Increasingly, control will mean the
ability to make changes without permission.
As I peer into my crystal ball and contemplate statistical process control, I predict changes in three major areas: statistics, processes and control. I will address these areas in reverse order because I believe that will reflect more accurately the difficulties managers and engineers will face in dealing with SPC's future.
First prediction -- Control is dead. Long live control! Changes in the processes and statistics areas will require understanding new enabling technologies, which will be driven by new ways of thinking about control. Changes in the area of control will be the most difficult because they involve fundamentally new philosophies.
The concept of centrally planned economies has been relegated to the dustbin of history. Unquestionably, free people are immensely more productive, happier and healthier than their counterparts living in planned economies. In the political realm, control is dead, a few straggler nations notwithstanding.
Modern organizations remain islands of central planning afloat in a sea of political freedom. This won't last. I predict that this freedom finally will make its way into business organizations when people begin questioning why some companies are more productive than others. How, for example, can Nucor Steel garner $3.6 billion in sales with a headquarters staff of only 23 employees? The questioners will find that these organizations' leaders are hostile to the very idea of management.
"If you could get into your employees' minds, you could manage 'em, but you can't get into their minds," asserts Nucor executive David Aycock. "People are free in their minds, and you can't manage a free mind." Such thinking explains why Nucor's stock price appreciated 12,439 percent since current management took over in 1973. Compared to that, the growth of Baldrige winners looks positively anemic.
After more than 50 years, the quality profession in the United States finally dropped the word "control" from its organization's name, the American Society for Quality. However, if its continued fascination with schemes such as ISO 9000, ISO 14000 and their derivatives are any indication, control and planning still lie near to its heart. For quality to survive as a profession, this attitude must change.
In the future, control will be achieved with systems that don't require reliance on oppressive procedures administered by bloated bureaucracies. Such procedures commonly prohibit process operators from making significant changes without first getting permission, usually by negotiating a labyrinth of complex steps and rules. Increasingly, control will mean the ability to make changes without permission. Process operators will perform ad hoc experiments on their processes without asking anyone first.
To prosper in this new environment, quality professionals will need to become conversant with new principles and ways of thinking. I recommend the following reading: Objectivism: The Philosophy of Ayn Rand by L. Peikoff (1991. New York: Dutton); The Fatal Conceit: The Errors of Socialism by F.A. Hayek (1989. Chicago: University of Chicago Press); and American Steel: Hot Metal Men and the Resurrection of the Rust Belt by R. Preston (1991. New York: Prentice-Hall).
Second prediction -- Process networks will become widespread. Since Adam Smith, circa 1776, the prevailing wisdom has maintained that efficiency results from the division of labor. The modern organization is a testament to that mind-set. Work and authority are divided along functional lines, e.g., engineering, marketing and manufacturing. By specializing in a specific area, according to the theory, a worker will perform the job better and more efficiently than a nonspecialist. Each specialty requires further specialization and division of labor, e.g., the steps along an assembly line.
Unfortunately, all too often the central purpose, which is to add value, becomes lost in all the specialization. Value is added by processes that zig and zag through an organization, with each department contributing. Looking at this from a smaller perspective, value is added at each step along the assembly line.
New technologies allow people to see an entire process despite increasingly complex divisions of labor. Primary among these technologies is the electronic network. Intranets allow people within an organization to communicate with one another without regard to time or place. Extranets extend this principle to the entire value-adding chain, from supplier to customer. The Internet promotes information exchange between people and organizations around the world, whether or not they are directly involved in the process. These networks make it easier to coordinate quality activities across internal departmental boundaries as well as between an organization, its suppliers and its customers. Nearly every quality problem (and solution) I have ever seen has involved multiple departments or companies.
Networking changes will produce a great deal of cultural resistance from old-guard managers and engineers. Such resistance may slow progress down but ultimately will fail to stop it. The quality professional is in a unique position to appreciate the value of these changes. Unlike other specialties such as manufacturing or marketing, quality is inherently cross-functional. However, initiatives such as ISO 9000 have reinforced existing barriers to change; formally documented processes are by nature more rigid processes. Tomorrow's managers and engineers will rely more on cooperation and trust than on written rules and procedures. Quality professionals must lead the effort to dismantle the bureaucratic impediments to cooperation and trust that they helped erect.
