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Keeping Up with the Quants: Your Guide to Understanding and Using Analytics Hardcover – June 11, 2013

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Keeping Up with the Quants: Your Guide to Understanding and Using Analytics + Big Data at Work: Dispelling the Myths, Uncovering the Opportunities + Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
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Product Details

  • Hardcover: 240 pages
  • Publisher: Harvard Business Review Press (June 11, 2013)
  • Language: English
  • ISBN-10: 142218725X
  • ISBN-13: 978-1422187258
  • Product Dimensions: 0.8 x 6.2 x 9.5 inches
  • Shipping Weight: 15.5 ounces (View shipping rates and policies)
  • Average Customer Review: 3.6 out of 5 stars  See all reviews (21 customer reviews)
  • Amazon Best Sellers Rank: #176,046 in Books (See Top 100 in Books)

Editorial Reviews


Shortlisted for CMI Management Book of the year award 2013 (New Manager category)

“an accessible and timely introduction to the data mining work of quantitative analysts.” Named it one of “Four Books [that] Should Top Every Marketer’s Summer Reading List.” —

“goes into fascinating detail about how Intel and other successful companies—including Verizon Wireless, TD Bank Group, and Merck—help managers and data scientists understand each other well enough to collaborate effectively.” — CNNMoney/Fortune magazine

“perfect for professionals who want a better grounding in understanding and applying data results to business goals” — Midwest Book Review

“Written for readers without a business degree or background in statistics, Keeping Up With the Quants explains how to read, interpret, and glean value from your data.” — T+D magazine (American Society for Training & Development)

“the book makes for great reading for leaders trying to corral data in their organization.” — Small Business Trends (

“Decision makers who want to understand how to utilize Big Data have a useful primer in Keeping Up with the Quants." — BizEd magazine

“a terrific book for those who aspire to be data-savvy consumers or managers, even for those who might become quants one day themselves.” — Seeking Alpha

ADVANCE PRAISE for Keeping Up with the Quants:

Erik Brynjolfsson, professor, MIT Sloan School of Management; coauthor, Race Against the Machine
“As digital information becomes ever more abundant, quantitative literacy becomes ever more essential. There is no better guide to this new landscape than Keeping Up with the Quants.”

Daryl Morey, General Manager, Houston Rockets—
“Tom Davenport is the number one analytics expert in the world today. Whether you are an executive looking to integrate analytics in your decision making or a manager seeking to generate better conversations with the quants in your organization, this is the book for you.”

Jim Goodnight, cofounder and CEO, SAS—
“Analytics experts understand that the path to knowledge includes advanced data analysis. To bring everyone else up to speed, this book is required reading.”

Dr. Seung-Han Lee CBE, Chairman and CEO, Homeplus Group (Tesco Korea)—
“Insight comes from analytics. You can learn how to find treasure in your data from this book.”

Tim Phillipps, Deloitte Touche Tohmatsu Limited Global Leader, Deloitte Analytics—
“Analytics is not just a fad—it’s the future. If you are looking for a competitive data edge, this book is for you.”

Dr. Gary W. Loveman, Chairman and CEO, Caesars Entertainment, Inc.—
Keeping Up with the Quants provides a compelling and accessible road map for managers to understand the process by which analytic questions are framed, examined, and turned into powerful business insights.”

About the Author

Thomas H. Davenport is the President’s Distinguished Chair at Babson College and a research fellow at the MIT Center for Digital Business. He is also a senior advisor to Deloitte Analytics and the cofounder and research director of the International Institute for Analytics. Davenport is the coauthor of Competing on Analytics and Analytics at Work. This is the seventeenth book he has authored, coauthored, or edited.

Jinho Kim is a professor of business and statistics at the Korea National Defense University and the research director of the KNDU Lab for Analytics Research. He holds a PhD from the Wharton School and is the author of six books published in Korea, including the bestselling 100 Common Senses in Statistics and Freak Statistics. He has developed and run an educational program for building individuals’ analytical skills. His current research focuses on the use of analytical methods to address various issues in business and society.

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Customer Reviews

This book is pitched so low that it is of little value.
Thomas Davenport and Jinho Kim have written an excellent - easy to read book about what, why and how the Quantitative Analyst is, does, and relates to business.
Jeffrey L. Ridings
If you see any truth in that at all, this book is a must read.
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Most Helpful Customer Reviews

21 of 22 people found the following review helpful By Mark Graham on June 13, 2013
Format: Hardcover
With data analysis becoming more important in every kind of business and organization (highlighted by Netflix, Amazon, Moneyball, and Nate Silver's political blog 538 among many others), this book offers timely advice. Keeping Up with the Quants explains the basic groundwork of the types and workings of data analysis. However, you need not be a quant to understand this book. In fact it is geared to non-quants who want to better understand how to work with the number crunchers/analysts. Even if you don't actively do the statistics yourself, it is still helpful to get up to speed on how to think about the bigger picture for using analytics.

