Featured Product
This Week in Quality Digest Live
Quality Insider Features
Sara Harrison
Ask younger colleagues to train them
Harry Hertz
Nine takeaways from Baldrige recipients
Nate Burke
Create a frictionless customer experience
Del Williams
Tubular cable conveyors can be flushed with water, rinsed, and sanitized without disassembly
Joseph Near
Differentially private programs provide randomized outputs, and privacy bugs aren’t detectable by observing output values

More Features

Quality Insider News
Provides supervised 24/7 remote monitoring of up to 12 environmental and equipment status conditions
ABM Equipment doubles industry-standard capabilities with Eagle Product Inspection technologies
Compact system provides semiautomatic testing and error proofing, helping reduce operator motion and overall cycle time
Rigaku KT-500 features HIRES technology for superior analysis of carbon steels and more
Optimized operating efficiencies for more accurate flow measurement under diverse conditions
Engineered to cover the core business needs of smaller companies and projects
MaaS will be part of product innovation, on-demand scalability, and integrating AI with data analytics

More News

Quality Transformation With David Schwinn

Quality Insider

Teaching Statistics That Help, Not Hinder, Management

Using statistics intelligently to make decisions

Published: Wednesday, September 19, 2012 - 13:55

As I titled this column, I was reminded that W. Edwards Deming liked to say, “The most important numbers are unknown and unknowable.” But some numbers are important, and most managers do not know how to manage them. I don’t want to sound like a complainer, but this issue has been close to my heart for nearly 30 years, and it arose powerfully for me as I was preparing to teach a statistics course that I hadn’t taught in an academic environment before. I’ll share my story so you can get a sense of my biases and passions for this topic.

I don’t remember formally learning anything about statistics or variability during my undergraduate engineering education. We could find a formula for nearly every situation and get an exact answer. That ended with my senior design project when we were told to use all those formulas and get those exact answers, then multiply the answers by a “design factor” of 200–400 percent. That was for safety I thought, but in retrospect, some of it was because up to that point, we had unknowingly ignored the variation inherent in the design-and-build processes. I then had to complete my final thesis in which I generated quantitative prediction models about machine downtime. My advisor showed me how to calculate and include statistical confidence limits. I used them as I was told, without really understanding where they came from.

In graduate school, I took courses in business statistics and in operations research. Given that I could barely understand our instructor who spoke with a heavy foreign accent, I got through the course just fine by plugging and cranking the formulae, just as I had done in engineering school. I still did not understand the underlying theory. At Ford, when our corporate operations research folks could not solve a big operations problem, Deming solved it in 10 minutes with a pencil, paper, and a control chart. Years later, when my wife, Carole, and I were working with Russ Ackoff, the co-author of the pioneering textbook on operations research, he declared that operations research in America was dead.

As I review my early career in engineering, management, quality, manufacturing, design, and research, I can remember only two areas where we used statistics. We unknowingly used inferential statistics to inspect incoming parts and we used control charts in another office to monitor and try to improve the quality of a different set of incoming parts. Deming and others later taught me that managers need to understand analytic studies in statistics. The primary tool for those studies, of course, is a control chart. I did not learn about control charts in school. Deming, Professor David Chambers, and a few others taught me the power of analytic studies to influence the future, vs. the power of enumerative statistics (essentially descriptive and inferential statistics) to make a decision about what you have in your hand—great for deciding whether or not to accept a shipment of material.

At Ford, we started applying Deming’s theory on a grand scale. After I left Ford, I helped other manufacturing organizations use control charts to improve their operations. After a couple of years, we started to help manufacturing organizations to improve things beyond the factory floor, such as usage of resources, timeliness of orders and estimates, and employee turnover. We used control charts to reduce student dropout rates in educational institutions, reduce teller wait times in banks, reduce repair time in government military facilities, reduce resource usage at utilities, streamline benefits-providing processes at insurance companies, and increase sales at printers, stock brokerages, and banks. All the while, we noticed plenty of evidence in the media that most people did not understand basic variation… two or three points does not a trend make. Finally, I’m ready to tell you about my most recent reminder of my concern.

