Synopsis
Creating and leveraging knowledge assets is the critical competitive capability today. Speed and knowledge have emerged as the keys to success. And knowledge embedded in products and business processes now drives what can be created and delivered to the customer. Performance and knowledge must become a continuous cycle. Knowledge is captured from performance that will improve the next round of performance. Performance to knowledge, knowledge to performance, and so on, forming a knowledge engine that feeds on itself. Rather than collecting and cataloguing knowledge "just-in-case" someone needs it, Baird and Henderson explain that leaders must build a knowledge engine that focuses knowledge, acquires learning from experience and drives what is known quickly back into performance "just-in-time". Built on five years of research and application in leading corporations, "The Knowledge Engine" explains the principles of building the capability to create and leverage knowledge assets and gives concrete examples and practical tools to get you on your way.

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OUR BOOK is not about knowledge management, data warehouses, or e-commerce. Read the first page Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover

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Most Helpful Customer Reviews   1 of 1 people found the following review helpful: The guide of knowledge economy, 21 May 2001 By A Customer It was a Friday afternoon when this book 'came' to me. I took a brief look at the whole seven chapters and it was evident, that I would spend most of time during the weekend reading this excellent book. I've read many titles from the category of knowledge management, but this book explains all the important principles composed in the 'fuel' of knowledge engine. The principles are not listed tediously, but proved by the examples from the 'real' business. This title is classified by me far from the 'academic' title. I agree with the authors that it is not enough time to learn and acquire the necessary knowledge to do the business which is today in most cases the 'quick and dirty' type (focusing on single loop learning which is seeking efficiency -doing things right, instead of effectiveness - doing the right things).  Comment | Permalink | Was this review helpful to you? (Report this) › See all customer reviews...		Search Customer Reviews Only search this product's reviews

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