- Hardcover: 240 pages
- Publisher: Harvard Business Review Press; 1 edition (March 6, 2007)
- Language: English
- ISBN-10: 1422103323
- ISBN-13: 978-1422103326
- Product Dimensions: 1 x 6.5 x 9.5 inches
- Shipping Weight: 14.4 ounces (View shipping rates and policies)
- Average Customer Review: 3.7 out of 5 stars See all reviews (136 customer reviews)
- Amazon Best Sellers Rank: #150,791 in Books (See Top 100 in Books)
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Competing on Analytics: The New Science of Winning 1st Edition
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Harvard Business School Press, Davenport in particular, has produced some excellent books on competitive analytics and the like, with good case studies ” - ZD Net
From the Back Cover
In a world where traditional bases of competitive advantage have largely evaporated, how do you separate your company's performance from the pack? Use analytics to make better decisions and extract maximum value from your business process.
In Competing on Analytics: the New Science of Winning,Thomas H. Davenport and Jeanne G. Harris argue that the frontier of using data has shifted dramatically. Leading companies are doing more than just collecting and storing information in large quantities. They’re now building their competitive strategies around data-driven insights that are, in turn, generating impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling supported by data-savvy senior leaders and powerful information technology.
Why compete on analytics? At a time when companies in many industries offer similar products and use similar technology, distinctive business processes count among the last remaining points of differentiation. Many previous bases for competition—such as geographical advantage or protective regulation—have been eroded by globalization. Proprietary technologies are rapidly copied, and breakthrough innovations in products or services are increasingly difficult to achieve.
That leaves three things as the basis for competition: efficient and effective execution, smart decision making, and the ability to wring every last drop of value from business processes—all of which can be gained through sophisticated use of analytics.
Davenport and Harris show how exemplars—organizations as diverse as the Boston Red Sox, Netflix, Amazon.com, CEMEX, Capital One, Harrah’s Entertainment, Procter & Gamble, and Best Buy—are using new tools to trump rivals. Through analytics, these companies identify their most profitable customers, accelerate product innovation, optimize supply chains and pricing, and leverage the true drivers of financial performance.
A timely, much needed resource, Competing on Analytics promises to rewrite the rules of competition.
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Top customer reviews
I was a little disappointed that the coverage of HR/talent analytics was only covered in the realm of professional sports, but Davenport & Harris have published an article since this was written that focuses specifically on that.
Since the Oakland A's adopted this style several other teams (all of them by now?) engage in some form of analytics to remain competitive. In big business more primitive forms have been using spreadsheets and Access to understand differentiation and segmentation.
I picked up this book to gain a high level understanding which it successfully provides. As I read the examples of Yield Management by American Airlines to optimize pricing I started to understand how this could be applied to any industry.
Of course companies like Amazon and Ebay utilize analytics to send e-mails to a customer that trigger an interest or compliments a past purchase.
The chapter on competing on analytics with internal processes has a good list of Typical Analytical Applications for Internal Processes which will point many in the right direction. The book will not tell you how to set up your analytics, but will give some pointers on what tools to use and know about to compete on analytics.
In the same chapter the use of Financial Analytics is helpful as they provide some insight on what to include for a scorecard. Some items would be 1) Selecting profitable new markets to enter 2) Attracting and selecting the right customers 3) Driving pricing in accordance to risk and 4) Reducing the severity of claims (warranties or returns).
Similar to the Typical Analytical Applications for internal processes, they include a list for marketing as well along with supply chains.
Overall the book will be helpful for people who work with folks who do the analytics and to have more insight when working a process. Use this book with some others to become more educated about the growing use of analytics in every industry, especially as private and non-profit industries continue to be more global.
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.