Competing on Analytics: The New Science of Winning

by Thomas H. Davenport and Jeanne G. Harris

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Davenport and Harris argue that in industries where products and processes have converged, analytics is becoming the primary basis of competition, and they profile companies like Capital One, Harrah's, and Amazon that embedded data-driven decision making into their strategy. They outline five stages of analytical maturity and the organisational capabilities required to move up them.

Published:: 2007
Pages:: 240

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In the Conversation

In this collection, Competing on Analytics: The New Science of Winning references 3 other books and is cited by 1 other book.

It draws on The Innovator's Dilemma, Built to Last and Crossing the Chasm.

It’s picked up by Prediction Machines: The Simple Economics of Artificial Intelligence.

Scroll down to read the exact passages where other authors reference this book and what they say about it.

What This Book Draws On

The books Harris references and why each one mattered to the argument.

Davenport and Harris draw on Christensen's Innovator's Dilemma to explain how analytics-driven entrants disrupt incumbents who lack data infrastructure and decision processes

References

The Innovator's Dilemma

by Clayton Christensen

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Cite Collins and Porras's Built to Last when discussing how analytical leaders institutionalize fact-based management as a core ideology rather than a tool

References

Built to Last

by Jim Collins

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Reference Moore's Crossing the Chasm when analyzing the adoption curve of analytics capabilities across industries and the transition from early adopters to mainstream use

References

Crossing the Chasm

by Geoffrey Moore

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What Other Authors Say About It

The exact passages where other authors bring up “Competing on Analytics: The New Science of Winning” and what they take from it.

Extend Davenport and Harris's Competing on Analytics thesis to the AI era, arguing that the competitive advantage has shifted from having better analytics to having cheaper and more pervasive prediction embedded in every business process

Cited in

Prediction Machines: The Simple Economics of Artificial Intelligence

by Ajay Agrawal, Joshua Gans, and Avi Goldfarb

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Intellectual Lineage

How ideas flow through the citation network. Ancestors are books this title builds on; descendants are books that build on it.

Builds on (2 layers deep)

Directly cites

The Innovator's Dilemma

Built to Last

Crossing the Chasm

2 steps back

The Effective Executive

Influenced

Directly cited by

Prediction Machines: The Sim...

Unexpected Connections

Books from completely different categories that share citation overlap with this one. These are the reads you would not find by browsing a single shelf.