Scientometrics, Knowledge Management, and Social Network Analysis

I keyed in ‘knowledge management’ in Google Trends. And here is the rather surprising result (at least for me), especially if we contrast that with the number of academic publications with the keyword ‘knowledge management’ in my previous post. As can be seen, the search volume has actually decreased more than 50% from its peak in 2003.

Anyway, here is another trend that is more predictable (but still interesting to see) where I compare the keyword ‘Lotus Notes’ (blue) and ‘Sharepoint’ (red).

Criticisms of Knowledge Management can generally be categorized into 4 groups, namely:

1. The “Fad” argument. Wilson (2002) describes it as “in large part, a management fad, promulgated mainly by certain consultancy companies, and the probability is that it will fade away like previous fads.”
2. An overfocus on IT. In a survey of knowledge management papers from 1990-2000, Swan & Scarborough (2002) found that more than 40% were written by and for computer or IS/IT professionals, suggesting that the IT community “has become an important professional patron of KM.” They further suggest that, although a common rationale for KM calls for a variety of  management practices, the patronage of KM by specific professional communities, especially that of IT, has paradoxical effects — promoting its use and success, but also separating it into areas of narrow focus, thus limiting its effectiveness. But, it is also important to note what Gartner Research (Harris, 2006) suggested that while “strictly speaking, KM does not require the use of software” they “believe that KM technology is necessary to a good KM program.”
3. The questionable validity of the models that underlie KM practice. Many alternative models and classification systems have been proposed for KM, with a major focus evident in the literature on Nonaka’s SECI (Socialization, Externalization, Combination, Internalization) cycle and the conversion of tacit to explicit knowledge, likely driven by the over-focus on IT discussed above. Several critics have pointed out this is, at minimum, an oversimplification. For example, Styhre suggests that “in the knowledge management literature, there is little patience with an organizational resource that cannot be reduced into a number of categories and skills” (Styhre, 2003) and criticizes the codification or knowledge representation approach.
4. The usefulness and validity of the knowledge itself. Underlying all this is an even more fundamental question — is the knowledge that is being created, captured, shared or recorded actually useful and relevant knowledge? These concerns are especially true of explicit knowledge, frequently captured in IT systems. Is what is being captured “best” practice or just
   “any” practice?

Bibliography:
Harris, K. (2006). Knowledge management enables the high performance workplace. Gartner Inc.
Styhre, A. (2003). Understanding knowledge management: Critical and postmodern perspectives. Copenhagen: Copenhagen Business School Press.
Swan, J., & Scarborough, H. (2002). The paradox of “knowledge management”. Informatik Informatique, 2002(1), 10-13.
Wilson, T. D. (2002). The nonsense of ‘knowledge management’. Information Research, 8(1).

Source: Developing a Model of Next Generation Knowledge Management by Kenneth A. Grant and Candace T. Grant.

Further to my previous post on knowledge audit, some questions that should be answered when doing knowledge audit are as follows:

• What information exists in my organization, and where is it located?
• What expertise resides in my organization–who knows what?
• What relevant expertise resides outside my organization, where does this expertise exist, and how do I gain access to it?
• What are the best sources of relevant internal and external information and knowledge?

Source: here

I am currently reading Robert McKee’s Story. In its very first chapter, he discussed why story is very inseparable from human life (pp. 11-12).

Day after day we seek an answer to the ageless question Aristotle posed in Ethics: How should a human being lead his life?

Traditionally humankind has sought the answer to Aristotle’s question from the four wisdoms – philosophy, science, religion, art- taking insight from each to bolt together a livable meaning. But today who reads Hegel or Kant without an exam to pass? Science, once the great explicator. garbles life with complexity and perplexity. Who can listen without cynicism to economists, sociologists, politicians? Religion, for many, has become an empty ritual that masks hypocrisy. As our faith in traditional ideologies diminishes, we turn to the source we still believe in: the art of story.

The knowledge acquisition bottleneck can be described as:

• Narrow bandwidth. The channels that exist to convert organizational knowledge from its source (either experts, documents, or transactions) are relatively narrow.
• Acquisition latency. The slow speed of acquisition frequently is accompanied by a delay between the time when knowledge (or the underlying data) is created and when the acquired knowledge becomes available to be shared.
• Knowledge inaccuracy. Experts make mistakes and so do data mining technologies (finding spurious relationships). Furthermore, maintenance can introduce inaccuracies or inconsistencies into previously correct knowledge bases.
• Maintenance trap. As the knowledge in the knowledge base grows, so does the requirement for maintenance. Furthermore, previous updates that were made with insufficient care and foresight (“hacks”) will accumulate and render future maintenance increasingly more difficult.

As summarised by Christian Wagner in his paper titled Breaking the Knowledge Acquisition Bottleneck Through Conversational Knowledge Management.