Competing on Analytics

by Thomas H. Davenport

You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool.

In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.

Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.

Genres: Business, Nonfiction, Management, Science, Technology, Economics, Artificial Intelligence

218 pages, Hardcover

First published February 1, 2007

About the author

Tom Davenport holds the President's Chair in Information Technology and Management at Babson College. His books and articles on business process reengineering, knowledge management, attention management, knowledge worker productivity, and analytical competition helped to establish each of those business ideas. Over many years he's authored or co-authored nine books for Harvard Business Press, most recently Competing on Analytics: The New Science of Winning (2007) and Analytics at Work: Smarter Decisions, Better Results (2010). His byline has also appeared for publications such as Sloan Management Review, California Management Review, Financial Times, Information Week, CIO, and many others.

Davenport has an extensive background in research and has led research centers at Ernst & Young, McKinsey & Company, CSC Index, and the Accenture Institute of Strategic Change. Davenport holds a B.A. in sociology from Trinity University and M.A. and Ph.D. in sociology from Harvard University. For more from Tom Davenport, visit his website and follow his regular HBR blog.

Reviews

[Horia · Rating 3 out of 5]

I am not impressed with the information in this book. It just provides an overview for analytics.
I have to agree that the models I contains are valuable for someone (me) that doesn't work in the domain. However, I could argue that just keeping those and cutting back on useless descriptions would have made for a more concise (thus appealing) read.
The audience that I would imagine would be reading this book would be: the people that want to sell analytics to some company.

[Nam KK · Rating 1 out of 5]

Lack in depth, the book reads like an undergrad student's essay, just elevated with high-level buzzwords and jargons. Strange for an analytical book, it comes with very little figures to back its arguments up. All it has are ambiguous ones, such as: the company A applied analytical approaches, and its market value increased from X to Y. You can always refute by saying the company B, applying analytical approaches, has its market capitalization falling from $100Bn to $20Bn within n years. The book uses several companies for examples again and again, namely Netflix, Google, Amazon.com - there is nothing wrong with them, but each time he barely scratches on the surface. When he runs out of examples, he imagines ones, with names such as PulpCo, ConsumerCo, etc.

Save the earth, save some trees (they shouldn't have been cut down), and save your time by not buying this useless book.

[Willis · Rating 4 out of 5]

This is not the kind of book that you read for fun. I read it for work reasons because I've been doing more work related to analytics and how to improve business decisions based on better data. So I found this to be an extremely useful book for what I do at work in helping me to think outside of just statistical methods. The premise is that it takes a lot of different skills: computer science, statistics, business understanding, communication skills to really be able to be an analytical company. As a result, I found that this book broadened my horizons on what is possible and the future. It does not have much detail on how to actually do analytics as it focuses more on a high level view of what analytics are and how they can be of benefit.

[Celz Lin · Rating 5 out of 5]

This book discuss the importance of Data Analytics in different fields and industries. How people use analytics to compete and win. It is the weapon of the future. I was inspired by this book. I hope to read the new updated version of this book soon.

[Hristo Milev · Rating 2 out of 5]

Very little actual science. The book is mostly general comments that don't contribute anything original.

[Digna · Rating 4 out of 5]

Valuable, structured read for anyone interested in analytics.

[Yash Verma · Rating 4 out of 5]

If you want to know the areas or functions where analytics can be applied, this is the book. Book is divided in two parts, first will give information on the "Where" part of the application of analytics in an organization and second part deals with the "How" to apply it.

[Mitch · Rating 1 out of 5]

Jargon, buzzwords, dated.

It isn't clear that the authors actually know any business analytics. They have some surveys, observations, and stories. They explain that companies use data to succeed, but we already know that. There are a few useful tables, but not many. The book doesn't go very deep. It doesn't to analyze data. The book doesn't even discuss which questions to ask. Asking the right questions about data is important and you could do it without using ltos of map. I've even seen people mine data just with good ways of presenting the data-network analysis. You won't learn anything useful here.

