 | Summaries and Customer Reviews are supplied by Amazon.com | You have more information at hand about your business environment than ever before. But are you using it to "out-think" your rivals? If not, you may be missing out on a potent competitive tool. In "Competing on Analytics: The New Science of Winning" , Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon: Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples - from organizations as diverse as Amazon, Barclay's, Capital One, Harrah's, Procter & Gamble, Wachovia, and the Boston Red Sox - illuminate how to leverage the power of analytics. |
Average Customer Rating:   A general manager's guide to making analytical decision-making a core competitive competence At one level, the premise of this book is clear to most executives: business decisions should be based on rigorous analysis of as much relevant data as possible. When I joined LEK Consulting in 1985 we were pioneers of using spreadsheets for financial modeling, rather than the ubiquitous HP12c calculator: how much more quickly we could model different scenarios and how much more accurately (because spreadsheets could be more easily checked). In many ways it has been a relentless progression along this path ever since. What Davenport and Harris show, however, is that analytics themselves have become a core area of competitive competence: "At a time when companies in many industries offer similar products and use comparable technology ... many of the previous bases for competition are no longer available. Unique geographic advantage doesn't matter in global competition, and protective regulation is largely gone. Proprietary technologies are rapidly copied, and breakthrough innovation in products or services seems increasingly difficult to achieve. What's left as a basis for competition is to execute your business with maximum efficiency and effectiveness, and to make the smartest business decisions possible. And analytical competitors wring every last drop of value from business processes and key decisions."
I would argue that many of the other bases of competition are not "gone" but can only be sustained for short periods of time in today's highly competitive world. What "Competing on Analytics - The New Science of Winning" shows, however, is that to build a true core competence in analytical decision-making takes a huge amount of investment in data collection, cleaning, analysis (techniques and technologies) and interpretation. The interpretation requires, in most cases, highly skilled people who understand both analytics and how to apply its insights. This is a competence which can take years to build and which therefore is not easy for a competitor to copy.
The results cannot be denied: the book abounds with examples of companies which have decreased costs, grown sales and increased customer satisfaction by detailed analysis of their data, and Part II provides a useful guide to "Building an Analytical Capability". "Competing on Analytics" is well written, easy to read and a value guide for executives wanting to maximize the effectiveness of their organization and build analytical decision-making as a core competence. Not-so-new consulting speak In spite of its alluring title, this book is mediocre at best. The authors rehash a bunch of consulting speak that has been around the data warehousing and business intelligence space for a decade or more. After finding Davenport's Thinking for a Living: How to Get Better Performances And Results from Knowledge Workers to be pretty thought provoking, I was disappointed with this work. Unless you are brand new to data warehousing and business intelligence, don't waste your time.
The authors promote analytics as the sound way to make decisions that ultimately make a company more competitive. There is some obvious truth in that concept, I guess. However, they fail to acknowledge that first movers (those companies that usually have competitive advantage) often have to make decisions without the benefit of clean, historical data. In fact, the authors go so far as to say that clean data is a prerequisite to good analysis which is in turn a prerequisite to good decision making which, only then, leads to competitiveness.
As a two-decade veteran of the business intelligence space, I do agree with much of what the authors have suggested. The formula they propose works well for established companies with large, historical data stores to draw upon. The trouble is, they imply that analysis-driven decision making is the secret to competitiveness. Making good decisions, especially when you don't have all (or very much) of the data -- a very typical scenario in first-mover environments -- is the real secret to competitiveness. Competing, perhaps... but not competitive edge This book is well written, structured and thought out. All combined, this book is easy to follow. There are some good examples of companies leveraging analytics to compete in the market. Furthermore, the prescient reader will find some interesting areas for analytic investigation to pursue in his own organization.
On the negative side, the notions of data warehouses and data marts are only superficially explored. No practical architectural analysis is provided. After reading this book, Im not convinced that data warehouses or data marts are anything more than glorified databases.
It is true that customer/supplier/market data is becoming widely available, the challenge being in making sense of this data. However, I dont believe a company can find its competitive edge solely by crunching data and making intelligent forecasts. The better (read accurate) the forecast, the more bridle the model. How can it ever respond to non-linear events? What will happen to companies which invested heavily in analytics - like the authors suggest - when a paradigm shift inevitably occurs in the market? What good will all those forecast models be then? But thats a decision the reader should make for himself.
Overall, the book relatively short and worth the read.
Lists Applications, but Provides Little Else Davenport argues that leading companies are now building their competitive strategies around sophisticated analyses and predictive modeling. Many previous bases for competition, such as geographic advantage or protective regulation, have been eroded by globalization.
Some industries are more amenable to analysis than others. Examples include those with lots of transaction data, such as in financial services, travel and transportation, and Internet sales. More specifically - hotel and airline yield management, health care (where to focus improvement efforts), insurance pricing, selecting sports talent, general hiring (using FICO scores), tax compliance focus, etc.
The frustrating and highly limiting part about "Competing on Analytics" is that it doesn't reveal the mechanics of these improvement efforts. Solid Book on Analytics in business Great introduction into the application of Analytics in business. Primarily focused on usage and benefits, with a small component on underlying technologies used to implement an analytics as a primer.
Highly recomend for anyone looking to better understand analytics as a whole, and how they can impact your business. |  |
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