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Understanding Variation: The Key to Managing Chaos
Great book
158 pages, Hardcover
First published January 1, 1993
52 people are currently reading
1,279 people want to read
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Displaying 1 - 30 of 50 reviews
January 17, 2023
Absolutely incredible. Required reading for anyone who wants to become data driven in business. And all this in 162 pages!
February 9, 2017
I have followed Mark Graban's Lean Blog and podcast for many years and I have observed that he truly has strong and open opinions on Lean and Six Sigma and how/where they intersect. After Mark mentioned how influential this book was in both a podcast and subsequent blog, I decided I should check it out. Responses to his post on Linkedin also confirmed this was a good book choice for someone who is a constant student in all things Continuous Improvement.
I was expecting a book that was heavily laden in theory and statistical formulas. Although this book does cover some very basic statistical formulation, the book is NOT about theory, but how to put statistics to work for you today.
Although the author holds a Phd. he does not write this book as an academic looking for peer review. The book uses very plain English and rather than using the common terminology used in most 6 Sigma or Statistics books - he has chosen to use terms and stories that will appeal directly to managers and leaders.
The cases he discusses, although fictitious, are true representations of things that occur in business everyday. People "squirreling" away inventory, making reactionary decisions based on shifts in averages, and even thinking that you are doing great, when your business is tanking.
Read this book right through the appendix. In one of the 3-4 appendices, the author gives you a case and suggests you work through it on your own. This pulls together the learning in the other chapters.
This is a very quick and easy read and I am very glad I listened to this recommendation. Process control meets leadership!
I was expecting a book that was heavily laden in theory and statistical formulas. Although this book does cover some very basic statistical formulation, the book is NOT about theory, but how to put statistics to work for you today.
Although the author holds a Phd. he does not write this book as an academic looking for peer review. The book uses very plain English and rather than using the common terminology used in most 6 Sigma or Statistics books - he has chosen to use terms and stories that will appeal directly to managers and leaders.
The cases he discusses, although fictitious, are true representations of things that occur in business everyday. People "squirreling" away inventory, making reactionary decisions based on shifts in averages, and even thinking that you are doing great, when your business is tanking.
Read this book right through the appendix. In one of the 3-4 appendices, the author gives you a case and suggests you work through it on your own. This pulls together the learning in the other chapters.
This is a very quick and easy read and I am very glad I listened to this recommendation. Process control meets leadership!
September 22, 2010
No Trouble: predictable & conforming to spec (leave it alone)
Product Trouble: predictable but too much non-conformance (change the process)
Process Trouble: unpredictable with conformance (find & remove sources of unpredictability - cheaper than changing the process)
Double Trouble: unpredictable & too much non-conformance (find & remove first, then see where you are)
Specification is the Voice of the customer. Process Limits are the Voice of the Process. If the process cannot meet the specs, it must be changed. (Or the specs must be changed.)
To improve a process, listen to the voice of the process / natural process limits. Changing the specs without acknowledging the impact on the process will only cause bad behavior.
Goals/specs are a major source of "creativity" - processes can not operate better in response to the Voice of the Customer (specification or goal). They can only improve if the process itself is improved.
Product Trouble: predictable but too much non-conformance (change the process)
Process Trouble: unpredictable with conformance (find & remove sources of unpredictability - cheaper than changing the process)
Double Trouble: unpredictable & too much non-conformance (find & remove first, then see where you are)
Specification is the Voice of the customer. Process Limits are the Voice of the Process. If the process cannot meet the specs, it must be changed. (Or the specs must be changed.)
To improve a process, listen to the voice of the process / natural process limits. Changing the specs without acknowledging the impact on the process will only cause bad behavior.
Goals/specs are a major source of "creativity" - processes can not operate better in response to the Voice of the Customer (specification or goal). They can only improve if the process itself is improved.
February 20, 2019
In fairness to the book, I doubt its aimed at me. This book was given to us by my company when we took a course normally meant for managers. It is very much directed at people who needs to be convinced using statistics is a good idea, not those who have already drunk the cool-aid.
April 23, 2011
I never thought a book on statistics would be exciting, but this one was! It helps that it’s full of stories, stories of the misuse of statistics in management, highlighting the “numerical naiveté� surrounding us (vi). Businesses are managed today off the typical monthly management report; Wheeler shows the irrelevance of such reports for making sound managerial decisions. Graphing the data in control charts present much more meaningful information, and allow one to distinguish between the variation inherent within the process and data that legitimately signal that the process has changed.
The author’s principles are simple and his examples from real life are convincing. He shares more than one horror story of managers being rewarded for the changes they implemented when sound data analysis later revealed that their “improvements� were nothing of the sort.
The author’s principles are simple and his examples from real life are convincing. He shares more than one horror story of managers being rewarded for the changes they implemented when sound data analysis later revealed that their “improvements� were nothing of the sort.
March 9, 2024
Distilled a complex subject down to the crucial events, then over stretched those to fill out enough pages to claim it's a book instead of a pamphlet. Good examples, though.
February 19, 2020
Every manager should read this book. In essence, comparing the current month to the average of previous months will be “good� half the time and “bad� half the time.
This book explains a simple, more educated approach to understand variation and the more appropriate questions to ask and when to ask them.
This book explains a simple, more educated approach to understand variation and the more appropriate questions to ask and when to ask them.
