Content By Harish Jose

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By: Harish Jose

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 19th-century figure of speech—“pull oneself over a fence by one’s bootstraps.” Another description is to start with something small that over time turns into something bigger—a compounding effect from something small and simple.

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By: Harish Jose

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 that everything is static, the customer will always have the same requirements, and will be happy if the specifications/requirements are met.

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By: Harish Jose

I came across an interesting phrase recently.

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By: Harish Jose

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 depends!”

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By: Harish Jose

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.

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By: Harish Jose

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 “radical change or improvement.” Kakushin is another Japanese word that means “innovation” and is used synonymously with kaikaku.

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By: Harish Jose

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 “fuzzy concepts.” I am using the term in a loose sense and will not go into depth or specifics.

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By: Harish Jose

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 capable of teaching in a humorous and engaging way. One of the gems in the book is, “Which way you should go depends on where you are.”

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By: Harish Jose

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 learning about epistemology for a while now, and I find it an enthralling subject.

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By: Harish Jose

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.