||Information and its dicontents: an introduction -- The illusion of control: our information past -- The best of all worlds: information ecology -- Information strategy -- Information politics -- Information behavior and culture -- Information staff -- Information management processes -- Information architecture -- Connecting to the company: information and the organization -- Information and the outside world -- Implementing information ecology. In Information Ecology, Thomas Davenport proposes a revolutionary new way to look at information management, one that takes into account the total information environment within an organization. Arguing that the information that comes from computer systems may be considerably less valuable to managers than information that flows in from a variety of other sources, the author describes an approach that encompasses the company's entire information environment, the management of which he calls information ecology. Citing examples drawn from his own extensive research and consulting, including such major firms as AT & T, American Express, Ford, General Electric, Hallmark, Hoffman La Roche, IBM, Polaroid, Pacific Bell, and Toshiba, Davenport illuminates the critical components of information ecology, and at every step along the way, he provides a quick assessment survey for managers to see how their organization measures up. He discusses the importance of developing an overall strategy for information use; explores the infighting, jealousy over resources, and political battles that can frustrate information sharing; underscores the importance of looking at how people really use information (how they search for it, modify it, share it, hoard it, and even ignore it) and the kinds of information they want; describes the ideal information staff, who not only store and retrieve information, but also prune, provide context, enhance style, and choose the right presentation medium; examines how information management should be done on a day to day basis; and presents several alternatives to the machine engineering approach to structuring and modeling information.