5.0 out of 5 stars
Practicing analytics
Reviewed in the United States 🇺🇸 on 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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