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Turning Numbers into Knowledge: Mastering the Art of Problem Solving
Full of tools, tricks, and tips for solving problems in the real world, this book serves as an ideal training manual for those who are new to or intimidated by quantitative analysis and acts as an excellent refresher for those who have more experience but want to improve the quality of their data, the clarity of their graphics, and the cogency of their arguments. In addition to containing numerous updates to the contents—references, URLs, and reading lists—this second edition includes a new foreword, revised chapters, and an epilogue. Mastering the art of problem solving takes more than proficiency with basic calculations; it requires understanding how people use information, recognizing the importance of ideology, learning the art of storytelling, and acknowledging the important distinction between facts and values. Intended for executives, professors, and students, this guide addresses these and other essential skills.
247 pages, Paperback
First published April 1, 2003
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Displaying 1 - 16 of 16 reviews
November 24, 2012
Koomey's book "Turning Numbers into Knowledge" is definitely far more concerned about the process of analyzing data and presenting data than it is about mastering the art of problem solving. That is, Koomey does a fine job drawing together topics on research, analyzing data, presenting data, and introductory critical thinking skills. However, those looking for heuristics to use as approaches to solving problems will not find any here (at least not in the strict sense of, say, something like those found in works by Gyorgy Polya--though props must be given to Koomey for at least mentioning Polya).
For what this books does provide, Koomey does a not only a very nice job of presenting the his techniques and information, but it is also an incredibly well-written book. Koomey does provide both good and bad examples and explains how they contrast and what makes the good examples effective. There is some repetition relevant to certain principles Koomey is trying to reinforce throughout the book, and while I understand the purpose of such reinforcement, I did find it tiresome at times. Also, no statistical methods or rigorous mathematical examples are covered; these are left to other books, I suppose. That is, anyone looking for something akin to what they would find in a statistical "Design of Experiments" class will not find any such treatment here.
Overall, though, Koomey's book is a good one in that it does provide some business-esque (read: math-lite) approach to data analysis, and it does focus on the general craft of data analysis and presentation. It aims to being an introduction with breadth, and it does this nicely. There is an extensive "Further Reading" section for those that wish to peruse other sources Koomey uses and references.
For what this books does provide, Koomey does a not only a very nice job of presenting the his techniques and information, but it is also an incredibly well-written book. Koomey does provide both good and bad examples and explains how they contrast and what makes the good examples effective. There is some repetition relevant to certain principles Koomey is trying to reinforce throughout the book, and while I understand the purpose of such reinforcement, I did find it tiresome at times. Also, no statistical methods or rigorous mathematical examples are covered; these are left to other books, I suppose. That is, anyone looking for something akin to what they would find in a statistical "Design of Experiments" class will not find any such treatment here.
Overall, though, Koomey's book is a good one in that it does provide some business-esque (read: math-lite) approach to data analysis, and it does focus on the general craft of data analysis and presentation. It aims to being an introduction with breadth, and it does this nicely. There is an extensive "Further Reading" section for those that wish to peruse other sources Koomey uses and references.
April 15, 2014
There's plenty of very good advice in this book. But if you've been through some academic training, you've probably heard a fair bit of it before. That said, the book compiles this knowledge in a more organized manner than I've seen elsewhere. Further, while many have heard admonishments about how to present research, make comprehensible figures, etc., the advice is not always taken to heart.
However, two broad shortcomings.
1. The book is a bit dated on internet topics and research, which have progressed significantly since 2007/2008.
2. Koomey's examples of good/bad research are not so clear cut as he makes them out to be, and involve a bit of nepotism & the values-masquerading-as-numbers he so ardently warns to be careful of. Koomey's principles are fine, but one has to wonder if J. Holdren's critique of Lomborg is really the best example of exposing the flaws of poor research/numerology. It's too long to get into the details, but one could easily argue Koomey's choice of examples is more about the values of his environmental left cohort and former professors than pure numbers. At the very least, and example centering on the problematic predictions made by Holdren, Ehrlich, and other colleagues in the 60's/70's would have been just as good an example, but Koomey instead chooses to needle center/center-right ecomodernists like Lomborg, P. Huber, and M. Mills.
