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on June 15, 2010
This book contains some occasional flashes of brilliance, like Figure 1-1 which succinctly summarizes the key questions addressed by analytics. The rest of the book is padded with pointless, meandering and buzzwords-laden prose. Case in point:

"Stage 5 organizations develop a robust information management environment that provides an enterprise wide set of systems, applications, and governance processes. They begin by eliminating legacy systems and old spaghetti code and press forward to eliminate silos of information like data marts and spreadsheet marts. They hunt for pockets of standalone analytic applications and either migrate them to centralized analytic applications or shut them down."

The entire book actually reads like that.

As an applied statistician and an avid reader of business books, I cannot - for the life of me - imagine why people will want to write a book like this. What is the target reader of such a book? Technical professionals like myself will find the book absolutely useless to guide analytical projects. Business professionals will be confused and put off by all the buzzwords.
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on January 22, 2010
I received a pre-release copy of Tom Davenport' new book Analytics at Work: Smarter Decisions, Better Results. The book is a follow-on to Competing on Analytics: The New Science of Winning and is a shorter, pithier book than its predecessor. Once again Tom collaborates with Jeanne Harris and this time Robert Morison of the Concours group. Where the previous book focused on so-called analytic competitors, this is about "analytics for the rest of us". It is a very readable book with some good practical advice that does not require the remaking of your company in a new image. It is also a quick read, it is only 180 pages or so, which should help get more people to read it.

And I hope people do read it. As Tom says "The unexamined decision isn't worth making" and too many companies and organizations are making unexamined decisions, failing to apply data they have about what works and what does not, making the same mistakes over and making dumb decisions. Like Tom I think it is time for this to stop and this book will tell you how.

The book's focus is broad, covering how analytics can address key questions of information and insight in each of the past, present, future - reporting, alerts and forecasting give information in the past, present and future while modeling, recommendations and predictions/optimization do the same for insight. For me the most useful part of the book is part one - a set of chapters describing The Analytic DELTA - Data, Enterprise, Leadership, Targets and Analysts - what Tom regards as the 5 critical elements of successful analytic adoption:
* D - accessible, high quality data - I particularly like the focus on uniqueness as a criteria and on using the business need (decision) to drive data quality and integration
* E - enterprise orientation not fractured analytic projects
* L - analytical leadership
* T - strategic targets - a crucial element, that of focusing on using analytics to develop distinctive capabilities. This chapter has a great list of processes that lend themselves to analytics and a very helpful "ladder of analytic applications" to develop from simple to more complex analytic solutions
* A - analysts - a nice chapter with good thoughts on how to manage analysts as a strategic resource.

Part two addresses how to stay analytical through embedding analytics in business processes, building an analytic culture, reviewing your business comprehensively and embarking on an analytical journey towards "more analytical decisions and better results." I really liked the focus on embedding analytics in business processes - this is a topic close to my heart and one we discussed in Smart Enough Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions. The authors do a nice job of explaining why organizations need to adopt a test and learn mindset, to be always unsatisfied and mindful of change and to focus on an "industrial" analytic process.

The authors end by pointing out that becoming analytic is not a one-time activity but must be ongoing - it is a journey which organizations must begin, where they must build momentum and where they must go from thinking of analytics to thinking about decisions and decision making, from analytic management to decision management.
It's a great book and you should buy it.
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VINE VOICEon January 27, 2010
Analytics is a hot topic and executives looking to get value from business intelligence. This book discusses how they do that. I recommend this book as perhaps THE book for people looking to establish and sustain an ability to use information in decision-making and process execution.

There is a sweet spot for business books between the illustration of a business idea and a discussion of its practical implementation. Business books that are too high level offer great ideas that appear realistic only to angels. Too low of a level and it's a technical manual that makes the idea seem mundane. I mention this because Analytics at Work rests firmly in the sweet spot between these extremes.