Third prediction -- "Statistical political correctness" will finally end. Although the bread-and-butter methods will remain, the entrenched reluctance to use newer statistical techniques will disappear. (See "SPC: Statistical Political Correctness?" by D. Udler and A. Zaks, Quality Digest, November 1997.) Change here will be driven by the enabling technology of computers, which now make it as easy to use a complex technique as a simple one. Techniques such as exponentially weighted moving averages and multivariate analysis will become more widespread. Standard SPC methods also will spread as people take greater responsibility for their own work.
The challenges facing managers and engineers are primarily educational. Classical Shewhart charts remain popular after so many years because they are both powerful and easy to understand. This is not necessarily so with, say, Hotelling's T2. Because we can't manage a free mind, we must educate process operators in the more advanced techniques if we expect those techniques to be properly used.
About the author
Thomas Pyzdek is president and CEO of Quality Publishing. He has written hundreds of articles and papers on quality subjects and authored 13 books, including The Complete Guide to the CQM and its accompanying CD-ROM. He is a fellow of the American Society for Quality and an ASQ-certified quality and reliability engineer. Pyzdek received ASQ's prestigious Edwards Medal in 1995.
Robert T. Amsden
Leaders must build company cultures where everybody
knows management wants to help rather than control.
The late W. Edwards Deming said that if a process is in statistical control, then and only then could someone predict the future of that process. The statement's logic is quite clear: Such a process has, by definition, no special causes working on it; it's stable, unchanging and thus predictable. Applying Deming's idea at a higher level, can we predict statistical process control's fate? Is SPC as an application currently in statistical control? If we take seriously management expert Tom Peters' description of current business as a place where we must "manage in chaos," then business isn't in statistical control, so how could we predict the future application of SPC?
I prefer not even to try to predict. I would much rather emphasize SPC's capabilities. Accordingly, I will address three areas: SPC's potential in an organization, the organizational requirements to enable SPC to meet this potential and the necessity of including SPC in business school curriculums.
Several years ago, I heard Kaizen author Masaaki Imai describe the attitude of some Japanese consultants. If asked to help improve an organization's productivity 10 percent to 15 percent, they would politely decline. If the organization wanted 30-percent to 50-percent improvement, they would still refuse. However, if the organization said it was looking for 100-percent improvement, or even greater, they would jump at the opportunity to work with it.
What Imai was saying didn't immediately sink in. Later, when I viewed "An Address to Dow Chemical Company," a 1984 video by Bill Conway, then president of Nashua Corp., Imai's message finally got through to me. Conway recalls how he directed the company's hard memory disk division to use SPC and the Deming philosophy to improve yields. When the project began, yield was 63 percent; seven months later, the division had surpassed the target of 95 percent. Production volume increased 300 percent without adding employees or floor space. This was exactly what Imai had said was possible. And this was accomplished in the United States, with an American's ideas.
They accomplished all these improvements, as well as others, by gaining control over business processes through SPC, explains Conway. The division identified the manufacturing processes' 26 or so fundamental variables. Using about 125 control charts, it brought these processes into statistical control and then narrowed the operating ranges. The division learned the lessons so well, it could run a special order for a customer and, immediately afterward, easily change the process parameters back to standard disk production. This example illustrates SPC's incredible potential.
What does an organization need to do to unleash SPC's power? Will training all employees in SPC do the trick? Not without leaders who are sold on SPC and understand both its theory and application. Leaders must build company cultures where everybody knows that management wants to help rather than control. This requires a process orientation within the organization, not a strictly results-oriented management.
A brief example will illustrate what I mean. A team of spray painters studied its own manual spray paint process. Through simple data collection and analysis, the team found that some painters weren't meeting the job requirements. Did management fire these below-average associates? No. When the team further learned that training wasn't adequate, management changed the training. Because managers understood SPC, they were dedicated to finding and solving the problem's root causes. They emphasized helping the associates, not blaming them.