January 1, 2025
What a fantastic book. I wish I had read it sooner. Written simply and easy to follow. And extremely insightful
May 1, 2019
Read this for my Six Sigma Black Belt training.
November 11, 2024
coworker lent me this book. Quick and EZ read abt data in business
May 3, 2022
Li em 1999 esse livro que me ajudou muito a montar um sistema de controle de defeitos no processo que eu controlava na época. Atualmente é a metodologia padrão para se medir e analisar defeitos em processos na empresa que trabalho.
Read
June 11, 2020for work....need i say more?
September 8, 2011
Clear, simple and to the point explanation of, a apriori, a hard topic.
The book's goal is achieved, the reader will understand variation
The book's goal is achieved, the reader will understand variation
Want to read
January 1, 2024Ced rec
new thread ->
new thread ->
May 18, 2021
A classic book for all those who want to use data better.
I had heard about this book for a number of years and really looked forward to getting stuck in. Now, a caveat from me - I already use control charts in my work and a lot of the arguments against the use of traditional management reporting and targets expounded in the book I have eulogised for a fair few years.
What's notable of course is that this text is over 20 years old now and yet the learning is not universal with the same problems Wheeler identified still remain today.
What you'll get in this short book is
- what problems exist in how performance is measured traditionally
- how to measure differently using control charts
- how to interpret them.
- a handy exercise to try yourself!
It's accessible, it's quick to read and it gets a massive recommendation from me!
I had heard about this book for a number of years and really looked forward to getting stuck in. Now, a caveat from me - I already use control charts in my work and a lot of the arguments against the use of traditional management reporting and targets expounded in the book I have eulogised for a fair few years.
What's notable of course is that this text is over 20 years old now and yet the learning is not universal with the same problems Wheeler identified still remain today.
What you'll get in this short book is
- what problems exist in how performance is measured traditionally
- how to measure differently using control charts
- how to interpret them.
- a handy exercise to try yourself!
It's accessible, it's quick to read and it gets a massive recommendation from me!
January 22, 2022
***I can tell that Elon Musk has read this book.***
Managing a company by means of the monthly report is like trying to drive a car by watchin the yellow line in the rear-view mirror.
data showing that food causes cancer and cancer cures smoking.
there is nothing new under the sun--just more of it.
The way these two running records move up and down together suggests that the number of home runs hit by each was a subject to some external influence. One possible explanation is that they faced essentially te same set of pitchers each season.
Since the average is generally near the mid-point of a set of data, you should expect to be above average about half the time, and to be below average about half the time.
Before a single month can be said to signal a change in the time series that single value must go beyond one of the two limits.
Managing a company by means of the monthly report is like trying to drive a car by watchin the yellow line in the rear-view mirror.
data showing that food causes cancer and cancer cures smoking.
there is nothing new under the sun--just more of it.
The way these two running records move up and down together suggests that the number of home runs hit by each was a subject to some external influence. One possible explanation is that they faced essentially te same set of pitchers each season.
Since the average is generally near the mid-point of a set of data, you should expect to be above average about half the time, and to be below average about half the time.
Before a single month can be said to signal a change in the time series that single value must go beyond one of the two limits.
September 11, 2019
Not exactly a fun read, but a pretty light read as statistics books go. Wheeler did a good job of convincing me of the utility of process behavior charts in understanding variation in a process, evaluating what is normal variation and abnormal variation, and then using the data to prompt appropriate questions for process improvement.
Fairly quick to get through and a mostly casual tone throughout.
Read as part of Intermountain's Advanced Training Program (ATP) course in Quality Improvement.
Rating: PG, nothing concerning but certainly nothing here for kids.
Fairly quick to get through and a mostly casual tone throughout.
Read as part of Intermountain's Advanced Training Program (ATP) course in Quality Improvement.
Rating: PG, nothing concerning but certainly nothing here for kids.
February 23, 2018
Great book. It provides even more tools behind the Deming Management method and a way to truly improve. The math is simple and he does a great job of demonstrating how hard math really is only for the mathematicians and demonstrates how it does not and cannot help as much as the methods developed and espoused by Dr. Shewhart and Dr. Deming. Recommended for all.
April 4, 2022
I'm a Process Engineer and this book was not only applicable to what I do, but also an enjoyable read! It was very easy to understand with lots of graphs and examples. It's educational, and even a bit sassy at times. I will definitely refer back to this book when I need to analyze data
March 16, 2018
A must read from an authority.
April 20, 2019
Required read for a certification at work. The book does a good job giving you an understanding of how important data is when it comes to process improvement.
March 29, 2020
A fantastic book about management in the age of data-driven decision-making.
September 22, 2020
Relevant for everyone in the WBR!
September 20, 2021
Good information; text book read
September 29, 2021
Never thought a book on statistics could be that interesting. The bad part is to realize how poorly I have been analyzing data so far
March 8, 2022
It looks like one single concept was discussed in all chapters of the book. It is great how the author presents examples of different industries.
May 3, 2022
I learned real stuff:
You only need 30 data points.
Everything falls within 3 standard deviations of the mean.
Now I can make histograms and Pareto charts. What in the world.
You only need 30 data points.
Everything falls within 3 standard deviations of the mean.
Now I can make histograms and Pareto charts. What in the world.
May 30, 2022
Excellent short read on understanding process variability.
August 2, 2022
An important book on understanding statistical process control.
November 23, 2023
Wish i had read this book 15 years ago. Fantastic.
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