[John Hieb · Rating 4 out of 5]

The original edition (2007) is one of the best books on the importance and impact of analytics in driving business results I have on my shelf. As a fan of Davenport's other books and articles, I was excited to read this updated version (2017). It is a high level overview, and most of the examples are new or updated. As expected, it covers a lot of new ground, as the tools, skills, and the world of information has changed significantly in the last decade. The book contains useful models for benchmarking analytical capabilities. This is a good read for managers, but there are not a lot of practical examples of how to implement or specific comparisons of tools/skills/approaches.

[David Cain · Rating 2 out of 5]

The focus in this brief volume is on trends in analytics as well as how and why organizations should improve their analytical capabilities. I would have preferred to see more details and case studies that delve into specific metrics that have helped organizations, rather than the generalities that fill out most of this text. After reading this, you will be convinced that your organization needs to improve its analytical capabilities, but this book will not necessarily give you a detailed road map that will get you there. Nevertheless, it serves as a good introduction to the topic.

[Isk · Rating 3 out of 5]

Gave me a better picture of how analytics is used in other companies (and how to better convince people that analytics is needed =)), but... Definitely to be skimmed.

[Dana · Rating 4 out of 5]

My boss gave me this book as I entered the world of analytics and it was a perfect primer for what to expect and how to think about solutions to my company's problems.

[Dewayne · Rating 4 out of 5]

This books still carries much relevance today despite being written over 10 years ago in 2007. Authors Thomas Davenport and Jeanne Harris were on the leading edge of sharing the new standard for business competition in this book. The standard is about competing on data with analytics. This Harvard Business School book is written as expected with a heavy academia structure. It first defines what it means to be analytically driven as a company before providing a framework to assess and help mature your organizations analytics capabilities regardless of role. 

I found it interesting seeing the fruits of labor from many of the companies focused on analytics capabilities highlighted in this book (Amazon, Netflix, Google, and Capital One). Many of these companies are extremely successful and based on many crowds the gold standard for being analytically driven.

It would be great to have this book updated to share what has happened based on the projections and what is different now. 

[عباد ديرانية · Rating 3 out of 5]

كتاب جيّد في مجاله رغم قدمه النسبي، قرأتُ معظمه في مادة جامعية عن "التحليل المهني" ("بزنس أناليتك")، المحتوى نظري جدًا والهدف منه هو أن يُعلِّم القارئ كيفية إدارة فرق تحليل البيانات، بدون الخوض في طريقة عمل هذه الفرق أو مهامها التقنية مطلقًا. برأيي أن أهم فصوله هي الفصلان الرابع والخامس (إدارة عمليات البيانات داخل الشركة وخارجها)، والفصل الثامن (وهو مقدّمة ممتازة في سلسلة تحليل البيانات المتكاملة). أشعر شخصيًا بصراع وأنا أقرأ هذا النوع من المحتوى، فهو مفيدٌ بلا ريب، لكني أشعر بأن قيمته لشخص لا يعرف أسس تحليل البيانات تكاد تكون منعدمة، وممتن شخصيًا لأني أكملتُ قبل قراءته موادًا جامعية في الأسس التقنية للبيانات والإحصاء والذكاء الاصطناعي، وهي خلفية أجدها حتمية للاستفادة من كتاب كهذا، فبدونه يصبح "المدير" ناقلاً للأفكار الواردة في الكتاب بدون أن يستطيع نقدها أو البناء عليها. رغم ذلك، أشعر -شخصيًا- بقصور على هذا الصعيد لأن خبرتي بالمجال تبقى محدودة، ولستُ مقتنعًا بأن هذا المحتوى هو الطريقة الصحيحة لتأهيل مديري الشركات لتبنّي تحليل البيانات في عملهم.

[Zack Plauche · Rating 2 out of 5]

I gave it 2 stars because
1. It reads horribly. There's so much fluff, LARGE and not useful repetition, and not really that useful advice. It doesn't actually tell you how to build these things even in it's "process to become an analytical competitor.
2. There were some useful parts in the beginning, but it's very general. The advice isn't practical in how to actually build the analytical capability.

There were some useful parts though (MOSTLY IN THE FIRST CHAPTER). I believe if someone wrote a summary of it (in plain english) that might be worth reading.

I'd say it is worth a read, but it is painful.