I can't overstate the necessity for leadership that is committed to quality through prevention rather than inspection. Managers must work actively to help their associates identify, solve and implement solutions to work problems. Only then can an organization achieve the social reorganization described by management expert Peter Drucker in his article, "The Emerging Theory of Manufacturing" (Harvard Business Review, MayJune 1990). Once in place, this social organization using SPC (Drucker calls it SQC) "identifies where, and often how, the quality and productivity of the entire process can be continuously improved." SPC makes possible both high quality and productivity while providing "work worthy of human beings," says Drucker. This demands knowledgeable and dedicated leadership.
Finally, a short note about business schools. Currently, business statistics courses contain very little, if any, SPC. Because the courses are offered in business schools, rather than in the engineering or science fields, they don't emphasize scientific method. Consequently, business schools have a great opportunity to provide their students with basic courses in SPC, including an introduction to scientific method through the plan-do-check-act cycle.
Such a course must accomplish two things. First, it should ground business students in a thorough understanding of SPC theory. Second, it should make very clear SPC's usefulness in business. This will enable business school graduates to begin their careers already understanding SPC's basics and appreciating its potential. If they have really caught the vision, these graduates will choose a company because it asks them to put SPC to work.
About the author
Robert T. Amsden, Ph.D., is an associate professor of the MIS and decision sciences department at the University of Dayton in Ohio. He has researched total quality systems in the United States, Japan and Europe.
Besides consulting and training in these fields, Amsden co-authored the popular texts SPC Simplified, 2nd edition, 1998, SPC Simplified Workbook, 2nd edition, 1998, and SPC Simplified for Services (published by Quality Resources).
Donald J. Wheeler
First and foremost, SPC is a way of thinking,
with some tools attached.
The control chart, now 73 years old, remains the central technique in what Shewhart called statistical process control. And yet, even though SPC has been around for 73 years, considerable confusion persists about it. I believe this is because many have sought to reshape it according to their own backgrounds and experiences.
Some hear the term "SPC" and immediately think of classical statistical procedures. They try to fit SPC into a framework of parameters, distributional assumptions, tests of hypotheses and confidence levels. Attempts to share this version of SPC meet with the same total lack of comprehension as classical statistics.
Others hear the term SPC and think of process control. They consider it a manual process control technique to maintain a status quo. It's something to use after they've wrestled the process into a satisfactory state. "And because this is what SPC is about," they assert, "Wouldn't you like to know about some of the neat algorithmic process control and process modeling techniques that have been developed in the past few years?"
This group would gladly teach you a course or sell you some software. But as with the classical statistics approach to SPC, this perception creates a hurdle of truly mathematical proportions to overcome. Those without calculus shouldn't attempt it.
A third group equates control with conformance to specifications. SPC for them is all about producing product within specifications. They think of it as a complex route to a simple objective and therefore try to simplify SPC. They prefer to bypass the computations based on the data and use the specifications to set action limits instead.
Unfortunately, this simplicity misrepresents SPC. Those who embrace this approach may meet with limited success, but because they don't seek to get the most out of their processes, they don't reap all the benefits available from SPC. They return to sorting as a way of life: Make enough stuff, and some of it probably will be good.
Lastly, there's the group confused by the above three groups. Although they don't understand the first two interpretations of SPC, people in this group presume there must be something to all the mathematics, so they encumber SPC with distributional assumptions, conditions and requirements. As a result, the charts don't get used.
Enough! SPC is not about statistics, process control or conformance to specifications. While it can be used in all of these ways, SPC is much more than any one of these narrow interpretations. It is, at its heart, about getting the most from processes and continually improving those processes and outcomes.
Where there is merely training in the use of tools, SPC will fail. However, organizations that promote education and allow the way of thinking to take root will be transformed. For this reason, SPC's "success" appears spotty, and it will continue to do so in the future.
But is SPC obsolete? No. No other technique can boast the same combination of ease of use and statistical sophistication as the control chart. SPC's empirical approach has been the dominant investigative technique for 400 years and shows no signs of faltering. The control chart's unequaled ability to facilitate communication always will be beneficial. And the unparalleled simplicity with which it identifies opportunities for improvement always will have a place in organizations that wish to stay in business.
About the author
Donald J. Wheeler is an internationally known consulting statistician and the author of Understanding Variation: The Key to Managing Chaos and Understanding Statistical Process Control, Second Edition. © 1998 SPC Press Inc.