Analytics at Work: Smarter Decisions, Better Results

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.

Provides great insights from a students perspective. There is a vast amount of business acumen shared with the reasoning for a move to data analytics. The DELTA model is easy to understand, and is sound reasoning for leadership in any organization.

In my review of the authors previous book,  Competing on Analytics: The New Science of Winning , I was critical of their lack of acknowledgement of intuition and experience as critical aspects of decision-making. The authors have come a long way with this new book and have made a more balanced argument. Overall, this second book is better than the first because it is much more tangible for business leaders and it is much more inwardly focused (on processes and staffing, for example). There is some consulting speak, but not as much as in their first book.Chapter seven, Embed Analytics in Business Processes, is particularly good. In it, the authors warn against adoption of analytics on a one-time, project basis (they call this craft analytics). Instead, they advocate analytics as an integral part of the corporate persona. They give many great tips on how to overcome the common objections and roadblocks to adopting an analytics culture.I have two minor issues with the book. One issue is the authors' implication that reporting and dashboarding are simplistic forms of BI. Enterprise and departmental reporting remain the predominant need in BI since most companies still don't have it. Another minor issue revolves around a statement the authors make: "Most information work is done through personal productivity tools like Microsoft Office." I absolutely agree with their observation. Even with the advent of very complex and expensive BI software packages, humble Excel remains the workhorse of end-user reporting and analysis. Unfortunately the authors never really address this reality. Even with these two minor issues, this is a really solid book. Highly recommended.

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.

Another in a serious of Tom Davenport data mantras. It is pretty clear that you can buy your way into the book by having Tom D and/or Accenture work on a big project, but I guess that's the way this stuff goes. As for the content, this is a better book then Competing on Analytics, but about 50% too long. Seriously, why don't they just publish this stuff as a pamphlet or a couple long articles in HBR? Couple good models and frameworks for organizing people and thinking around data, but no real discussion about analysis itself. For those seeking to grow analytics at your company, this can be a good hat tip to, "This is how the best in class do . . . . ", but this doesn't make the work any easier.

This book illustrates how some businesses are improving results by using data analysis to inform decisions. This is a clear trend over the past decade and a wide range of examples are given.What makes this useful is that it is written for business users who want to learn more about this area and improve the analytical capabilities within their organisations. So it includes frameworks which cover the stages of analytical evolution in a business, and the key ingredients for success, along with some thoughts on making the journey to more data-driven decision making.I like the fact that it is concise and not a great thick tome, but still gives good coverage to a very topical subject. Although I've said it's really for non-analysts, I think analysts will also find it an encouraging and thought provoking book.It's probably the best book for practically introducing the subject and the authors are all credible and advising major companies in this space.

A very good pragmatic guide to introducing the use of business analytics into the wrokplace. Focusing on the business rather than the technology this book provides some valuable frameworks for evaluating the current analytics maturity of an organisation along with practical steps and examples of how to implement.

If you are like me and data has become an increasing part of your daily work, this book should help you provide yourself with a framework to adopt analytics successfully. This book provides guidance from the business side of analytics, rather than the IT side, and I found that made it accessible and understandable as a manager.

Easy to read, well structured and supported with examples, this book sets the path to evolving the analytical capabilities of any company in a sustainable, profit-focused way.

Informative, easy-to-read and understand.