Six Sigma is known for using statistical methods. And this is why is it useful for benchmarking. In their book Six Sigma: The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, by Ikel Harry, Ph.D., and Richard Schroeder, the authors describe three kinds of benchmarking, internal benchmarking (comparing divisions within a company), competitive benchmarking (comparing with competitors within an industry), and functional benchmarking (comparing with competitors across industries). These three types of benchmarking are discussed in more detail in the previous post.
But how do you compare in such a way as to make sure you are comparing apples to apples, and not apples to oranges? You use the process of quantitative benchmarking, which allows such a comparison. It has two components.
1. Yield or defect rate
For a particular product, service, or transaction, the percentage of units of production that come out defect-free is called the final yield. The defect rate is therefore 100% minus the yield rate. So a process that has a 15% defect rate has a 85% yield. They are two different ways of measuring the same phenonemon.
2. Opportunities for defects
If there are ten processes that are involved in making a unit, and each one has five different ways of creating a defect, then there are 10 x 5 = 50 opportunities for defects involved in the manufacture of that unit. Obviously then, the more complex the product, and the more complex the manufacturing process to create that product, the higher the number of opportunities of defect will be.
What you do is take the yield to the power of 1 over the number of opportunities for defect, and you will get the average yield per opportunity for a defect. This expressed in percent can be converted to a sigma level. Here’s an example from the book.
Product | Final
Yield |
Defect
Opportunities |
Average Yield
Per Opportunity |
Sigma
Level |
A | 85% | 600 | .85 ^ (1/600) = 99.97% | 3.5 |
B | 96.8% | 48 | .968 ^ (1/48) = 99.97% | 3.5 |
So product A and B, despite being of different complexity, can still be compared with this method with the result that each product has the same capability per opportunity. This allows the benchmarking of quality of similar processes, even if they produce products that have widely varying yields and number of opportunities for defects.
It is the statistical tools of Six Sigma that allow benchmarking beyond the mere competitive benchmarking, which is more common, to the more ambitious functional benchmarking that allows one to learn from a wider variety of “best practices” not just in one own’s industry, but across all industries. Then Six Sigma can be used to implement measurable change within one’s own company and processes to match those that are best-in-class,
So what specifically do the authors recommend companies benchmark? That is the subject of the next post.
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