Wisdom as an Attribute of Knowledge Work

Article: Rooney, D., B. McKenna, and F. D'Agostino, Wisdom as an Attribute of Knowledge Work

Type of article: Position paper

Audience: Academics, Knowledge Management Professionals

Focus: To define wisdom within the dimensions of psychology and philosophy and its role within knowledge management.

Summary:
Wisdom in the context of decision making is needed because judgment is easily clouded, influence misused, ethics less considered. The authors assert that wisdom is well defined by approaching it both psychologically and philosophically but affirms the approaches are different yet commonalities exist. Further wisdom embodies rational and transcendent forms of knowledge.

From a psychological perspective wisdom coordinates knowledge and judgments. While philosophically wisdom encompasses the social dimensions of shared understanding using adjectives such as prudent, sensory, visceral, worldliness, and tolerance.

To be rational is to reason for the purpose of attainment. Whereas to be transcendent is to know what is possible without rationality.

The primary objective of the article is to debate wisdom’s role in the context of knowledge management. According to Van Loon, decision making becomes increasingly difficult as the volume of sources and types of information grow and vary but Rooney suggests that perhaps wisdom shall prevail.

‘Practical Wisdom and Philosophy’ is the authors focus, from which a framework evolved:

• Ethics – humane tolerance
• Aesthetics – communicative eloquence
• Ontology – classificatory assumptions either explicit (definitions, codes, manuals etc) or implicit (assumptions or implied through practice)
• Mindlessness – to act without regard for routinized ruts, organisational coherence and predetermined destinations.
  

The author concludes warning the reader of potential pitfalls because of the inadequate theorization of knowledge.

Review:
The article’s psychological and philosophical bent aroused interest providing a multi-faceted perspective on wisdom and its application thereof. The authors substantiate their arguments citing authors of varied backgrounds. The article is aptly titled to peak interest from knowledge management specialist curious about the role of wisdom. An interesting read but the article left me wanting to know more. As aptly suggested by the authors how do you measure knowledge, exploit intellectual capital and use computer-based knowledge management systems versus applying wisdom, ethics and imagination.

Article Name: A Framework of Knowledge Management Systems: Issues & Challenges for Theory and Practice.
Author: Jungpil Hahn, Mani R. Subramani
Publication: Knowledge Management Systems 
Keywords: Information in organizations, knowledge management, knowledge management systems, organizational behaviour, organizational learning.

Summary: (259 Words)
Knowledge management concepts and practices in organizations are increasingly becoming important and firms are making momentous IT investments in deploying knowledge management systems (KMS). Knowledge management is the systemic and organizationally specified process for acquiring, organizing, and communicating knowledge of employees so that other employees may make use of it to be more effective and productive in their work.

This paper supplies an in depth research on knowledge management systems by proposing a developed framework called “Locus of Knowledge”. This framework is comprised of:
- Document Repository (Data Warehousing)
- Yellow Pages of Experts (Expertise Profiles and Databases)
- Collaborative Filtering (Internets and Search Engines)
- Electronic Discussion Forum

This framework provides a means to explore issues related to KMS and unifying dimensions underlying different types of KMS. As the basis of value creation increasingly depends on the influence of the intangible assets of firms, knowledge management systems (KMS) are emerging as powerful sources of competitive advantage. However, the general recognition of the importance of such systems seems to be accompanied by a technology-induced drive to implement systems with inadequate consideration of the fundamental knowledge problems that the KMS are likely to solve.

The possibilities that authors have discussed and raised within this paper is all about the size and diversity of networks, the maintenance of knowledge flows, and the long term effects of the use of KMS. This will facilitate a framework for the organizations as a reference that would enhance the usability of Knowledge Management System to its fullest and will also open avenues for future perspectives.

Review: (105 Words)
This article is one of unique writings from other articles. It portrays a sense of formal knowledge management framework and its methodology. One of the beauties about this article is that it explored positive, neutral and negative views of the topic and provided with clear evidences and investigations of each author.

One of the few weaknesses of the articles is that it’s not targeting one particular audience and keeping the views quite general. Conclusion is well built but leaves me with few questions to explore and search, which is on the other hand, is productive for audience. Overall it’s a nice article and worth reading.