Davenport, Harris and Morison have taken ideas originally expressed in Competing on Analytics and taken them to the next level - reality. If competing on analytics describes the characteristics of an `analytic competitor' and their principles, then this book moves from principle to practice discussing issues from data management, through to changes in corporate structure and culture. The book is comprehensive without being a compendium. It is clearly written to provide a guide that helps you apply analytics to your situation without being a set of instructions that are applicable to few people.

Strengths:

The book has frequent and recognizable examples of executives and applications of analytics. These examples illustrate the author's points without appearing contrived. The examples and case studies are a real strength particularly as they come from companies with different levels of analytic intensity. This gives the reader the ability to see how analytics comes in many sizes and fits different situations.

A practical discussion of the issues related to analytics rather than a relentless boosting of the idea and principles. The authors recognize that business intelligence has been around for a while, that people will adopt analytics at different levels of intensity and that makes the book real to executives and practitioners.

The book offers a comprehensive discussion of the strategies, organization structure and execution implications of analytics in the enterprise. For a 214-page book, Analytics at Work covers a lot of ground without seeming rushed or superficial.

Graphical, the book makes effective use of frameworks and diagrams that bring the concepts into tighter focus and reality. Executives can use these diagrams to understand and perhaps more importantly to share with others to explain how analytics apply to their business.

Challenges:

While the book discusses analytics at all levels, it tends to concentrate analytics activities into a specific group of subject matter experts. While I agree that analytics requires specific skills, setting these `quants' up as a special group may limit the spread of analytics across the enterprise. This is a minor point that does not reduce the value of the book.

Overall Analytics at Work is a rare book that covers both the concept and the implementation of a business idea. I recommend the book as it represents a well-balanced, action oriented approach that executives should read to raise the value of information in their enterprise.
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on June 23, 2011
This book is an easy read especially if you are used to more informative books on analytical rigor and methodology. The good aspect about the concept of this book is that it does get people thinking about analysis and using fact based decision making models. What this book lacks in is connecting the dots between assumptions and actual skill sets. It does go into some techniques and approaches but this in itself is not detailed enough. Compared to other books used in graduate school methodology courses, this book falls short where it should be leading the way forward. Page 10-11 in the section "When Are Analytics Not Practical" states many scenarios where going on an ad hoc decision making paradigm is preferable. Here is the beginning of where this book falls apart. All of these scenarios are perfect opportunities to employ analysis. The lack of the authors understanding of analysis and how it can be applied to these scenarios is concerning. The best use of this book would be as a introduction to analysis provided to an audiance that is not familiar with logical fact based decison making paradigms.

The most important aspect to this book is that it gets people thinking about how to use fact based decision paradigms. And that is essential in this economic environment.

Some titles I would refer that would fill in the gaps that this book has created are:
The Psychology of Intelligence Analysis
Intelligence Analysis: A Target-Centric Approach
Structured Analytic Techniques for Intelligence Analysis

I understand that most people who read business books probably are wondering what tittles referring to intelligence analysis would have to offer the business world. The answer is simple, the principles outlined in those books are very similar to the ones outlined in Analytics at Work. The difference is that those three titles offer a more holistic approach to analyzing any problem that an organization may face.
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VINE VOICEon January 24, 2010
Well composed follow-up by the writers of "Competing on Analytics: The New Science of Winning" and Robert Morison, coauthor of "Workforce Crisis: How to Beat the Coming Shortage of Skills and Talent". While the previous effort by Davenport and Harris focused on the use of analytics for competitive strategy, this book focuses on deploying analytics in day-to-day operations. Use of the "five stages of analytical competition", which describes the analytics phases through which firms pass as their level of maturity increases from "analytically impaired" or "flying blind" to "analytical competitors" or "enterprise-wide, big results, sustainable advantage", continues here, but is now superimposed by what the authors deem the "DELTA" success factors - accessible, high-quality "Data", "Enterprise" orientation, analytical "Leadership", strategic "Targets", and "Analysts" - that are associated with the transition of firms from one level of competitive strategy to the next. The authors further this presentation of the analytical DELTA by discussing the embedding of analytics in business processes, the building of an analytical culture, the continual reviewing of analytical approaches, and meeting challenges along the way.