Other books likely to be helpful include Nate Silver's bestseller The Signal and the Noise: Why So Many Predictions Fail -- but Some Don'twhich makes statistical thinking fun to read about. A Lessor known work (which I learned about it in Silver's book) is Paul E. Meehl's classic Clinical Versus Statistical Prediction. This book is definitely more technical than Silver's but is geared to working with softer, psychological/behavioral issues (for reviews of the out of print edition go here: Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence, for a lessor expensive edition here: Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence(at this writing only the out of print edition has reviews, but it can be pricey).
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20 of 21 people found the following review helpful By Lauren Hirs on August 11, 2013
Format: Hardcover
Keeping Up With the Quants was interesting enough to keep me (a 9-year veteran of a predictive analytics field) reading to the end, but I frequently felt like the book was oversimplified - even for "non-quants." If there are professionals out there who don't know some of these basics, I'm scared for the future of business. If you already know different chart types, statistical basis like R-squared and regressions, and that correlation does not equal causation, you may want to skip. That said, it's a quick enough read that it's worth a look for the gems hidden within it.

I'd judge this an ideal book for a student or new grad looking to understand basic concepts of analytics, but maybe not for experienced workers.
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Format: Hardcover
Almost everything most business leaders know about analytics they have learned from Tom Davenport and the material he provides in his books, notably in Competing in Analytics and Analytics at Work. In a more recent book, Judgment Calls, he and co-author Brooke Manville offer "an antidote for the Great Man theory of decision making and organizational performance": organizational judgment . That is, "the collective capacity to make good calls and wise moves when the need for them exceeds the scope of any single leader's direct control." The more non-quants there are in a given organization, the better prepared that organization will be to take full advantage of the results that quantitative analysis can produce, hence the importance of Judgment Calls.

Davenport wrote Keeping Up with the Quants in collaboration with Jinho Kim to demonstrate how quantitative analysis works -- even if (especially if) their reader does not have a quantitative analysis background -- and how to make better decisions. "Analytics can be classified as descriptive, predictive, or prescriptive according to the given methods, [applications,] and purpose." They examine three analytical thinking stages and how to apply them and then shift their attention to six steps of quantitative analysis. I commend them on their skillful use of various reader-friendly devices that include boxed mini-commentaries (e.g. "The Danger of NOT Thinking Analytically," Pages 19-21), Worksheets, Tables (e.g. 5-1, "Data-mining software for finding patterns in data," Page 140), Figures (e.g. 6.1, "The process of becoming a proficient quantitative analyst," Page 156), a "Summary" at the conclusion of Chapters 1-13, and real-world examples of what can be learned (i.e.
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15 of 18 people found the following review helpful By Let's Compare Options Preptorial TOP 500 REVIEWER on June 10, 2013
Format: Hardcover
If you read the literature about new grads unable to find jobs except at McD's, one exception is a new category of job and profession called "Data Scientist" which started being used as late as 2009/2010. There now even is a CDSO--Chief Data Science Officer-- in some data intensive firms! IF your team doesn't yet have a CDSO, tell them to create the position and give it to you, especially if you're reading this review and considering purchasing this book. Entry data science: $90K range; Manager: $165K; CDSO: $220K including options, etc. (Source: DS assn.).

This little gem won't turn you into a data wonk overnight, but it IS a "condensed" Data/ MBA course (especially quantitative analysis in IT) showing the most current aspects of analysis from a big data vantage point. To be brutally honest, folks who got their MBAs even as recently as four years ago, and studied linear programming etc., are now having to once again reinvent themselves with the much more heavily statistical nature of mining, machine learning, Web X.o, etc.

My premise is: to be successful, we ALL need to be data scientists today, whether or not it fits our current job description! If you see any truth in that at all, this book is a must read. It avoids the deep math and algorithms behind the analysis, but gives very clear analogies, examples, and techniques in English to help with the most important steps: interpretation, relevance and use.

A recent trend in big data is "ala carte" dashboards, where users configure Sharepoint and other tools via Excel etc. LOCALLY. If you're not a quant, you ARE a quant CUSTOMER, and deserve to maximize the tools you have in front of you. Asking the right questions is 75% of getting that benefit.
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