(Posted by Jocelyn for Afraz) 

The Role of AI-based Technology in Support of the Knowledge Management Value Activity Cycle

Fowler, A. Journal of Strategic Information Systems, 2000.

Mim-Summer Group (Dick, Holger, Ashwini, Eleanor, Kai)

Type of Article: Empirical study using case based research and analysis.

Audience: Management students, CIOs, IT professionals, Database developers, KM professionals.

Focus/Theme: Explores the potentials and limitations of AI technology use in knowledge management through the exploration of a case study.

Summary

This article relates the relatively older field of Artificial Intelligence (AI) to the newer practice of knowledge management and explores the potentials and limitations. The author does this through linking it to Nonaka’s knowledge spiral and related concepts. He also considers three main areas of AI investigation; knowledge based expert systems (KBES), neural networks (NN) and case based reasoning (CBR) and links these through investigation of a real world case study in a recognised “knowledge company”. The structure he uses is a “Knowledge Value Chain” (KVC) loop to test the concepts under investigation. The medium is a case study featuring a company (Bay-Point) and he takes a phenomenological approach using Glaser and Strauss’s Grounded Theory developed for ethnographic studies. He conceptualises the ideas discovered using the KVC and grounded in the data obtained during the empirical component of the study to reach his conclusions.

The article explores the idea that tacit knowledge is hard to capture. The article is primarily concerned with exploring the extent to which AI technologies, so full of promise early on and with very little practical application to date, can be employed to support businesses manage tacit knowledge ongoing. Overall can AI assist to capture and organise knowledge? His conclusion is yes it can support those processes (capture, disseminate, embody), but reiterates Davenport and Prusak (1998) that only the human brain has the ability to create knowledge. He recommends a combination of formal explicit (machine-based) and tacit (human) knowledge processes to produce problem-solving capabilities to provide a competitive edge in today’s companies. He quotes Polanyi by saying that tacit knowledge cannot be codified and represented by a set of articulated rules or algorithms, and notes that this is still true even despite the advances in fuzzy logic and “intelligent agent” technologies. Tacit knowledge is embedded in perception, belief and values which are characteristics that contravene the principles of computer science. Artificial Intelligence (AI) technologies cannot substitute for the knowledge process, but it can facilitate it.

Review

The article is very well written and readable, even though very lengthy in its attempt to encompass and relate the different knowledge management and AI concepts. Using one case study to expand the framework was a good idea, although it could be argued that only one case study was insufficient to illustrate the complex ideas described. However the author does provide a very thorough literature review and simplifies a very broad field (AI development) to three main concepts to enable better understanding. The choice of an ethnographic approach suited the subject of enquiry; can AI technologies deal with the capture and dissemination of tacit knowledge? The conclusion that no it can’t, but it can take the dog work out of it.

References;

Davenport, T and Prusak, L (1998). Working Knowledge; How Organisations Manage What they Know. HBS Press, Boston.

Nonaka, L. Takeuchi, H. (1995). The Knowledge Creating Company; How Japanese Companies Create the Dynamics of Innovation. Oxford University Press. New York.

Polanyi, M. (1998). Personal Knowledge: Towards A Post-Critical Philosophy. Routledge, London.

Title: Many Rivers to Cross from ICT to Knowledge Management Systems.

ARTICLE SUMMARY & Review (Week3-Class4) by Torrance Mayberry
(Group: Pennie, Ian, vijay, Helen Ng )

Author: Paul H. J. Hendricks
Audience: Academics, Knowledge Management Change Agents.
Theme: ICT acts as catalyst for knowledge management and ICT alone cannot make organizations more knowledgeable.
Aim: Discern relationships between ICT tools and knowledge.

The relationship between ICT tools and knowledge management has proven to be problematic. The advocates of ICT-driven knowledge management suggest ICT alone enables knowledge acquisition, knowledge transfer and distribution, and knowledge creation. In other words, alone, a pure engineering approach can make organisations more knowledgeable.

The advocates against a pure engineering approach acknowledge that ICT can act as a catalyst for knowledge management but they also argue that ICT tools primarily address data and information and not knowledge. In other words, a pure engineering approach ignores the management approach to knowledge.

Research conducted in the period 1993 – 1998 has shown that much of the knowledge management literature was biased towards a technological agenda. This research cites the engineering approach to knowledge was the dominant position in the knowledge management space. Moreover, the engineering approach to knowledge steered away from wider organisational issues and it ignored social and behavioral factors.

