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	<title>Comments on: Six Sigma Part II</title>
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	<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/</link>
	<description>Using principles of Science and Statistical Thinking in Policy</description>
	<pubDate>Wed, 07 Jan 2009 12:42:16 +0000</pubDate>
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		<title>By: John</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22129</link>
		<dc:creator>John</dc:creator>
		<pubDate>Sat, 06 Dec 2008 21:25:53 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22129</guid>
		<description>I think the next wave is already upon us and called "Lean Manufacture"</description>
		<content:encoded><![CDATA[<p>I think the next wave is already upon us and called &#8220;Lean Manufacture&#8221;</p>
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		<title>By: Six Sigma Belt</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22128</link>
		<dc:creator>Six Sigma Belt</dc:creator>
		<pubDate>Fri, 05 Dec 2008 06:33:04 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22128</guid>
		<description>Interesting article and good follow-up conversation.  My biggest question about Six Sigma is how long before the next great quality system emerges to compete and then everyone will be jumping ship for the latest processes and methodologies.</description>
		<content:encoded><![CDATA[<p>Interesting article and good follow-up conversation.  My biggest question about Six Sigma is how long before the next great quality system emerges to compete and then everyone will be jumping ship for the latest processes and methodologies.</p>
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		<title>By: John</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22057</link>
		<dc:creator>John</dc:creator>
		<pubDate>Thu, 03 Jul 2008 21:38:43 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22057</guid>
		<description>Hi John,

I think one key word idea in your comment is "...good implementation of six sigma.."  There is, of course, variation in how Six Sigma is defined and carried out.

It is also true that a planned approach to improvement efforts is better than some helter skelter arrangement.

But planned approach to improvement, good implementation, top management support, etc., are not the exclusive domain of Six Sigma.  In 1950 Deming told the management of Japan's industry that they had to be in the leadership.  Nothing new about that.

As for dramatic yield improvement, it happens.  I have seen it many times and often before there was such a thing as Six Sigma.  Again, there is nothing particularly Six Sigma about that, not is it particularly new.

Another example is the  DMAIC methodology.  In one form or another it's been around for years.  

As I pointed out in another post, I have advocated the use of in-house, specially trained resources to guide improvement efforts.  I didn't name the role after Karate belts, I called them statistical quality consultants, but it's basically the same idea.  I was advocating that to clients in 1980.  Six years before Six Sigma hit the scene.

In an article I wrote for an Australian Business Journal, I called Six Sigma, largely a matter of the "...same soup in a different can..."  Six sigma has basically changed a lot of terminology, added some statistical smoke and mirrors and other than that is not terribly different from the traditional ASQ approach to quality.  That is why it has been so completely embraced.  It's nothing really new.  It is a defect oriented program.  Set the spec, find the defect via inspection, segragate the defect, find the "root cause" (is if there were such a thing) and take corrective action.  In part III I point out why that falls short in my opinion.

