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Reinventing 'Knowledge Management' : Part One

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The field of Knowledge Management (KM) has existed for about a decade, and after an initial flurry of enthusiasm (at one point six of the top ten business best-sellers were about KM) it has fallen into disarray. Part of the problem is that the field has been dominated by three largely disconnected groups:

Academics & business gurus, who write about theory that is too general and abstract to have much practical application,

Knowledge managers and project managers who cobble together pragmatic custom applications, often in an undisciplined and unsustainable way, applications that are often abandoned as needs, roles and technologies change, and

IT managers who, with the best of intentions, buy and install commercial 'KM tools' that never get much front-line take-up

Ten years later many organizations have little to show for large investments in promising KM tools, projects and infrastructure. What went wrong, and is it too late to save KM from the scrap heap of failed management fads?

I believe one cause of the failure of KM was the attempt to build generalized tools that were expected to have application in almost all industries and business processes. Such tools work well enough in the old financial information (FIS), sales and marketing (SMIS) and human resources (HRIS) systems. In these 'classical' IT systems, both the content (financial, customer and employee data) and the application (financial statements, customer reports and employee records) are relatively standard across a wide variety of industries.

By contrast, knowledge content (like leading practices, industry analyses and methodologies) is particular to each industry and to each department and process within a company. Here are four examples to illustrate this:

Example of Content

Example of Process

R&D process in a pharma company

patent for a new drug

drug development

Sales process in a consultancy

customer analysis

selling an assignment

Production process in a newspaper

article or editorial

intelligence gathering, editing

Distribution process in a newspaper

newspaper edition


A knowledge tool designed for one of the above processes is unlikely to be optimal for another process, any more than a machine designed to make lasers would be optimal for blending fruit. And there are three additional dimensions to the problem that complicate matters further:

There are four steps in the knowledge/learning cycle:

Capturing: e.g. putting it in a memo, filing cabinet or Windows folder

Manipulating: e.g. repurposing, reapplying, or reorganizing it

Learning: e.g. internalizing someone else's knowledge, reading, taking courses, OJT

Sharing: e.g. conversations in various media and forums to exchange knowledge

There are three ways to improve the 'knowledge culture' of an organization (see diagram at top of this article)

Develop or improve tools which enforce standard processes which, in turn drive effective employee behaviour,

Develop, teach and inculcate processes that drive effective employee behaviour, and

Directly address effective employee behaviour by training, reward systems, communication etc.

There are three distinct types of knowledge in orgaqnizations:

Intelligence, also known as 'explicit' knowledge or ' know-what' (such as the four content examples in the chart above)

Expertise, also known as 'tacit' knowledge or 'know-how '

Networks, contacts, relationships and 'know-who'



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