Six Sigma
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Executive Summary
Upon delving into the topic of materials management, one methodology seems to prevail among the current data and analysis of the manufacturing business segment. Six Sigma, a customer-centered statistical approach to quality management, has been very successful in Japan and within the manufacturing sector of American and European businesses. After extensive research, it was found that Six Sigma can also be applied to a variety of other business sectors with only minor variations in the process. Companies must always be careful in selecting the correct metrics and quantifiers for a Six Sigma program, but because of the adaptability of the method, it can be applied almost universally. There are some negatives associated with the Six Sigma process, but many of these can be addressed on an individual project basis. It is also theorized that over time, all drawbacks will be addressed and eventually eliminated as the process evolves. This method possesses the flexibility to adapt to the changing business environment and will most likely be a significant business concept for some time.
Problem Definition
With even the smallest amount of research into the materials management, inventory control, or supply chain management sectors of business, one single idea surfaces, invariably. Six Sigma. What is Six Sigma? And is it really all its cracked up to be? Over the last 15 years, the term Six Sigma has become prevalent in most areas of business, not just the manufacturing sector. Through analysis of recent data from a variety of sources, it is clear that Six Sigma has permeated every business sector, both public and private and is gaining momentum daily. Is this momentum reaching a critical mass that will result in explosion?
Sigma six is now being used on a much wider scale than its original intent as a process variance reduction technique in the manufacturing sector. One can only wonder if applications to other business processes will yield similar results. Can Six Sigma be as affective for non-manufacturing business segments? And if not, will these potential failures affect the credibility of the system, especially among those business sectors that may really benefit from it? Can this new technique for quality control live up to the wide acclaim it has gained so rapidly, or will it simply be a footnote in this chapter of the history books?
This research paper sets out to answer some of these questions through review and analysis of only a minute cross-section of data regarding this renowned technique. Specifically, the following questions will be addressed:
What is Six Sigma, and what are its most successful applications?
Has Six Sigma been successfully applied to a variety of business fields and sectors? If so, what are the variances that have allowed the program to succeed?
What, if any, are the drawbacks, or negatives associated with this method?
Does the Six Sigma method possess the elasticity to adapt to the constantly changing business world?
Background Data
To understand the implications and applications of Six Sigma, one must first understand what the term means and the technique it is used to describe. One of the most succinct explanation of Six Sigma comes from Karen G. Moores study of sigma six at Ford Motor Company. Karen describes the phenomenon this way:
“In statistics, the Greek letter sigma is used as a measure of variation. In a business, or manufacturing context, sigma measures the capability of a process or product to perform defect- or variation-free work. The sigma value indicates how likely a defect is to occur (or the standard deviation between the mean and the nearest specification limit). Most companies operate at about three sigma, or at a quality standard of 99 percent. A sigma value of six indicates that a process will not produce more than 3.4 defects per million opportunities – or a standard of 99.99966 percent. Six Sigma, then, is a data-driven methodology for eliminating or reducing defects or variation in any process. Six Sigma improvement projects attempt to identify and eliminate the root cause of defects or variations through the several step process of define, measure, analyze, improve, and control. The ultimate goal of Six Sigma is to achieve customer satisfaction through continuous improvement in quality.”
This definition, while a good foundation for an understanding of the methodology, needs clarification and further study. The process involved in Six Sigma (define, measure, analyze, improve, and control, or DMAIC) is the driving force behind all the success stories. This process warrants a closer look.
The Define stages purpose is to increase the Six Sigma teams understanding of the problem at hand through research, research, and more research. Because this technique is based in the needs of the customers, and actually defines error by what the customer deems acceptable, the key elements of this process are:
identifying all customers, including other businesses, members of the supply chain, and final consumers,
identifying the needs of those customers,
and identifying customers requirements and expectations in regard to your product or service.
This information can be gathered through a variety of methods, but generally consumer, or market, research performed by a neutral third party firm is adequate for addressing the needs of consumers. This research may take place through focus groups, one-on-one interviews, or telephone or internet questionnaires, depending on the level of depth required to understand the needs of the consumers. Data can be gathered from other businesses in much the same way, but there must be sensitive consideration of current and future business relationships. This business-to-business research process is typically more successful and accurate if it is performed on a one-on-one basis with members of the other company. Due to long-standing business relationships, knowledge of the field, and previous quality control initiatives, many insights may be available from such business partners.
The Measurement stage involves defining the information gathered in the first phase. This data must be related to quantifiable, measurable variables that can be analyzed and manipulated. This is often the most difficult stage for companies with a wide range of products, or companies that are involved in the service sector.