Literature DB >> 16447373

Competing on analytics.

Thomas H Davenport1.   

Abstract

We all know the power of the killer app. It's not just a support tool; it's a strategic weapon. Companies questing for killer apps generally focus all their firepower on the one area that promises to create the greatest competitive advantage. But a new breed of organization has upped the stakes: Amazon, Harrah's, Capital One, and the Boston Red Sox have all dominated their fields by deploying industrial-strength analytics across a wide variety of activities. At a time when firms in many industries offer similar products and use comparable technologies, business processes are among the few remaining points of differentiation--and analytics competitors wring every last drop of value from those processes. Employees hired for their expertise with numbers or trained to recognize their importance are armed with the best evidence and the best quantitative tools. As a result, they make the best decisions. In companies that compete on analytics, senior executives make it clear--from the top down--that analytics is central to strategy. Such organizations launch multiple initiatives involving complex data and statistical analysis, and quantitative activity is managed atthe enterprise (not departmental) level. In this article, professor Thomas H. Davenport lays out the characteristics and practices of these statistical masters and describes some of the very substantial changes other companies must undergo in order to compete on quantitative turf. As one would expect, the transformation requires a significant investment in technology, the accumulation of massive stores of data, and the formulation of company-wide strategies for managing the data. But, at least as important, it also requires executives' vocal, unswerving commitment and willingness to change the way employees think, work, and are treated.

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Mesh:

Year:  2006        PMID: 16447373

Source DB:  PubMed          Journal:  Harv Bus Rev        ISSN: 0017-8012


  5 in total

1.  The Impact of Big Data Management Capabilities on the Performance of Manufacturing Firms in Asian Economy During COVID-19: The Mediating Role of Organizational Agility and Moderating Role of Information Technology Capability.

Authors:  Junling Zhang; Hualong Li
Journal:  Front Psychol       Date:  2022-07-06

2.  Strategies for data analytics projects in business performance forecasting: a field study.

Authors:  Maël Schnegg; Klaus Möller
Journal:  J Manag Control       Date:  2022-04-04

3.  Perceived evidence use: Measurement and construct validation of managerial evidence use as perceived by subordinates.

Authors:  Denise M Jepsen; Denise M Rousseau
Journal:  PLoS One       Date:  2022-04-26       Impact factor: 3.752

Review 4.  Finding Pluto: An Analytics-Based Approach to Safety Data Ecosystems.

Authors:  Thomas T Barker
Journal:  Saf Health Work       Date:  2020-10-01

5.  ASAS-NANP symposium: mathematical modeling in animal nutrition: the progression of data analytics and artificial intelligence in support of sustainable development in animal science.

Authors:  Luis O Tedeschi
Journal:  J Anim Sci       Date:  2022-06-01       Impact factor: 3.338

  5 in total

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