Harish Jose

Harish Jose has more than seven years of experience in the medical device field. He is a graduate of the University of Missouri-Rolla, where he obtained a master’s degree in manufacturing engineering and published two articles. Harish is an ASQ member with multiple ASQ certifications, including Quality Engineer, Six Sigma Black Belt, and Reliability Engineer. He is a subject-matter expert in lean, data science, database programming, and industrial experiments, and publishes frequently on his blog Harish’s Notebook.

Wed, 05/11/2016 - 18:07
Bootstrap KaizenLean tools for humans
Wed, 10/24/2018 - 12:02
I am writing today about “bootstrap kaizen.” This is something I have been thinking about for a while. Wikipedia describes bootstrapping as “a self-starting process that is supposed to proceed without external input.” The term was developed from a…
A ‘Complex’ View of QualityCustomer-centric is more than a catchphrase
Tue, 10/02/2018 - 12:03
I am a quality manager by profession. Thus, I think about quality a lot. How would one define “quality?” A simple view of quality is “conformance to requirements.” This simplistic view of quality lacks the complexity that it should have. It assumes…
Kufu EyesProblem solving requires looking past the surface
Mon, 08/27/2018 - 12:03
I came across an interesting phrase recently. I was reading Kozo Saito’s paper, “Hitozukuri and Monozukuri,” and I saw the phrase “kufu eyes.” Kufu is a Japanese word that means “to seek a way out of a dilemma.” This is very well explained in…
Reliability Sample Size Calculation Based on Bayesian InferenceWhen is enough, enough? That depends.
Mon, 07/02/2018 - 12:03
I have written about sample size calculations many times before. One of the most common questions a statistician is asked is, “How many samples do I need—is a sample size of 30 appropriate?” The appropriate answer to such a question is always, “It…
The Best Kind of KaizenWithout understanding, improvement is unlikely
Wed, 05/09/2018 - 12:01
I have been writing about kaizen a lot recently. It is a simple idea: change for the better. Generally, kaizen stands for small incremental improvements. Here I’m going to look at what is the best kind of kaizen. The twist in the dumpling A few…
Looking at Kaizen and KaikakuKnowing when to plod and when to sprint
Mon, 03/12/2018 - 13:02
In today’s column, I will be looking at kaizen and kaikaku through the lens of the explore/exploit model. Kaizen is often translated from Japanese as “continuous improvement” or “change for better.” Kaikaku, another Japanese term, is translated as…
In Defense of Fuzzy ThinkingWith continuous improvement, wherever we are, there we are
Thu, 02/01/2018 - 12:02
It’s not easy to find topics to write about, and even if I find good topics, it has to pass my threshold level. As I was meditating on this, I started to think about procrastination and ambiguity. So my column today is about the importance of “…
Which Way You Should Go Depends on Where You AreThe dangers of misapplying linearity
Thu, 12/14/2017 - 12:02
I recently read Jordan Ellenberg’s wonderful book, How Not To Be Wrong: The Power of Mathematical Thinking (Penguin Books, 2014). I found the book to be enlightening and a great read. Ellenberg has the rare combination of being knowledgeable and…
Epistemology at the Gemba Multiple perspectives of knowledge and wisdom
Mon, 10/30/2017 - 12:03
Today I will look at epistemology at the gemba. Epistemology is the part of philosophy that deals with the theory of knowledge. It tries to answer the questions, “How do we know things, and what are the limits of our knowledge?” I have been…
Rules of Three and FiveTips for sample sizes
Wed, 08/23/2017 - 12:03
It’s been a while since I’ve written about statistics. So in this column, I will be looking at the rules of three and five. These are heuristics, or rules of thumb, that can help us out. They are associated with sample sizes. Rule of three Let’s…