Armand Feigenbaum: The Forgotten and Rarely Mentioned ‘Quality Guru’

       As I write this PIP, it was slightly more than a week ago the last of the post-World War Two ‘quality gurus’, Armand Feigenbaum, passed away.  You didn’t know that?  I didn’t read or hear about it either shortly after it happened.  Unfortunately I saw some brief mentions of his passing in the social media groups but may have missed others.  I can’t believe this and this is a disservice to a man who made monumental contributions to our profession. 

We deify W. Edwards Deming, Joseph Juran, or Phillip Crosby.  All of them made significant contributions to the quality profession and I’m not denying that.  Feigenbaum, who made many contributions to our profession, made his mark in the United States, so he never got the press and the lemming like worship as those gurus above.  Maybe he was even more ahead of his time than they were. 

Feigenbaum made his mark in the United States right after World War Two when someone who took the approach he advocated was ignored, or worse, by nearly all companies.  I’ve never been able find out why.  Maybe it was because he did not seek the same level of publicity or have an entourage of individuals who sought to profit from his wisdom as the other quality gurus.  He was the first ‘quality guru’ I studied.  While I learned a lot from the other gurus above, as I read their wisdom they repeated many of the concepts Feigenbaum had already mentioned and advocated.

Feigenbaum contributed far more to today’s quality and process improvement movement than most in the profession now understand.  He advocated the concept of ‘Total Quality Control’ which was the title of his landmark work published more than fifty years ago.  The idea of a ‘hidden plant’?  Yep, that’s his.  But in my view his most significant contribution was to focus on quality costs, a core concept.  That approach was later adapted to six sigma which lead to its wider adaptation by business where previous quality and continuous improvement methodologies ran out of gas or fell on their face.

Finally what company did Feigenbaum work for when he applied these principles?  What company is noted as the one which really made six sigma a core part of business?  General Electric and I don’t think that is a coincidence.

Categorical Data Analysis: Sometimes That’s All You Can Get and That is Okay

      If you work in manufacturing, data collection is not usually a problem.  By their nature these operations give off numerous amounts of data and information.  The problem is usually to capture all of it and then filter out what you need from the whole vast collection.

      The world of services and transactional six sigma is more of a challenge.  By their very nature, these operations do not throw off the vast quantities of continuous data.  Yes, transaction counts and time duration are sometimes available. But many transactional process vary significantly in complexity within an area of study so you cannot make the assumptions we do in manufacturing.  It’s not thousands of one uniform product rolling down a conveyor belt.

      What is one to do?  Frequently transactional data is classified into categories.  For example, customer service operations classify the resolution of a customer contact into categories and then various subcategories.  On numerous occasions, teams I work with use Pareto analysis to drill down to root cause of problem areas of focus in these types of operations.

      This is definitely not an ideal approach to take.  But sometimes that is all the data you have and there might be a lot of it to work with.  Also many operations have cyclicality to their data so the frequently espoused idea to ‘take two or three months’ worth of data and use that’ could be a bad idea.  There’s can also be a ‘Hawthorne Effect’ too.  Both of these issues are not generally brought up or acknowledged by the ‘data experts’ who should know better.

      So the next time you have a process improvement opportunity but only categorical data, don’t lose heart.  You can use six sigma rigor to perform the analysis and still improve a process.  The results may positively surprise you.