According to research conducted by the authors, 40% of major business decisions are not based on facts, but on the manager's gut. As the authors point out, "sometimes intuitive and experience-based decisions work out well, but often they either go astray or end in disaster: executives pursue mergers and acquisitions to palliate their egos, neglecting the sober considerations that create real value; banks make credit and risk decisions based on unexamined assumptions about always-rising asset values; governments rely on sparse intelligence before deciding whether to wage war. Such are the most extreme cases of ill-informed decision making. In other cases, nonanalytical decisions don't lead to tragedy, but they do leave money on the table: businesses price products and services based on their hunches about what the market will bear, not on actual data detailing what consumers have been willing to pay under similar circumstances in the past; managers hire people based on intuition, not on an analysis of the skills and personality traits that predict an employee's high performance; supply chain managers maintain a comfortable level of inventory, rather than a data-determined, optimal level; baseball scouts zoom in on players who 'look the part', not on those with the skills that - according to analytics - win games". And "while analytics are not perfect, we prefer them to the shoddy alternatives of bias, prejudice, self-justification, and unaided intuition. Humans often make long lists of excuses not to be analytical, but there's plenty of research showing that data, facts, and analysis are powerful aids to decision making, and that the decisions made on them are better than those made through intuition or gut instinct. Therefore, use analytics. If you can measure and analyze something, do it - but don't forget to incorporate your experience, knowledge, and qualitative insights around the world".

The point of this book is to present a set of tools to make one's firm more analytical, and demonstrate that becoming more analytical should be an essential concern for the entire organization. In essence, the authors present analytics to readers who do not necessarily want to transform their firms into analytical competitors, but to move them to greater analytical maturity. This reviewer particularly enjoyed the second part of this book, which discusses various topics centered around the concern of staying analytical. For example, the authors discuss the difference between "craft" and "industrial" approaches to employing business analytics, where the former is a one-time effort that is inherently limited in effect, and the latter takes more time and effort up front but leads to instantaneous automated decision making. Accompanying this discussion is an explanation on how embedded predictive analytics fits into claims processing in the insurance industry, and a well presented diagram by SPSS that shows how manual and automated or partially automated decision making can be joined together in one overall process, reminiscent of what James Taylor and Neil Raden present at length in "Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions". The authors later discuss what their research has concluded on how to overcome obstacles, or "sticking points" specific to embedded analytics implementations.

The chapter entitled "Build an Analytical Culture" combined with the earlier chapter "Analysts" from the first part of the book are especially well written, incorporating discussions on how to start and grow an analytical culture, as well as how to attract and retain analytical talent. In the closing chapters, the authors present what they do and do not promise, and as a consultant this reviewer especially appreciated this aspect of this text; regarding the latter, "analytical decisions aren't the only ones that will lead to success", "your analytical decisions won't always be perfect", "you'll need to develop new analytically based insights to stay ahead of the competition", "sometimes the world will change, and invalidate the models that guide your decisions", and "analytics are not all you need to make good decisions"; regarding the former, "you'll make better strategic decisions", "you'll make better tactical and operational decisions", "you'll have a better ability to solve problems", "you'll have better business processes", "you'll be able to make faster decisions and get more consistent results", "you'll be able to anticipate shifting trends and market conditions", and "you'll get better business results". In the view of this reviewer, this book is not only appropriate for business readers new to analytics, but for consultants and other practicing individuals already comfortable with analytics who want to continue to demonstrate the value of analytics to clients. Well recommended.
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on September 3, 2011
Analytics at Work is billed as a how to guide for managers to "effectively deploy analytics in their day-to-day" operations (from the inside cover). Though I enjoyed the book, I don't believe that a reasonable person could say that it lives up to the promise. Instead, Davenport and his co-authors provide a very general framework that lacks the advertised day-to-day details required for deployment.

