, process mapping and fail-ure mode and effects analysis, can bevaluable, but not when the work isdone in a meeting room. According toBill Murray in the movie WMat AboutBob? "There are two types of people inthis world: those who like NeilDiamond and those who don't." Inthat statement, Murray gave us ananalogy for the two types of engineersin this world: those who like to sit in ameeting room to theorize what's goingon and those who like to go to theworkplace and find out.A related example on the StanfordGraduate School of Business' websitesays:

The Canon executive couldn'tfind the English word. He wantedto express the belief of Japanesemanagers that when somethinggoes wrong, the only solution is toge t to the site to see what's happen-ing. "We have a phrase in English,"volunteered Sam Wood, assistantprofessor of manufacturing andtechnology. "We say you have to goto the gemba." The Japanese man-agers roared with laughter. Gemba,the Japanese word for the scene ofthe action, was precisely the wordthey had been trying to translate!

5. There is little connection be-tween formal education and the abili-ty to come up with good ideas. This isdirectly related to point three. Thosedosest to the action often know moreabout the process than many of thepeople above them on the organiza-tional chart. They frequently haveknowledge the process or design engi-neer may not.

I was once in a four-hour meeting

plex theories for why a measurementsystem process had recently not beenworking. After two requests, the engi-neers agreed to let me look at theprocess itself. I watched the processfor a while and then asked the opera-tor if he knew what the problem was.He said he did. I asked him if he'd tellme, and he did. I asked him why hedidn't tell anyone before. He grinnedat me and said, "No one else asked."

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6. The interplay between theoryand data is like a chicken and an egg.Which came first? W. EdwardsDeming emphasized the need to havea theory, even a hunch, before startingto solve a problem when he wrote,"Experience without theory teachesnothing."3 However, the commonphrase "letting the data talk to you"suggests using data first to generatetheories.

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The solution to which comes first canbe found in Figure 1 (see p. 66). Thereis no first. In some projects, broadbased, passive data collection maygenerate theories where virtually noneexisted. An example of this is collect-ing three samples in a row from eachof four eight-cavity machines, once anhour for an eight-hour shift, over sevendays. In other projects, a well-planned,theory based experimental design, say

a fractional factorial design, may nar-row down theories.7. The Pareto principle wins out.

The uniform principle (if it existed)would say many small parts play aroughly equal role in the improvement.This would hold true if each of theDMAIC phases contributed between 15and 25% to the overall success of theproject. The Pareto principle often winsout, however, because one of the

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TITLE: What Makes a Six Sigma Project Successful?

SOURCE: Qual Prog 38 no5 My 2005

WN: 0512101027006

The magazine publisher is the copyright holder of this article and it

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What Makes a Six Sigma project successful

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