However, two broad shortcomings.
1. The book is a bit dated on internet topics and research, which have progressed significantly since 2007/2008.
2. Koomey's examples of good/bad research are not so clear cut as he makes them out to be, and involve a bit of nepotism & the values-masquerading-as-numbers he so ardently warns to be careful of. Koomey's principles are fine, but one has to wonder if J. Holdren's critique of Lomborg is really the best example of exposing the flaws of poor research/numerology. It's too long to get into the details, but one could easily argue Koomey's choice of examples is more about the values of his environmental left cohort and former professors than pure numbers. At the very least, and example centering on the problematic predictions made by Holdren, Ehrlich, and other colleagues in the 60's/70's would have been just as good an example, but Koomey instead chooses to needle center/center-right ecomodernists like Lomborg, P. Huber, and M. Mills.
July 5, 2021
Simple, effective tips of checking your work & finding new solves.
Enjoyed it thoroughly.
5 stars.
#Recommended
Enjoyed it thoroughly.
5 stars.
#Recommended
January 31, 2021
Give meaning to the numbers!
Jonathan Garo Koomey's book "Turning Numbers into Knowledge" is a step-by-step approach to business analysis for beginners. The basics of studying raw data as well as problem solving are all discussed in the book in a fairly easy-to-read manner, helpful for business students but also a good reference point for experienced business analysts and professors.
Mr. Koomey makes things as clear as possible when he discusses the idea of looking into different types of data. Be it a scientific report or a series of graphs showing the highs and lows of the economy in a given period of time, he provides many tips and tricks for readers to dissect the data within while at the same time avoiding the irrelevant bits. He also teaches readers how to compile and create data reports while keeping things as straightforward and up to the point as possible. It's more or less the theory of quality over quantity.
Some exercise questions are featured at the end of the early chapters, however they are few and far between. I would have liked to see questions that focused on specific case studies, rather than telling the reader to find articles and surveys online to solve the questions. I understand that the author probably wanted to keep the book as flexible as possible with the readers, however the reality is that not everybody has equal access to external sources of information, and it is therefore better to have the exercise questions based on sources available in the book itself.
Aside from that minor issue, "Turning Numbers into Knowledge" is a book worth reading if you want to learn how to solve problems more efficiently. It has all the tools necessary for beginner project analysis and creation, and is even packed with references and interesting links to websites for further information. Best of all, the book is not complicated and makes for an easy reading experience as well as a good starting point for learning the foundations of business analysis.
Jonathan Garo Koomey's book "Turning Numbers into Knowledge" is a step-by-step approach to business analysis for beginners. The basics of studying raw data as well as problem solving are all discussed in the book in a fairly easy-to-read manner, helpful for business students but also a good reference point for experienced business analysts and professors.
Mr. Koomey makes things as clear as possible when he discusses the idea of looking into different types of data. Be it a scientific report or a series of graphs showing the highs and lows of the economy in a given period of time, he provides many tips and tricks for readers to dissect the data within while at the same time avoiding the irrelevant bits. He also teaches readers how to compile and create data reports while keeping things as straightforward and up to the point as possible. It's more or less the theory of quality over quantity.
Some exercise questions are featured at the end of the early chapters, however they are few and far between. I would have liked to see questions that focused on specific case studies, rather than telling the reader to find articles and surveys online to solve the questions. I understand that the author probably wanted to keep the book as flexible as possible with the readers, however the reality is that not everybody has equal access to external sources of information, and it is therefore better to have the exercise questions based on sources available in the book itself.
Aside from that minor issue, "Turning Numbers into Knowledge" is a book worth reading if you want to learn how to solve problems more efficiently. It has all the tools necessary for beginner project analysis and creation, and is even packed with references and interesting links to websites for further information. Best of all, the book is not complicated and makes for an easy reading experience as well as a good starting point for learning the foundations of business analysis.
July 4, 2011
Simple, straightforward, right on. Koomey compiles a great set of principles and practices to follow in constructing and presenting research. Full of provocative quotes and entertaining graphics. NOT a joy read, but an enjoyable exploration of a topic that otherwise could have been maddingly pedantic.