[Gabriel Le Gall · Rating 3 out of 5]

This book was rather interesting but not as insightful as I expected. I liked the frameworks presented in the first section "The Nature of Analytical Competition" but I agree with the previous comment saying that this book was not very impressive. The research conducted by the authors did not unveil much and I feel like they simply confirmed what we all assumed was true: Analytics is a competitive advantage, it leads to increased ROI, It's not only about IT it's about people... etc. At the end of the day, I don't think I learned much from this book.

[Katherine Morgan · Rating 4 out of 5]

Bought this book in 2010 when I changed careers. Since I was encouraged to learn about project management at time, that book also landed on my desk - but then I never found time to read it - for a bunch of reasons.
Ian challenged me to read a business book a month (Or something like that) this year. So I picked up this book - wish I had read it back in 2010. It really gives me insight into my current employer.
First chapter I noticed was mildly outdated but then I was fine with the rest of the book. It's excellent. Definitely I recommend it for those in the finance industry.

[Bill · Rating 2 out of 5]

Not as in-depth as I expected from "Harvard Business School Press" but it did give a basic overview of data analytics. The book covered the differing approaches and levels of analytics in business along with results of some case studies. While the book does give multiple examples of companies doing various styles of analytics, it lacks the details I was hoping for and didn't give much in the way of time it took to see results of the approach. It also doesn't offer any paths or guidance in how to achieve goals using the data. That's all left to the individual analyst and business.

[Adam Ribaudo · Rating 1 out of 5]

I read this book for a graduate level course but it feels especially outdated and irrelevant now. Perhaps to no fault of the authors. We can take for granted now that organizations will leverage data to gain a competitive advantage but this book spends chapters lauding that notion's virtues.

The book was written in 2007 and I thought the compliments it paid to data innovations in the financial sector were especially cringe worthy.

[Basil Latif · Rating 3 out of 5]

This book is a slog to get through. The author re-hashes the same 3 or 4 examples of organizations that are effectively "competing on analytics" and does a poor job of building any type of story or narrative of how these analytics journeys were undertaken –– rather this book is choppy, jumpy explanation of how analytics is used/ can be used in organizations. There are some interesting tidbits of information, but unfortunately, those are too few to make this book worth a reader's time.

[Laura · Rating 4 out of 5]

Very useful for understanding the history and placing an organization in its context in preparation for change. The practical section provides a helpful framework for thinking about developing analytical capacities in an organization. While some translation may be needed to inform my field, institutional research (higher education), I've found it useful.

[Zak Boston · Rating 2 out of 5]

This book is best suited to business experts who are completely unaccustomed to statistical business intelligence. This niche must be getting rarer every year since the book was published and the book suffers a less than incisive title choice with the word “new”. I do not recommend this book to non-MBAs not because they have expertise but because they lack it.

[Beige Alert · Rating 2 out of 5]

Opening book for an analytics class and I get why it was chosen as a start, but the book was way too high level (if you can even call it that) and self serving (it's a client generating tool for the author's consulting) and evangelical for my tastes.

[Heng · Rating 2 out of 5]

The book was filled with some useful frameworks and very high-level examples. There seemed to lack a overarching theory but instead of series of ideas stitched together, leaving the reader to have to fill in some holes in terms of how one truly competes with analytics.

[Jeremy Parkin · Rating 4 out of 5]

Solid book of its type. Inevitably the examples and predictions in books like this can start to feel dated very quickly, but the underlying ideas are still good, and there are some useful frameworks and directional questions that have given me food for thought.

[Utkarsh Kumar · Rating 3 out of 5]

This book gives examples of how data analytics has evolved from descriptive to real time change and prescriptive aspect with the analytics changing the enterprise overall strategy, process and working and making them more data savvy and competitive

[Comandante Ernesto Che Guevara · Rating 4 out of 5]

Academic

[Dele Tosh · Rating 3 out of 5]

An interesting overview on the need for analytics. This is just an overview.

Desperately needs an update in light of all the advancement in data science.

[Miles · Rating 4 out of 5]

Mr Davenport gives a very interesting read about the world of data and its implications in the business world. With real life examples that add context and understanding.

[Campbell Scott]

P