Statistical Engineering Links Statistical Thinking, Methods and Tools

In Closing the Gap Roger W. Hoerl and Ronald D. Snee lay out a sensible case for focusing on statistical engineering.

We’re not suggesting that society no longer needs research in new statistical techniques for improvement; it does. The balance needed at this time, however, is perhaps 80% for statistics as an engineering discipline and 20% for statistics as a pure science.

True, though I would put the balance more like 95% engineering, 5% science.

There is a good discussion on LinkedIn:

Davis Balestracci: Unfortunately, we snubbed our noses at the Six Sigma movement…and got our lunch eaten. Ron Snee has been developing this message for the last 20 years (I developed it in four years’ worth of monthly columns for Quality Digest from 2005-2008). BUT…as long as people have a computer, color printer, and a package that does trend lines, academic arguments won’t “convert” anybody.

Recently, we’ve lost our way and evolved into developing “better jackhammers to drive tacks”…and pining for the “good ol’ days” when people listened to us (which they were forced to do because they didn’t have computers, and statistical packages were clunky). Folks, we’d better watch it…or we’re moribund

Was there really a good old days when business listened to statisticians? Of course occasionally they did, but “good old days”? Here is a report from 1986 the theme of which seems to me to be basically how to get statisticians listened to by the people that make the important decisions: The Next 25 Years in Statistics, by Bill Hunter and William Hill. Maybe I do the report a disservice with my understanding of the basic message, but it seems to me to be how to make sure the important contributions of applied statisticians actually get applied in organizations. And it discusses how statisticians need to take action to drive adoption of the ideas because currently (1986) they are too marginalized (not listened to when they should be contributing) in most organizations.

Christine Anderson-Cook: I do feel that we as statisticians are making some good strides towards being involved in all aspects of product development, process improvement and decision-making.

I don’t see the goal of Roger and Ron’s article as to give ourselves a new label – as clearly that is unlikely to have any lasting impact – but rather to give clarity and definition to the category of work that takes available tools and makes them applicable, relevant and appropriate to solving key problems that will play an important role in shaping the success of our institutions.

As Chair-Elect of the Statistics Division, I welcome discussion about how the division can have a leadership role in helping our members make a difference in their jobs.

I think the role of ASQ statistics division should be to increase the effective adoption of statistical thinking in the management of organization in the United States. New tools are fine, but the paucity of adoption of known useful statistical tools is the big issue. Organizations in the USA need huge improvement in their statistical thinking (acknowledging variation barely exists in management decisions). Some people can focus on developing new and more complicated tools – and that can be quite exciting. But there is a huge need in just getting basic applied statistics used. The place I think focus is needed is on making that happen. And that means working on getting statistical thinking adopted by managers and senior executives.

Making this happen requires a good deal of management understanding and a focus on tools and methods that work and people will use and learn from. I think the focus that is most valuable is on how to get good statistical thinking adopted and statistical tools used well.

FYI, my father, William G. Hunter, was the founding chair of the ASQ Statistics Division.

Related: Statistical ConsultingThe Exciting Life of Industrial StatisticiansSearch Share Data – Checking the ACSIQuality, SPC and Your Careerposts on design of experimentsOpportunities and Challenges for Industrial Statisticians in the 21st Century by Gerald J. Hahn – SPC: History and Understanding

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