Setting aside time to celebrate quality offers an opportunity not only to reflect on our own quality improvement efforts, but also to recall other years and other celebrations, and to consider the history of the designation as well as of our own quality improvement efforts.
National Quality Month (October) started in 1988 in the U.S. and Canada, while Japan has been celebrating Quality Month (November) since 1960. World Quality Month was instituted in 2010, acknowledging the global impact that quality improvement has had on organizations, and recognizing that quality in products and services is important for organizations throughout the world.
The role of W. Edwards Deming and others is not to be forgotten as we reflect on the meaning of this month and recall its history.
Statistics has gotten a bad rap. People love to quote Mark Twain (“There are lies, damn lies, and statistics,” alternatively attributed to Benjamin Disraeli), Vin Scully (“Statistics are used much like a drunk uses a lamppost: for support, not illumination”), or Stephen Leacock (“In ancient times they had no statistics so they had to fall back on lies”).
For statisticians, these jokes have become quite tedious. Avoiding small talk at cocktail parties where quips are likely to come up or lying about one’s profession (“I’m a kind of mathematician” sometimes works) are not really satisfying alternatives to the lines that people have saved to shower on the innocent professional. What’s a statistician to do?
Myron Tribus, friend of PQ Systems, died August 31 in Pensacola, FL at the age of 94. Tribus, known as an organizational theorist, was director of the Center for Advanced Engineering Study at MIT, and taught thermodynamics for much of his career. He is best known among quality professionals as a friend, supporter, and interpreter of W. Edwards Deming. For more than 20 years, he shared his expertise at quality conferences and through his prolific writing. For his work with Pensacola in applying Deming’s principles, he was awarded the keys to the city, and received innumerable awards from quality professional organizations.
Tribus attended many of PQ Systems’ annual conferences, and in 1992 addressed participants as a keynote speaker, where he shared reminiscences about interactions with Deming. I recall a colorful story he shared in his presentation about his first meeting with Deming. This account had a lasting impression on me, as well as on other participants.
In a rapidly changing business environment, it’s sometimes hard just to keep up with everyday demands—never mind having time to develop new and better approaches to changing requirements, needs, or markets. Staying ahead of the curve sounds as if it might demand working longer hours, hiring more people, or cloning oneself, none of which seem likely in the short term. So how does one manage to innovate in this environment?
The word “innovation” itself summons images of new products, or dramatically new approaches to customer needs, or a new version of a product or a new application of technology. Per Byland in Entrepreneur asserts that innovations often involve simply rethinking supply chains or factory operations, even in small ways that improve processes. With respect to Henry Ford’s car and Jeff Bezos’ Amazon, “the factor that made these companies great wasn’t primarily technology; it was organization.”
By developing a mindset that continually asks, “How can this process be better?” organizations will find that innovation comes naturally. Fostering such a mindset lies at the heart of improvement as well as innovation.
It may be time to recall W. Edwards Deming and his 14 Points for Management that he outlined in chapter two of Out of the Crisis (MIT Press, 2000). Generally seen as keys to product and process improvement, they also reflect the process for innovation. Perhaps we can see these tried-and-true management principles in a new light.
Baseball generates what may be the greatest array of statistics of all sports. Aficionados love comparing records of home runs, hits, runs, doubles, triples, errors, batting averages, and other performance details, not only for individual players and teams, but also against historic records, sometimes collecting ammunition for a discussion with their brothers-in-law about who’s the best player or team, and how that player or team compares to record-breaking plays and players.
As with all statistics, sports statistics can be painfully distorted or innocently quoted to “prove” a point about a player or team. But statistics being statistics, they demand that any use of data respond to an appropriate question. Stats can be specious if the wrong question is being answered. Let’s see how this works. Can you answer this simple baseball question? (Feel free to look up statistics to support your response.)
Approaching the end of the school year means focusing on graduation rates, dropout rates, and other data suggesting trends for students.
Opportunities for considering statistics abound; but one must continue to examine the way that these statistics are actually used, by asking the right questions about the data.
For example: As teachers finish state testing regimens and head into final exams, it may be useful to see data related to average pay for teachers. Is it going up?
When giant companies known for the quality of their products and services find themselves suddenly in the news with massive recall efforts—think Volkswagen, Toyota, John Deere, Craftsman, Chipotle, and others—the question arises: “What went wrong?”
Before jumping to the conclusion that quality systems really don’t work (so why bother?), one must look to some of the reasons that established improvement efforts may fail.
Question: Can one make too much of variation in a process? The answer: It depends.
Chicken Little, reacting to an acorn falling from a tree, spread the alarm: “The sky is falling!” This kind of over-reaction is highly recognizable. What about the panicked investor whose stocks go down by a percentage point one day, who wants to sell everything and get out of the market? Or the teacher whose classroom seems cold, turning the pre-set thermostat way up (and then later, when the room seems too warm, turning it way down)? Or a sales manager who calls the team together to bemoan “disastrous trends” after a week’s drop in sales revenues?
While these may all patently represent over-reaction, they are recognizable behaviors—perhaps even in our own responses to changing situations. Panic can easily set in without understanding the meaning of this kind of variation. Known as common cause variation, it represents natural movement in data points in any process. One needs to know whether the sky is really falling, or if seed cycles of oak trees are predictable and stable.
To quality professionals, the challenge “So prove it!” is far more than a school yard taunt, since their organizations must continually demonstrate to customers, board members, suppliers, associations, regulatory bodies, and others that their products or services indeed meet the quality standards that they espouse.
So how does an organization—even one that is following strict standards for its products—manage to show that it is indeed doing so? In an age when every advertisement and TV commercial touts product quality, the word has lost its meaning to many. Nonetheless, being able to demonstrate the meaning of quality in products and services is not only important, but often required.
To some, increasing uses of robots represent a threat to jobs, families, and life as we know it. To others, they are the salvation of our civilization and the only hope for the future. Between these two polarized extremes, the late Peter Drucker, known as the father of modern management, offers a perspective from the past that may be even more relevant today.
A Harvard Business Review article by Rick Wartzman notes the comments that Drucker made as the debate about the effects of technology raged: “The full picture, as in all technological revolutions, emerges only if both—the better life for those who can adjust themselves and the suffering of those who are pushed out—are seen together and at the same time.”