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netondia's review against another edition
4.0
A great book that is sometimes a little hard to follow. It's pretty clear that this was meant to be used within the management classes given by the Deming Institute. A lot of the statistical tools you are told to apply with little explanation, and in a couple case you are told by Deming to "ask the instructor" if you have questions. However for the most part, the math used is pretty simple and have case studies that apply them.
The examples mostly deal with manufacturing as you'd expect from a book written in the 80s, but most of the advice is pretty timeless and applicable in any industry. It's a good read for managers and anyone interested in the history of engineering.
The examples mostly deal with manufacturing as you'd expect from a book written in the 80s, but most of the advice is pretty timeless and applicable in any industry. It's a good read for managers and anyone interested in the history of engineering.
teibrich's review against another edition
2.0
This book is a legend, and at the same time hard for me to recommend as I found it very difficult and somewhat exhausting to read. It feels like a long collection of lecture notes often contributed from various sources.
What I did like is the perspective I got on the state of the American economy at the time where the book was written: The focus here is really on a call to action to improve the quality of the industry.
Key learnings for me:
1) Focus on statistical control. A process without it is just chaos without clear capabilities
2) Use the upper and lower control limits to decide if a defect is related to a special cause or common cause. The first can be attributed to the person working on the item or can be resolved there. The second (common cause) is really just an outcome of the system and is the responsibility of management. Unfortunately, common causes are often not addressed by management and cause frustration.
3) Awards and rewards based on the variance of output in the system are really just like playing the lottery.
What I did like is the perspective I got on the state of the American economy at the time where the book was written: The focus here is really on a call to action to improve the quality of the industry.
Key learnings for me:
1) Focus on statistical control. A process without it is just chaos without clear capabilities
2) Use the upper and lower control limits to decide if a defect is related to a special cause or common cause. The first can be attributed to the person working on the item or can be resolved there. The second (common cause) is really just an outcome of the system and is the responsibility of management. Unfortunately, common causes are often not addressed by management and cause frustration.
3) Awards and rewards based on the variance of output in the system are really just like playing the lottery.
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