I found the book to be interesting and quite useful from a "oh, I hadn't thought of that..." perspective. However, I'm not sure that there is much original material here beyond the general framework -- most of which was presented in an earlier work by the same authors. Though I wouldn't recommend this book for serious analytic how-to, it would be a good read for someone seeking a general overview of the topic in a reasonably non-technical format.

For me, the measure of a book's contribution to my understanding of a topic is the number of marginal notes I make as I read. In this particular volume, I didn't make many marginal notes. I'm still very much of fan of Thomas Davenport; the quality of his thought on the topic of business analytics is top notch. Analytics at Work is still worth a quick read, especially if this is your first exposure to Davenport's framework for business analytics.
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Those who have read Competing on Analytics may incorrectly assume that there is not much new to learn in this sequel to it. Thomas Davenport and Jeanne Harris with Robert Morison do indeed review and reaffirm the core principles of analytics but they offer more, much more in this recently published book. For example, they continue with the five-stage model for analytical maturity ("God has decreed that all maturity models have five stages") but supplement it with an abundance of "pragmatic suggestions" with regard to the design and implementation process; they also offer a five-letter framework (DELTA) that has been adopted by numerous companies in recent years. "The first part [of Analytics at Work] is also more oriented to current practice. Part two opens things up a bit to address some of the capabilities that analytically oriented organizations will need in the future. Some firms are actually address those capabilities today."

DELTA is an acronym that helps to explain how to put analytics to work:

D for accessible, high-quality data
E for an enterprise orientation
L for analytical leadership
T for strategic targets
A for analysis

With regard to the five-stage model or process:

Stage 1: Analytically Impaired ("flying blind" because of the lack of one or more of the prerequisites for effective analytical work such as sufficient and reliable))

Stage 2: Localized Analytics (Although there are pockets of activity, they isolated, fragmented, disconnected, inconsistent, etc.)

Stage 3: Analytical Aspirations (Several managers recognize the need, begin to explore options, may attempt to collaborate, but progress may be slow because some critical DELTA factor has proven too difficult to implement)

Stage 4: Analytical Companies (Managers develop an enterprisewide perspective; also, they and their associates are eager to innovate and differentiate but the strategic focus is not as yet grounded in analytics)

Stage 5: Analytical Competitors (The company routinely uses analytics as a distinctive business capability, one that serves as the primary driver of performance and value throughout the enterprise)

Davenport, Harris, and Morison explain with meticulous care how to complete the process to reach and then remain at Stage 5. I especially appreciate the fact that they anchor their observations and recommendations within a real-world context, within a frame-of-reference, that is frequently provided by a mini-case study of an exemplary organization such as Olive Garden, an Italian restaurant chain owned by Daren Restaurants, that uses data on store operations to forecast almost every aspect of its restaurant operations. "Best Buy was able to determine through analysis of its Reward-Zone loyalty program member data that its best customers represented only 7 percent of total customers, but were responsible for 43 percent of its sales."

I also appreciate the brilliant use of various Tables that organize, showcase, and emphasis key points. For example, Table 2-1 (Page 39) that introduces brief but remarkably specific explanations of how to move from Stage 1 to Stage 2, from Stage 2 to Stage 3, etc. Readers would be well-advised to juxtapose this material with material provided in the next chapter when the co-authors explain the kind of leadership that is needed for successful transitions from one stage to the next until the given organization has reached Stage 5. After identifying and discussing 12 behaviors that analytical leaders tend to demonstrate (including but not limited to those at the C-level), they focus on four exemplary change agents: Shannon Antorcha (Carnival Cruise Lines), Greg Poole (Talbots), Tom Anderson (independent management consultant), and finally, Jim and Chris McCann (1-800-Flowers.com). These mini-case studies are followed by an especially valuable explanation of how specifically must function throughout the five-stage process.

