Speaking the Same Language

Both quality professionals and statisticians must be well-versed in statistics

by Matthew Barsalou

There is much overlap between a statistician and a quality professional. There also is a half a world of difference between them.

Quality professionals are those who apply statistical methods as part of a tool set when performing activities such as process improvement, performance assessment or root cause analysis. The exact statistical method may vary from task to task, but the ultimate goal is often to save money through prevention or cost reduction activities. The combination of statistical methods and quality tools provides quality professionals with a powerful toolbox for identifying and eliminating or reducing variation to achieve the ultimate end objective, which generally is some form of cost savings.

Quality professionals—such as quality technicians, auditors, engineers and managers—often have non-statistical backgrounds. Generally, quality professionals start with training or education in an area other than quality and move to quality after working in their industry in a different role. This background complements the quality professional’s quality-related activities because they often possess experience with products and processes they work with. Regardless of their exact position or role, the knowledge they have of their product or service is a great advantage.

A quality professional may have a background ranging from being an experienced production employee with a high school diploma to being an engineer with a graduate degree. Although helpful, a degree is not always required. A quality professional’s statistics-related education may come from one or two college courses in basic statistics or an industrial training program, such as Six Sigma training, or training in a specific statistical method, such as statistical process control (SPC) or design of experiments.

In contrast, a statistician requires years of formal education, often culminating with a master’s degree in statistics. A statistician may be able to innovate and publish resources on new statistical methods and innovative applications of existing methods; a quality professional typically is far less capable of such innovation in the field of statistics.

On the other hand, a quality professional must be able to understand and analyze a business process. Shifting the mean of a process to reduce scrap to achieve a financial impact may be a quality engineer’s main driver, for example. A professional statistician may be involved in applied statistics. A competent quality professional, in contrast, must live applied statistics. A quality professional working in a manufacturing company may make the wrong decision and cause a financial loss if he or she has no knowledge of statistics. A quality technician without knowledge of statistics, for example, may sample five parts and mistakenly conclude the process will not produce any defective parts because the samples are in specification. In this example, the quality technician failed to consider the position of the mean, the spread of the values or the sample size.

Natural crossover

Although separate fields, statisticians may venture into the world of quality using their knowledge of statistics to work as a statistical consultant or an organization’s in-house statistical consultant. Statisticians far removed from the quality world still may serve an unintentional role in the field of quality. Somebody must create new methods and push the boundaries of old methods so quality professionals can apply these methods to reduce variability on the shop floor or improve services.

ASQ’s Quality Body of Knowledge (QBoK)1 lists the many dimensions of the field of quality. In fact, 20% of the second section—the pursuit of operational excellence—pertains directly to the field of statistics. These areas of overlap between quality and statistics are shown in Table 1.

Table 1

Any quality professional seeking ASQ certification as a quality technician, engineer, reliability engineer, or manager of quality/organizational excellence2 must possess some basic knowledge of statistics to pass the exams. Any quality professional who seeks competency in the quality field also must possess some knowledge of statistics, regardless of certifications.

Statistics is the language of quality. Although quality professionals must understand statistics, not every statistician must understand the world of quality. For example, a statistician may be researching social sciences or working in a medical lab. For those statisticians working in that industry, there are many roles they fill while applying methods in the scope of the QBoK, such as internal consultant, trainer, mentor and innovator.

Statisticians are needed for supporting quality professionals in solving complex problems. Although quality professionals should be familiar with statistical concepts—such as hypothesis testing and regression analysis—a problem may require the application of statistical methods beyond the quality practitioner’s skillset. Suppose an organization invests in a complicated new process with multiple feedlines that requires the use of a multivariate regression analysis for an optimization project, for example. A professional statistician may be needed to plan and analyze the study. Ideally, the statistician also would teach the method to the quality engineer.

Somebody must train and mentor quality professionals who seek more knowledge of statistics, and this is a role an organization’s statistician can fill. This does not mean quality professionals will eventually replace the statistician. As the quality professional’s skill level increases, he or she still will need assistance addressing more complicated problems that remain outside their current skill level.

Innovation often refers to the creation of new products and services, and there is a need for statisticians there as well.3 Statisticians also are needed, however, for innovation in statistical methods4 to provide new methods that can be applied by quality professionals. Quality professionals may not be reading statistical journals looking for cutting-edge tools, but those methods that gain traction eventually can find their way into the hands of quality professionals. Just look at a physicist’s solution to a problem that kicked off the modern field of quality: Walter Shewhart’s SPC.5

The same language

Most statisticians probably are not quality professionals, and the majority of quality professionals probably are not statisticians. There is, however, a heavy overlap between the two fields as indicated by the ASQ QBoK, and this area of overlap presents opportunities for both sides.

The quality side provides new problems for the statisticians to solve, and statisticians can provide quality professionals with the methods—both in the form of new innovations and in training in current methods.

Although quality engineer and statistician are two separate fields, they must speak the same language: statistics.


  1. ASQ, "About the Quality Body of Knowledge," http://asq.org/knowledge-center/about-the-quality-body-of-knowledge.
  2. Ibid.
  3. Kymm K. Hockman and Willis A. Jensen, "Statisticians as Innovation Leaders," Quality Engineering, Vol. 28, No. 2, 2016, pp. 165-174.
  4. George E.P. Box and William H. Woodall, "Innovation, Quality Engineering and Statistics," Quality Engineering, Vol. 24, No. 1, 2012, pp. 20-29.
  5. Lynne B. Hare,"SPC: From Chaos to Wiping the Floor," Quality Progress, July 2003, pp. 58-63.

Matthew Barsalou is a statistical problem resolution Master Black Belt (MBB) at BorgWarner Turbo Systems Engineering GmbH in Kirchheimbolanden, Germany. He has a master’s degree in business administration and engineering from Wilhelm Büchner Hochschule in Darmstadt, Germany, and a master’s degree in liberal studies from Fort Hays State University in Hays, KS. Barsalou is an ASQ member and holds several certifications.

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