Supply Chain Vector [Electronic resources] : Methods for Linking the Execution of Global Business Models With Financial Performance نسخه متنی

Six Sigma and Global Business Models

As mentioned in an earlier chapter, the bane of international operations is process variation. Whether in a production, logistics or administrative environment, deviation from established performance standards will ultimately result in more inventories, higher landed costs, longer lead times and/or weaker financial performance. With this point a constant reminder for business managers, it would be wise for organizations to focus on tactics that reduce variation and its myriad ways of plaguing operations. Taken in hand with the lean philosophy, the one-two punch of increased velocity and reduced process variation is exactly the goal that supply chain managers should be pursuing.

Much more than a historical footnote, it was actually the TQM movement that first adopted the idea of reducing process variation. Then, as now, variation was defined as any difference between the planned and actual outcome of an event. Pioneers like W. Edwards Deming focused on the use of the standard deviation, limited at that time to a production environment, to first baseline and then help to reduce variation in product quality. Of equal historical importance, it is instructive to observe that the use of the standard deviation was first developed in 1893 by mathematician K. Pearson. [2] As mentioned earlier, it seems that the best tools are those that transcend both time and fad with characteristics that make quantification of process performance a reality. To borrow from the old Levi's tag line: "Quality never goes out of style." In business, neither does basic but solid math.

Six Sigma is a methodology that promotes enterprise-wide continuous improvements through the use of the standard deviation and other analytical tools. First introduced by Motorola in the late 1980s, Six Sigma is composed of tools designed to reduce variation in all business processes. Later adopted by equally high-profile companies like General Electric and Allied Signal, success stories related to Six Sigma abound in the business press and can be found in annual reports around the globe. Because of its client orientation, ability to reduce process variation and focus on cycle times, international business operations are a prime target for the application of Six Sigma.

The name Six Sigma actually finds its origins in the Greek letter "sigma," the symbol in mathematics that signifies standard deviation. The mathematical relevance of the standard deviation is that it measures spread (or dispersion) from the mean value of a population or sample. The business application of Six Sigma lies in its ability to first establish a mean (similar to average) value for a process and measure the spread from the mean of individual values. Of equal commercial significance, it has been proven that 68% of all values fall within one standard deviation of the mean, 95.5% fall within two standard deviations and 99.7% fall within three standard deviations of the mean. As shown in Figure 8.1, the term Six Sigma is used to reflect the fact that some results fall below the mean and others beyond it (hence the name Six Sigma as opposed to Three Sigma).

Figure 8.1: Standard Deviation

If customer requirements can be quantified, they can then be compared with the actual outcomes of a process. It must be stated, however, that just because 99.7% of all values fall within three standard deviations of the mean, it should not be deduced that process performance is at a 99.7% level. Actually, if the mean value is not consistent with customer expectations, many of the individual values that are within three standard deviations will still be outside the client's tolerance.

COMMERCIAL APPLICATIONS FOR THE STANDARD DEVIATION

When applying the principles of mathematics to business, it would be difficult to find a more versatile tool than the standard deviation. Sometimes confused with the arithmetic mean (average), the standard deviation measures the dispersion of data points in a population or sample. Technically, the standard deviation is defined as the square root of the sum of the squared differences between data points and the average value of those data points. Sounds impressive, but what does it mean?

The standard deviation actually begins with an average value for a data set, and then the individual values are subtracted from that average. All differences are then squared to account for any negatives and are then summed. From that point, the square root of the total value is calculated to arrive at the standard deviation. This figure is what is of most interest to mathematicians and businesspeople alike, as it defines the spread of data from the average.

Averages are important to the standard deviation because of a phenomenon in mathematics known as central tendency. Because averages are derived from all the values in a population or sample, the natural tendency is for the majority of individual data points to cluster around the average value. What the standard deviation reveals is exactly how dense the cluster of data points is. The goal of businesspeople is to make sure that individual outcomes in any process are as close to the mean (or, more importantly, customer specifications) as possible. The relevance of the standard deviation in this endeavor is that once a process can be measured, actions can be taken to bring outcomes within the specification limits agreed upon with a customer. An example of lead time management can be used to illustrate the application of the standard deviation in process improvements.

For analysis purposes, assume that a seller and buyer agree that the lead time for ocean shipments from Asia to the United States is 23. days door to door. As actual outcomes transpire, the standard deviation from the target transit time is calculated, showing the spread from the 23-day target. For example, if after tracking 100 shipments it is determined that the standard deviation is three days, it can be said that 68.4% of the shipments arrive either three days early or three days late (one standard deviation from the mean). Using the same logic, it can also be stated that 95% of the shipments are either six days early or six days late. For shipments that arrive in exactly 23 days, the objective is to continue to hit the transit time agreed upon. Of equal importance, businesspeople must analyze the late shipments and determine methods to bring as many as possible to the target date.

As one can see, standard deviation measures variation in processes. Once the operational definitions of any business process are defined, this tool can be used to isolate both compliance with and variation from a target. It is for this reason that the standard deviation has so many applications for business and should be used as a basic tool in process improvement initiatives.

On the other hand, as the mean value approximates the customer's requirements, more and more individual values will fall within the specification limits. If all of the values fall within the specification limits imposed by the client and are inside three standard deviations from the mean, the process is performing at a 99.7% or Six Sigma level. Expressed differently, achievement of Six Sigma means that only 3.4 defects will be found in every million opportunities. Although an admirable achievement, it is when processes are not operating at this level that is of greatest interest to practitioners of Six Sigma thinking. To that end, Table 8.1 shows a summary of Six Sigma levels associated with numbers of defects.

Table 8.1: Sigma Levels

[2]M.G. Kendall and W.R. Buckland, A Dictionary of Statistical Terms, Longman Group, 1971, p. 186.