I have been asked to teach managerial statistics for the first time this fall. The course has been offered for some years, but this is the first time I have been asked to teach it. I found both the syllabus and the textbook to be disappointing because of the heavy emphasis on enumerative studies. I also found the textbook to be very expensive. Remembering the series of “Statistics for Statisticians” workshops Deming used to lead toward the end of the 20th century and the lines of academicians who emotionally confessed to Deming that they had never adequately explained the limitations of enumerative studies to their students, I expected to easily find an alternative textbook. As I contacted academic colleagues, I found that they have frustrations similar to mine with no easy solutions. Again, I was deeply disappointed. I was forced to create a course pack. Thank goodness, I had PQ Systems’ Transformation of American Industry (QIP Inc., 1985) student activity guide and Total Quality Transformation trainer materials to lean on. All this gets me to the point of this column.

I have now committed to teach managerial statistics in a way that, at least based on my own experience, truly helps my students–future and current managers–to use statistics intelligently to make decisions. I am asking you to do the same with the managers of your organizations. Every manager watches numbers. Please help them to do so intelligently and help them to figure out which numbers to pay attention to. I expect some of the managers in your organizations already do use analytic studies of data with which to make intelligent decisions. If you can share such examples with me, I would love to share them with my students. That’s it. Please help your own organization make better decisions and help me better teach my students how some managers already make such decisions.

I am particularly interested in your feedback to this column. It will be useful to try to achieve Deming’s purpose for the transformation of western management.

Discuss

About The Author

Quality Transformation With David Schwinn’s picture

Quality Transformation With David Schwinn

David Schwinn, an associate of PQ Systems, is a full-time professor of management at Lansing Community College and a part-time consultant in the college’s Small Business and Technology Development Center. He is also a consultant in systems and organizational development with InGenius and INTERACT Associates.

Schwinn worked at Ford’s corporate quality office and worked with W. Edwards Deming beginning in the early 1980s until Deming’s death.  Schwinn is a professional engineer with an MBA from Wright State University. You can reach him at support@pqsystems.com.  

 

Comments

Statistics for Management

David, I provide statistics consulting for pharmaceutical consulting. I have learned from experience that expressing or reporting statistical analysis by graphical methods communicates best with management. Providing understanding of assumptions, the terms level of confidence, power, type 1 and 2 errors, and false acceptance and false rejection rates gives management the tools to understand their processes. Repeatability (precision), systemic bias and variance components are important for management to master - and I demonstrate them graphically.

Regards,

Stan Alekman 

Similar story

Hi, David, great story. I, too, have been appalled at what we're expected to teach as "business statistics." I taught an MBA course for a couple of years. It was a good refresher for enumerative studies, and had some very interesting problems for conditional probability and chi-square contingency analysis, but most of the rest of it was useless for managers, except as an intro to some of the concepts. The textbook had one chapter on control charts, and it was terrible...limits based on three standard deviations, etc. As a part-time adjunct, though, I had no input at all into what was taught. I steered those students who seemed interested in further study to Wheeler's books (especially "Making Sense of Data").

If you want an example, you might look at my QD article on Red-Green Dashboards. It tells the story of how I was able to switch a manager from using just red or green to using SPC. That might be interesting for your students. If you need more details or data, I'd be happy to provide them.

Refreshing article!

Great observations David and I would like to say something witty and intelligent, but you have stated the situation all too well.

Control charts at their core are simple, visual tools, but without the management support to hold everyone accountable, we are indeed heading for dire straits.  How can a manager hold their employees accountable if he/she does not recognize the value of the tool.  We can never hope to achieve success for the individual, departmental and company if we can effectively problem solve and understand all the weaknesses within our processes.  Ego, fear, politics and ignorance debilitate use and effectiveness of control charts and SPC operational arena.  When you hear peoople say things like,"I was forced to come to this training" or "HR told me I need this training for an up and coming audit", it speaks to the disconnect between the goals of the company, the management and the employees.  My own training and experiences are mix of success and failure, but I recall with great clarity the qualities of the finest managers I had the priviledge to work for and worth with on several differenct projects.  These successful leaders were confident, mentors, coachs, decisive, self-disclipined and always held their team accountable.

Sincerely,

Bob

Back in the 1980's, I also

Back in the 1980's, I also used materials from Transformation of American Industry. I caution you to think carefully before you use their material which, at the time, was NOT based on Shewhart's original work. I suggest you utilize the published works for Dr. Donald Wheeler, especially books like "Understanding Variation: The Key To Managing Chaos" and "Normality and the Process Behavior Chart." Steve Moore

I agree with Steve's comment

I agree with Steve's comment on using Dr. Wheeler's books and methods.  I took his week long class and it really opens your eyes on how simple using process behavior charts can be and the results generated.