In the next chapter, the focus is on analytical applications and once again a reader-friendly illustration (i.e. Table 5-1) identifies 12 industries and a few key applications for each. For example, manufacturing: supply chain, organization, demand forecasting, inventory replenishment, warranty analysis, product customization, and new product development. The other 11 include financial services, health care, and communications. The last category, "Every business," correctly suggests that the ultimate objective is effective and efficient performance management. To me, the most valuable Table is provided in the Appendix, A-1 ("The DELTA transitions," Pages 186-187). It focuses on the key points for each transition in terms of data, enterprise, leadership, targets, and analysts.

Congratulations to Thomas Davenport, Jeanne Harris, and Robert Morison on a brilliant achievement. Bravo!
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on July 13, 2010
Much as the authors' observations and insights on deploying analytics in organizations are useful, their DELTA framework and prescriptions for attaining maturity in the use of analytics can also be applied to other programs like Six Sigma or TQM or whatever. For example, their pronouncement that management/leadership needs to promote and champion the use of analytics for insight generation and decision-making - where have we heard that before? Likewise the call for enterprise-wide adoption and inculcation of the use of analytics. In that regard, the book seems derivative and does not offer much that is new by way of principles; some sections even verge on the trite e.g. the chapter devoted to Analysts, characterizing them almost as a special class of employees, discussing what they need and what it'll take to motivate and retain them, as if other run-of-the-mill employees do not have similar motivations and needs. One would (and should) question the value of such artificial distinctions.
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on August 16, 2011
This book is about improving performance in key business domains using data and analysis. Analytics at Work by Davenport, Harris, and Morison is built in-part on the first two authors' previous book (Competing on Analytics, Harvard Business Press, 2007) but this one is more of a how-to book; oriented to fact-based decision making. The authors show that analytics can start as simply as identifying key activities, creating simple metrics, reporting on them on a regular basis, and acting on the patterns that emerge. (p. 4)
The authors provide a five-element model with five stages of transitions (or levels of analytical focus) in the first half of the book. The five elements have the useful mnemonic of DELTA. D-Data: you can't be analytical without data. E-Enterprise: you need to be integrated across organizational silos. L-Leadership: they determine how analytical an organization will be. T-Target: apply the analytical efforts where they will do the most good. A-Analysts: finding, developing, managing, and deploying analysts. Each of these elements are taken through the five stages of transition. Stage One is analytically impaired; Two is localize analytics; Three is analytical aspirations; Four is analytical companies; and Stage Five is analytical competitors. Table A1 in the appendix is a 5×5 matrix that nicely summarizes the five elements in their five stages.
To the authors' credit, they included a section entitled When Are Analytics Not Practical? (p. 10) and suggest that there are times when judgment should overtake analysis. The second half of the book is devoted to organizations staying analytical, especially in Stages Three to Five. This focuses on three hallmarks of analytical organizations: Analytics are embedded, they continually reinforce a culture of analytical decisions, and continually review its assumptions and analytical models.
This little book (6 by 9.5 inches, 214 pages) is a great introduction to the subject, and leads the reader to want to learn more. It is easy to read, is a good introduction to the subject, and provides a formula for implementing analytics. The book has 11 chapters, a very nice index, plenty of examples from the authors' experiences, and is sprinkled with several tables and figures. As a manager, I was especially enamored with the chapter on how to manage analysts! I recommend this book to anyone who is interested in learning about the subject, a process for thinking about analytics, and taking their company or organization to the next level.
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on March 30, 2013
This book provided for me critical, foundational background knowledge as I researched for and wrote my book (on the topic of predictive analytics). This book is an inspiration, and one of a small number of must-reads I heartily urge all creators and thinkers to pack for your next flight!

Eric Siegel, Ph.D.
Founder, Predictive Analytics World
[...]
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