Other than that what is unique to Six Sigma is the statistical part of it and that is also what I criticized.  It is theoretically unsound and I don't think that there is much argument with that....at least not among statisticians.</description>
		<content:encoded><![CDATA[<p>Hi John,</p>
<p>I think one key word idea in your comment is &#8220;&#8230;good implementation of six sigma..&#8221;  There is, of course, variation in how Six Sigma is defined and carried out.</p>
<p>It is also true that a planned approach to improvement efforts is better than some helter skelter arrangement.</p>
<p>But planned approach to improvement, good implementation, top management support, etc., are not the exclusive domain of Six Sigma.  In 1950 Deming told the management of Japan&#8217;s industry that they had to be in the leadership.  Nothing new about that.</p>
<p>As for dramatic yield improvement, it happens.  I have seen it many times and often before there was such a thing as Six Sigma.  Again, there is nothing particularly Six Sigma about that, not is it particularly new.</p>
<p>Another example is the  DMAIC methodology.  In one form or another it&#8217;s been around for years.  </p>
<p>As I pointed out in another post, I have advocated the use of in-house, specially trained resources to guide improvement efforts.  I didn&#8217;t name the role after Karate belts, I called them statistical quality consultants, but it&#8217;s basically the same idea.  I was advocating that to clients in 1980.  Six years before Six Sigma hit the scene.</p>
<p>In an article I wrote for an Australian Business Journal, I called Six Sigma, largely a matter of the &#8220;&#8230;same soup in a different can&#8230;&#8221;  Six sigma has basically changed a lot of terminology, added some statistical smoke and mirrors and other than that is not terribly different from the traditional ASQ approach to quality.  That is why it has been so completely embraced.  It&#8217;s nothing really new.  It is a defect oriented program.  Set the spec, find the defect via inspection, segragate the defect, find the &#8220;root cause&#8221; (is if there were such a thing) and take corrective action.  In part III I point out why that falls short in my opinion.</p>
<p>Other than that what is unique to Six Sigma is the statistical part of it and that is also what I criticized.  It is theoretically unsound and I don&#8217;t think that there is much argument with that&#8230;.at least not among statisticians.</p>
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		<title>By: Chris</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22054</link>
		<dc:creator>Chris</dc:creator>
		<pubDate>Thu, 03 Jul 2008 16:07:03 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22054</guid>
		<description>John,
   I would agree with you if Six Sigma was simply an effort to move inspection upstream to the earliest opportunity to detect a defect in order to eliminate the possibility of adding further value to something of no value.  Fortunately, that is NOT what a good implementation of Six Sigma does and that is why I respectfully disagree with you and agree with Mike's earlier comments.  In my own situation, I've used the Six Sigma process to bring about improvements to the bottom line by changing the labor content of an assembly and by finding an improved process that takes longer (more labor) than the orginal, but achieve's such a dramatic yield improvement that it more than recovers the cost of the added labor.  Admittedly, I do not strictly use Six Sigma all of the time - it is a long and involved process, but when I have a problem with no clear, "just do it" solution you can bet I'll turn to the Six Sigma process and dig in.</description>
		<content:encoded><![CDATA[<p>John,<br />
   I would agree with you if Six Sigma was simply an effort to move inspection upstream to the earliest opportunity to detect a defect in order to eliminate the possibility of adding further value to something of no value.  Fortunately, that is NOT what a good implementation of Six Sigma does and that is why I respectfully disagree with you and agree with Mike&#8217;s earlier comments.  In my own situation, I&#8217;ve used the Six Sigma process to bring about improvements to the bottom line by changing the labor content of an assembly and by finding an improved process that takes longer (more labor) than the orginal, but achieve&#8217;s such a dramatic yield improvement that it more than recovers the cost of the added labor.  Admittedly, I do not strictly use Six Sigma all of the time - it is a long and involved process, but when I have a problem with no clear, &#8220;just do it&#8221; solution you can bet I&#8217;ll turn to the Six Sigma process and dig in.</p>
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		<title>By: Tom</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22043</link>
		<dc:creator>Tom</dc:creator>
		<pubDate>Sat, 28 Jun 2008 09:22:25 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22043</guid>
		<description>A number of interesting points, in both the original post and the discussion. Your discussion of Key Quality Characteristics and Fundamental Process Variables touches on the risk, when working to improve process outcomes (the dependent variable) that the improvement efforts will be myopic, overlooking other process outcomes and making them worse...also known as local suboptimization. I believe that one of the strengths of Six Sigma is the way that it attempts to mitigate this risk by requiring that all improvements have verified impacts on the corporate bottom-line.
I believe that Deming would have preferred that practitioners develop a deeper understanding of the process they are trying to improve and any impacted processes in the system, so as not to overlook any key outcomes or variables. However, being able to trace a single process outcome to the business bottom line requires developing a deeper understanding of the entire business value chain, an effort that I think Deming would have approved of.</description>
		<content:encoded><![CDATA[<p>A number of interesting points, in both the original post and the discussion. Your discussion of Key Quality Characteristics and Fundamental Process Variables touches on the risk, when working to improve process outcomes (the dependent variable) that the improvement efforts will be myopic, overlooking other process outcomes and making them worse&#8230;also known as local suboptimization. I believe that one of the strengths of Six Sigma is the way that it attempts to mitigate this risk by requiring that all improvements have verified impacts on the corporate bottom-line.<br />
I believe that Deming would have preferred that practitioners develop a deeper understanding of the process they are trying to improve and any impacted processes in the system, so as not to overlook any key outcomes or variables. However, being able to trace a single process outcome to the business bottom line requires developing a deeper understanding of the entire business value chain, an effort that I think Deming would have approved of.</p>
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		<title>By: John</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22038</link>
		<dc:creator>John</dc:creator>
		<pubDate>Tue, 24 Jun 2008 17:00:42 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22038</guid>
		<description>Thanks for your comment.  

I have no animosity to ideas or methods.  So your characterization of me, in addition to being of the nature of a personal attack, is simply untrue.  Elsewhere you suggest, by inference, that I am not a good 'continuous improvement professional'.  That's a little condescending. Why all the animus?  It's only an idea.

