Analytics at Work: Smarter Decisions, Better Results [Hardcover] chapter summaries and review

Analytics at Work: Smarter Decisions, Better Results [Hardcover] chapter Summaries:

Product Description

Most companies have massive amounts of data at their disposal, yet fail to utilize it in any meaningful way. But a powerful new business tool – analytics – is enabling many firms to aggressively leverage their data in key business decisions and processes, with impressive results.

In their previous book, Competing on Analytics, Thomas Davenport and Jeanne Harris showed how pioneering firms were building their entire strategies around their analytical capabilities. Rather than “going with the gut” when pricing products, maintaining inventory, or hiring talent, managers in these firms use data, analysis, and systematic reasoning to make decisions that improve efficiency, risk-management, and profits.

Now, in Analytics at Work, Davenport, Harris, and coauthor Robert Morison reveal how any manager can effectively deploy analytics in day-to-day operations?one business decision at a time. They show how many types of analytical tools, from statistical analysis to qualitative measures like systematic behavior coding, can improve decisions about everything from what new product offering might interest customers to whether marketing dollars are being most effectively deployed.

Based on all-new research and illustrated with examples from companies including Humana, Best Buy, Progressive Insurance, and Hotels.com, this implementation-focused guide outlines the five-step DELTA model for deploying and succeeding with analytical initiatives. You’ll learn how to:

Use data more effectively and glean valuable analytical insights
· Manage and coordinate data, people, and technology at an enterprise level

· Understand and support what analytical leaders do

Evaluate and choose realistic targets for analytical activity
· Recruit, hire, and manage analysts

Combining the science of quantitative analysis with the art of sound reasoning, Analytics at Work provides a road map and tools for unleashing the potential buried in your company’s data.

About the Author

Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College and the author, coauthor, or editor of thirteen books.

Jeanne G. Harris is Executive Research Fellow and a senior executive at Accenture’s Institute for High Performance in Chicago.

Robert Morison has been leading business research in professional services firms for over twenty years and is a coauthor of Workforce Crisis (Harvard Business Press, 2006).

Buy ‘Analytics at Work: Smarter Decisions, Better Results [Hardcover]‘ online

Analytics at Work: Smarter Decisions, Better Results [Hardcover] Book Reviews:

I received a pre-release copy of Tom Davenport’ new book . The book is a follow-on to 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 . 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.
() 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.
I just received this book and read it quickly. I had read the Davenport/Harris “Competing on Analytics,” which has come to be the Bible of business-oriented analytics books. This one is even more accessible, and is broader in its orientation. It’s not just for companies that want to compete on their analytical capabilities, but for any organization that needs to make more analytical decisions. The DELTA framework is a clear way to describe the key factors necessary to become more analytical, and the chapters on culture and decision-making in the second half of the book are very helpful. The ideas in this book are unusually easy to apply and it includes handy frameworks and models. Given the rise in analytical activity in organizations, I predict that this book will be just as successful as the first one, if not more so because of its broader focus.