Analytics at Work: Smarter Decisions, Better Results
By Thomas H. Davenport, Jeanne G. Harris, and Robert Morison
Harvard Business Press, 2010[powerpress: http://gsbm-med.pepperdine.edu/gbr/audio/winter2011/Mallette-book.mp3]
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. 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.
