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This chapter is from the book

What Is Six Sigma?

The term "Six Sigma" has several meanings. At the most encompassing level, a corporation can define it as its philosophy—a way of thinking. By doing so, a company's management structure, employee roles, and operations are defined, in part, by this fact-based discipline. Or it can be defined as a method and tool set—for example, using the Define-Measure-Analyze-Improve-Control (DMAIC) technique to make improvements and solve problems within an existing process. Or, at the simplest level, it can be defined as a specific statistical quantity, describing the number of defects produced due to variation in a product or process. Technically, Six Sigma is described as a data-driven approach to reduce defects in a process or cut costs in a process or product, as measured by "six standard deviations" between the mean and the nearest specification limit. "Sigma" (or s) is the Greek letter used to describe variability, or standard deviation, such as defects per unit. Figure 1.1 shows a normal distribution of a population, with its mean (m) in the center and a data point on the curve indicating one standard deviation (1s) to the right of the mean.

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Figure 1.1 A normal distribution.

How well a desired outcome (or target) has been reached can be described by its mathematical average; however, this may be misleading. The average of a data set masks the variation from one data point to the next. The standard deviation describes how much variation actually exists within a data set. An average is mathematically defined as the sum of all the data points divided by the number of data points. This is also called an arithmetic mean. The standard deviation is calculated as the square root of the variance from the mean.

Why is the number six frequently coupled with the word "sigma"? If a process is described as within "six sigma," the term quantitatively means that the process produces fewer than 3.4 defects per million units (or opportunities). That represents an error rate of 0.0003%; conversely, that is a defect-free rate of 99.9997%. That's pretty good, right? Professional marketers can relate to this because they see errors and can exploit the opportunity to reduce variation and its effects on results.

What level of variance (or error rate) in a process should you accept? If the resulting process data is within three standard deviations (3s) from the mean, is that good or bad? The answer depends on your business. Let's say you are in the shipping business, and you experience only a 1% error rate for every million deliveries. Is that good? That translates into a 99% error-free business (or a four-sigma level [4s]), or 6,210 defects per million. Is that good? In business terms, that means 20,000 lost pieces of mail per hour. That could cause some serious customer satisfaction issues. Within other industries, a "four-sigma" performance could mean 6,800 problems with airplane takeoffs per month, or 4,300 problems in common surgical procedures per week, or no electricity for almost 7 hours per month. Remember, the sigma measure compares your performance to customer requirements (defined as a target), and the requirement varies with the type of industry or business.

That is a brief technical description of Six Sigma. The concepts put forth in this book (and the literature) go beyond a mathematical discussion and extend into how companies deploy these statistical tools—as a business initiative. Successfully implementing the Six Sigma approach requires companies to consider changes in methodologies across the enterprise, introducing new linkages. Similar to the Total Quality Management (TQM) initiative, some benchmark companies create new employee roles (such as Black Belt project leaders). Some also institute a new management or organizational structure and new or revised project and operational processes to instill the concept.

Three benchmark examples of how Six Sigma permeates a corporate philosophy and becomes a business initiative can be found by studying Motorola, Allied Signal, and General Electric (GE). Motorola created Six Sigma (largely attributed to Bill Smith) as a rallying point to change the corporate culture to better compete in the Asia-Pacific telecommunications market. At that time, Motorola's main focus was on manufacturing defect reduction. Allied Signal rebuilt its business with bottom-line cost improvement using Six Sigma. Eventually Allied extended its Six Sigma implementation into its business and transactional processes for cost control. GE revolutionized how an entire enterprise disciplines itself across its operations, transactions, customer relations, and product development initiatives. GE implemented Six Sigma at the Customer for the customer and top-line growth using an approach called Design for Six Sigma, a methodology for product creation and development.

These three benchmark companies are pioneers in the traditional application of Six Sigma. They adhered to the three Six Sigma fundamentals of tool-task linkage, project structure, and, most importantly, result metrics. Before we explore the new growth-oriented Six Sigma for marketing, let's review Six Sigma's original methods (see Figure 1.2). This background information will help you understand how practitioners repair an inefficient or broken marketing process.

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Figure 1.2 Six Sigma fundamentals.

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