As you point out at the end of your comment, some methods work better than others.  It is also true that some methods are theoretically flawed and some are not.  It is the point of these posts to point out that Six Sigma, despite its wide acclaim, has deep theoretical flaws and doesn't work very well.  Both these assertions can be demonstrated.

As for the specific point you raise, the heart of Deming's point 3 is not to move inspection upstream.  It is, if you read it, a call to stop depending on the analysis of outcomes to improve.  That point seems to have been missed by you, although it was the main point I was trying to make in this second part of the Six Sigma posts.  

It is a general point and not aimed at Six Sigma specifically.  I included it in this discussion because it is germane.  Defects are outcomes.  You can't improve a process by reacting to its outcomes.

As for root cause analysis, that is just a more dliigent way to chase defects.  Moreover, if you believe that processes are systems, then there is no such thing as a 'root cause'.  It can only be defined subjectively.

You seem to have to the mistaken idea that if one wants to improve, one will improve.  I wish it were that simple.  But one must also have knowledge about what to do.  Otherwise you can (and people do) make things worse.  

Again thanks for your comment.  I think it's possible to have this discussion without characterizing the other people involved.</description>
		<content:encoded><![CDATA[<p>Thanks for your comment.  </p>
<p>I have no animosity to ideas or methods.  So your characterization of me, in addition to being of the nature of a personal attack, is simply untrue.  Elsewhere you suggest, by inference, that I am not a good &#8216;continuous improvement professional&#8217;.  That&#8217;s a little condescending. Why all the animus?  It&#8217;s only an idea.</p>
<p>As you point out at the end of your comment, some methods work better than others.  It is also true that some methods are theoretically flawed and some are not.  It is the point of these posts to point out that Six Sigma, despite its wide acclaim, has deep theoretical flaws and doesn&#8217;t work very well.  Both these assertions can be demonstrated.</p>
<p>As for the specific point you raise, the heart of Deming&#8217;s point 3 is not to move inspection upstream.  It is, if you read it, a call to stop depending on the analysis of outcomes to improve.  That point seems to have been missed by you, although it was the main point I was trying to make in this second part of the Six Sigma posts.  </p>
<p>It is a general point and not aimed at Six Sigma specifically.  I included it in this discussion because it is germane.  Defects are outcomes.  You can&#8217;t improve a process by reacting to its outcomes.</p>
<p>As for root cause analysis, that is just a more dliigent way to chase defects.  Moreover, if you believe that processes are systems, then there is no such thing as a &#8216;root cause&#8217;.  It can only be defined subjectively.</p>
<p>You seem to have to the mistaken idea that if one wants to improve, one will improve.  I wish it were that simple.  But one must also have knowledge about what to do.  Otherwise you can (and people do) make things worse.  </p>
<p>Again thanks for your comment.  I think it&#8217;s possible to have this discussion without characterizing the other people involved.</p>
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		<title>By: Mike</title>
		<link>http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22037</link>
		<dc:creator>Mike</dc:creator>
		<pubDate>Tue, 24 Jun 2008 11:23:07 +0000</pubDate>
		<guid isPermaLink="false">http://jsdstat.com/Statblog/2008/06/23/six-sigma-part-ii/#comment-22037</guid>
		<description>Your animosity toward Six Sigma is impacting your credibility ... and thinking.  Six Sigma addresses "variation" and not defects.  Defects are a key performance indicator.  The variation reduction is typically done through a form of root cause failure analysis.  Variation is usually identified through tools like statistical process control and control charts.  Neither of these rely on final inspection and are at the heart of Deming's 3rd point.  Contrary to your assertion, the entire chain of events does in fact fundamentally improve the process.

To paraphrase, all improvement tools are flawed.  Some have few enough flaws to allow them to be useful.  A good continuous improvement professional is knowledgeable regarding a multitude of tools and applies them only where they make sense.</description>
		<content:encoded><![CDATA[<p>Your animosity toward Six Sigma is impacting your credibility &#8230; and thinking.  Six Sigma addresses &#8220;variation&#8221; and not defects.  Defects are a key performance indicator.  The variation reduction is typically done through a form of root cause failure analysis.  Variation is usually identified through tools like statistical process control and control charts.  Neither of these rely on final inspection and are at the heart of Deming&#8217;s 3rd point.  Contrary to your assertion, the entire chain of events does in fact fundamentally improve the process.</p>
<p>To paraphrase, all improvement tools are flawed.  Some have few enough flaws to allow them to be useful.  A good continuous improvement professional is knowledgeable regarding a multitude of tools and applies them only where they make sense.</p>
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