To address the ICT-knowledge management problem, one must make a clear distinction between the engineering approach and the management approach. Additionally, one needs to discern between the four classes to knowledge: the knowledge storage approach; the knowledge flow approach; the organizational learning approach; and the knowledge measurement approach. An understanding of these distinctions combined with a set of assessment criteria will provide rationale to establish a meaningful link from ICT to knowledge management.

Review
In conclusion, this article and title assumes the reader of the article has a clear understanding that there are many rivers to cross get knowledge and that we, in knowledge management, know where the rivers to be crossed are located.

A few questions to ponder for the reader of this summary:

1. What are the many rivers in your organisation?
2. Have the many rivers been defined?
3. Where are the crossings located for the many rivers?
4. What are the bridges that need to be constructed to reach the other side?

Factors Affecting the Adoption of Knowledge Management Technologies: A Discriminative Approach

ARTICLE SUMMARY & REVIEW (Week3-Class4) by Fatemeh Hosseini

(Group: KMx6- Fatemeh, Skalk, Bee, Lanoi, Max, Roger)

Article: Factors Affecting the Adoption of Knowledge Management Technologies: A Discriminative Approach

Please find the review for this article here.

Knowledge management systems: finding a way with technology

ARTICLE SUMMARY & REVIEW (Week3-Class4) by Fatemeh Hosseini

(Group: KMx6- Fatemeh, Skalk, Bee, Lanoi, Max, Roger)

Article: John S. Edwards, Duncan Shaw & Paul M. Collier (2005). Knowledge management systems: finding a way with technology. Emerald Group Publishing Limited. 9 (1), 113-125.

Please find the review here.

The Tools & Technologies Needed for Knowledge Management

ARTICLE SUMMARY & REVIEW (Week3-Class4)
(By MIM-SUMMER: Ashwini, Dick, Eleanor, Kai, Holger)

Title: The Tools and Technologies Needed for Knowledge Management (KM)

Theme: This article aims to provide an overview of KM software market, broadly Consisting of two categories: KM infra-structure tools and technologies and KM access software.

SUMMARY

The author, referring to different definitions of knowledge management, recognizes the enormous value that human resources bring to an organization. She suggests that effective leveraging of knowledge, enabled by appropriate technology infra-structure providing the base for establishment of KM solutions, leads to organization environments where knowledge sharing and collaboration becomes a ‘BAU’. KM infra-structure tools and KM access software are the two major categories of KM software market.

KM Infra-structure Tools and Technologies

Data Warehousing Infra-structure: These include tools and application software that focus on extraction and analysis of data captured from business applications to support business decision-making.

Content Retrieval/Management software: These tools, supporting un-structured data management requirements of KM initiatives, enable users to organize information at the object level based on topical areas rather than full documents.

Business-ware Management Systems (BWMS): They enable knowledge capture & use by providing support for real-time application integration and business process automation.

Collaborative Applications: They focus on core functions like email, shared folders/databases, group calendaring/scheduling, and custom applications for knowledge sharing and collaboration.

KM Access Software

Enterprise Information Portals (EIP): This software, augmented by KM tools, provides individual/group access to both structured and un-structured data.

Intellectual capital Management (ICM) Software: It builds and manages the employee competencies inventory, monitors and manages processes by transferring know-how into corporate policies and procedures.

Workforce/Skills management Applications: They determine location of corporate expertise, help in hiring/deploying/retaining employees for supporting KM initiatives.

Emerging KM Tools & Technologies

The new emerging technologies include ‘knowledge exchange platforms’ for trading in knowledge, corporate learning management software, knowledge workflow management software, and knowledge profiling technologies.

REVIEW

The article provides a bird’s eye view of the various tools and technologies available in the KM software market. The simple language, good writing style, logical flow of subject matter has served the intended purpose of introducing the reader to the tools and technologies needed in KM. However, the importance of adoption of these technologies by the ‘people’ component of a KM system has been totally ignored and there is a scope for improving the structure of subject matter.

Reference:
Duffy, J. (2001). The Tools and Technologies Needed for Knowledge Management, Information Management Journal, 35 (1), pp 64.