As I was reading this book, I immediately noticed improvement in my day-to-day analytic performance.
As I was reading this book, I immediately noticed improvement in my day-to-day analytic performance.
January 20, 2016
This works well as both a reference and a good reminder of just how low the quality is for most data that you see presented - and how you can do better. If you have ever pondered just how it is that really stupid claims like "the Internet accounted for 8% of all electricity used in the US around the year 2000" ever got off the ground, much less lived as long as it has, this book is your guide to the answer.
July 28, 2022
This book somehow restored my belief in numbers and quantitative analysis. It's an excellent antidote for the many books out there that denounce statistics.
There is quality in good quantitative intelligence. A well-designed table or graph can provide new insights. But good tables or graphs are hard work. Data needs to be collected, processed, cleaned and interpreted before table design can start. Documentation is everything. Data should come with a story that does not need to be neutral, as long as readers can reconstruct it and weave their own narratives. A good table or dataset provides such basis for further analysis.
There is quality in good quantitative intelligence. A well-designed table or graph can provide new insights. But good tables or graphs are hard work. Data needs to be collected, processed, cleaned and interpreted before table design can start. Documentation is everything. Data should come with a story that does not need to be neutral, as long as readers can reconstruct it and weave their own narratives. A good table or dataset provides such basis for further analysis.
February 1, 2020
So this is my assessment of this book Turning numbers into knowledge by Jonathan B. Koomey according to my 7 criteria:
1. Related to practice - 3 stars
2. It prevails important - 3 stars
3. I agree with the read - 4 stars
4. not difficult to read (as for non English native) - 3 stars
5. too long and boring story or every sentence is interesting - 3 stars
6. Learning opportunity - 3 stars
7. Dry and uninspired style of writing - Smooth style with humouristic and fun parts - 2 stars
Total 3 stars
1. Related to practice - 3 stars
2. It prevails important - 3 stars
3. I agree with the read - 4 stars
4. not difficult to read (as for non English native) - 3 stars
5. too long and boring story or every sentence is interesting - 3 stars
6. Learning opportunity - 3 stars
7. Dry and uninspired style of writing - Smooth style with humouristic and fun parts - 2 stars
Total 3 stars
September 22, 2021
A good review of the basics.
Internet section out of date the moment it was published.
His attack at the end of Lomborg through Friel is unnecessary and quite likely incorrect. Has Koomey considered his own bias to the topic? Vested interest? Believe what you wish, but don't use a book on an unrelated topic to vent your political beliefs.
The moral of the story; take his advice and think critically, even if it means thinking critically of the book that prescribes it!
Internet section out of date the moment it was published.
His attack at the end of Lomborg through Friel is unnecessary and quite likely incorrect. Has Koomey considered his own bias to the topic? Vested interest? Believe what you wish, but don't use a book on an unrelated topic to vent your political beliefs.
The moral of the story; take his advice and think critically, even if it means thinking critically of the book that prescribes it!
April 20, 2022
A genuinely interesting book on thinking critically and then sharing and presenting your thoughts and data. There's a lot here worth considering and adding to your own approaches.
That said, large parts of it are quite dated; its approach to the internet feels straight out of 1994, but then the author references things in 2017 and you realize, oh, the new editions didn't lead to new thinking.
That said, large parts of it are quite dated; its approach to the internet feels straight out of 1994, but then the author references things in 2017 and you realize, oh, the new editions didn't lead to new thinking.
July 17, 2019
The art of making numbers talk so that non-numeric folk can understand it is rare. This book shares some of the techniques for doing that.
August 14, 2009
never under estimate the importance of your data to ink ratio!
August 23, 2009
The art of making numbers talk so that non-numeric folk can understand it is rare. This book shares some of the techniques for doing that.
December 14, 2010
Not a bad guide to writing good quantitative reports, and consuming other's reports in an intelligent way.
I do wish it had more on statistics though.
I do wish it had more on statistics though.
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December 5, 2014153.43 K828 2008
September 3, 2018
Very simple book about analysis. Many useful examples. Thorough coverage of dealing with data.
Displaying 1 - 16 of 16 reviews