Statistical Process Control for Right-Brain Thinkers

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Lon Roberts

"Stand firm in your refusal to remain conscious during algebra. In real life, I assure you, there is no such thing as algebra." — Fran Lebowitz

Known for her sardonic wit, perhaps the social commentator, Fran Lebowitz, did not intend for this bit of advice to teens to be taken literally. Nevertheless, I submit that it elicits a grin from many who are well beyond their teens because it rings true to their reality and their remembrance of sweating blood in Ms. Smith’s or Mr. Jones’ introductory algebra class. Since then, and throughout their professional careers, they have gone to great lengths to avoid even a close encounter with Xs and Ys, let alone the panoply of Greek symbols that statisticians bandy about.

Unfortunately, labels such as "innumeracy" merely strengthen their resolve to justify why math beyond the capabilities of a four-function calculator has little to do with life in the real world. If this outlook seems petty to my math-minded colleagues, I ask them to consider the defenses they would likely put up if being branded as "illiterates" for being unable, for instance, to elaborate on the Gothic writers’ influence on Coleridge and his poems.

In the contemporary workplace, it is necessary not only for "science majors" and "liberal arts majors" to work side-by-side, but it is becoming increasingly necessary for each to navigate in the domain of the other. People-people, for instance, must be capable of making data-driven decisions, while analytical-people must be capable of dealing with emotionally laden human issues. I would go a step further and assert that these two camps have a responsibility to assist one another in bridging the divide that has traditionally separated one from another.

Since the target audience of this article is people who are inclined to identify with the analytical camp, I will focus the remainder of my remarks on better understanding the other. Fortunately, by tapping into contemporary brain research and the lessons learned from stellar role models, we have some helpful insights to draw on. I’ll start with an instance of the latter.

In the Acknowledgements section of A Brief History of Time, the theoretical physicist Steven Hawking credits his editor with cautioning him that every equation in the book would half the number of sales. Heeding the editor’s advice apparently paid off: Despite the density and esoteric nature of the subject matter, the book has sold over 9 million copies since it was first published in 1988. It also appeared on the London Sunday Times bestseller list for 237 weeks. Yet, if at any time in writing the book Hawking felt that he had to "dumb down" the material, that was never communicated to the reader.

What Hawking discovered, and others before him—notables such as Albert Einstein, Richard Feynman, and Isaac Asimov—apparently understood was that it’s not only possible, it’s often imperative to communicate scientific and mathematical concepts in terms and mental constructs that appeal to non-specialists. Among the latter is a large number of individuals who would characterize themselves as "right-brain thinkers"—a label applied to intelligent, often highly-educated individuals who are more adept at seeing patterns and dealing with complex human issues than crunching numbers. Furthermore, considering the fact that some 80 percent of all U.S. jobs are service-related, the contribution of these individuals to the workforce has taken on added significance over the years.

By now the distinctions between so-called "right-brain thinkers" and "left-brain thinkers" have been extensively researched and well documented. Much of the pioneering work in this area was performed in the 1950s by the Nobel prize-winning neurobiologist, Roger W. Sperry. More recently, research in this area has benefited from fMRI brain scans, which, with current technology, are capable of pinpointing regions of neural activity within three millimeters.

For those who are unfamiliar with the territory, it is helpful to know that the left hemisphere of the brain is generally more active than the right hemisphere when linear-logical tasks are being performed. The opposite is true when the brain-owner is engaged in visualizing patterns and integrating information. Also, when it comes to their formal education, left-brain thinkers tend to major in the sciences and math, while right-brain thinkers tend to gravitate to the arts and humanities—but there are always exceptions. A case in point is Albert Einstein. In describing his thought process when solving complex conceptual problems, Einstein pointed out that:

. . . the words or language, as they are written or spoken, do not seem to play any role in my mechanism of thought . . . in my case the (elements of thought are) of visual and some of muscular type. Conventional words or other signs have to be sought for laboriously only in a secondary stage.

Unfortunately, we don’t have the benefit of brain scans to see what was going on inside of Einstein’s head when he was engaged in solving a problem, but as Davis and Hersch pointed out in their 1981 classic The Mathematical Experience, "Several recent studies on the way in which nonmathematical adults perform simple arithmetic seem to suggest the same [approach Einstein used in solving problems] is true for non-mathematicians as well."

In organizing and writing my book—SPC for Right-Brain Thinkers: Process Control for Non-Statisticians—I took the aforementioned lessons to heart. Actually, this came somewhat naturally to me since I consider myself to be a right-brained engineer.

As I pointed out in the book’s Preface, "The challenge that right-brain thinkers face in understanding and applying statistical process control [(SPC)] goes beyond the math . . . It is also a matter of approaching the subject from a different perspective altogether—through the side door, if you will, where the inner workings of [statistical process control] can be seen in action."

While an aversion to math may indeed be a stumbling block, simply going easy on the math does not account for the neurological factors that distinguish right-brain thinkers from left-brain thinkers. Indeed, as we saw in Einstein’s case, some right-brain thinkers may be adept at math—though they may take a more visual (and kinesthetic) approach then their left-brained counterparts. Also, with all due respect to Steven Hawking, perhaps the real benefit of omitting all equations but one (E = mc2) from his book, was that it compelled him to talk his way around the equations—going against his nature, I would guess, to express abstract theoretical concepts in a language other than math.

While statistical process control may not be on par with theoretical physics (or rocket science) when it comes to mathematical complexity, it may very well seem that way to those who are intimidated by the mere mention of the word "statistics." With that and my earlier comments in mind, I leave you with some suggestions for making this powerful tool accessible to right-brain thinkers who support service processes:
  • Broach the subject by linking it to a specific business process they can relate to, rather than starting with probability theory, the central limit theorem, theoretical distributions, etc. Help them visualize how statistical process control is relevant to them and their world.
  • Actively engage them in the process of setting up the statistical process control system. Keep in mind that service providers are an inseparable part of the processes they support.
  • Help them understand and appreciate the distinctions between run charts and control charts, but don’t minimize the former. Bear in mind that data streams within some service processes do not move fast enough to make multiple-observation sampling feasible.
  • Provide them with fill-in-the-blank spreadsheets for calculating control limits. Do not require them to memorize or utilize formulas to calculate sigma values.
  • Don’t insult their intelligence. Avoid characterizations such as "dumbing down" or "innumeracy."
  • Recognize the role and importance of intangibles in service processes. Understand what this means in terms of establishing metrics, collecting data, gaming the numbers, etc.
May all of your processes be in control!