Friday, 7 March 2008
Collective Learning Statement on Social Technologies
At the BIS4410 seminar on Social Technologies, it was noted that while these technology platforms may provide an efficient means of fostering organisational learning, they cannot replace traditional face-to-face conversations that take place in life scenarios such as the on-the-job learning or knowledge café. This is because it is sometimes very hard to put thinking into words and or writing them down. Informal or even formal face-to-face conversations remain the best way to transfer tacit knowledge which is the often the most important form of knowledge that needs to be well managed.
Collective Learning Statement on Social Networks (SN) and Communities of Practice (CoP)
At the BIS 4410 seminar on SN and CoP, the discussion centred around the similarities and differences between the 2 concepts, their examples, and their impact on knowledge management. One point I noted is the fact that when people say social networks nowadays, they are talking about online communities like MySpace and Facebook and not just ordinary network of people connected by being members of the same geographic community, family or social club. There was also a discussion on the difference between SN and CoP which was basically given as the purpose for setting up each of them. While CoPs are more domain or business oriented, SNs are more social and involve a larger number of participants and capabilities. However the 2 concepts can act as useful platforms for knowledge creation and sharing. Another impact is that of Technology on the way we live such that traditional means of socialising are giving way to technology-enabled platform that enable socialisation amongst people from very diverse geographic, political and cultural backgrounds.
Thursday, 6 March 2008
Collective Learning Statement on Knowledge Management (KM) Models
In discussing the emerging concept of KM, the problem of differentiating between KM models and methods (approaches) to managing knowledge also came to fore at the BIS 4410 seminar on KM models. Models were seen as abstraction of reality, an ideal state that can be achieved through several means and which is expected to yield the best results. On the other hand a method is a means or manner of procedure, especially a regular systematic way of accomplishing something or the procedures and techniques characteristic of a particular discipline or field of knowledge. These definitions imply that while models are high-level abstraction of an ideal, methods are detailed step-by-step procedure of achieving a goal. A question that came to my mind at this point was whether organisations should focus on the available KM models with a view to adopting suitable one for use or whether the focus should be on the method to adopt in identifying and disseminating knowledge within the organisation. Another point in this conversation is the fact that no matter what model an organisation seeks to adopt to manage knowledge, it must develop KM methods that are suitable for its own peculiar environment to successfully derive maximum benefits from the adoption of any particular KM model.
Having shown divergence in KM philosophies, definitions, theories and models which has left gaps that hinder Knolwedge management strategies development in organisations, the facilitators of the Module (Aboubakr and Mark) suggested - in their paper on Notions of Knowledge management - that a common basis is required to facilitate communication between practitioners having different roles and perspective; and to enable interoperability of different knowledge management strategieS among departments within an organisation or between different organisations. There was also an attempt to differentiate between ‘Information Systems’ and Knowledge Management Systems’ in the same paper. While Information systems are seen as systems where static relationships between entities dominate the architecture and design; and a single meaning is ascribed to all entities and to the relationship between them, while Knowledge management systems need to support ad-hoc dynamic creation of changing relationships amongst entities, thus supporting the unpredictable nature of knowledge. In my view, this position is similar to that of Malhotra (2000), who suggested that today’s net business have business models that support the constant and dynamic changes occurring in the business environment.
The important points learned from my research on the KM models and definition themes come from the movement to business model rethinking posited by Malhotra (2000) where organisations where urged to adopt KM to adapt to the rapid and dynamic changes in the e-everything age. Another one is the KM taxonomy presented by Earl (2001), which I think organisations can examine to adopt an approach or a combination of approaches that are in line with their organisational aspirations and environment.
Having shown divergence in KM philosophies, definitions, theories and models which has left gaps that hinder Knolwedge management strategies development in organisations, the facilitators of the Module (Aboubakr and Mark) suggested - in their paper on Notions of Knowledge management - that a common basis is required to facilitate communication between practitioners having different roles and perspective; and to enable interoperability of different knowledge management strategieS among departments within an organisation or between different organisations. There was also an attempt to differentiate between ‘Information Systems’ and Knowledge Management Systems’ in the same paper. While Information systems are seen as systems where static relationships between entities dominate the architecture and design; and a single meaning is ascribed to all entities and to the relationship between them, while Knowledge management systems need to support ad-hoc dynamic creation of changing relationships amongst entities, thus supporting the unpredictable nature of knowledge. In my view, this position is similar to that of Malhotra (2000), who suggested that today’s net business have business models that support the constant and dynamic changes occurring in the business environment.
The important points learned from my research on the KM models and definition themes come from the movement to business model rethinking posited by Malhotra (2000) where organisations where urged to adopt KM to adapt to the rapid and dynamic changes in the e-everything age. Another one is the KM taxonomy presented by Earl (2001), which I think organisations can examine to adopt an approach or a combination of approaches that are in line with their organisational aspirations and environment.
Collective Learning Statement on Knowledge Management (KM) Definitions
From the research conducted on the definition of Knowledge management as well as the related elements of ‘data’, ‘information’ and ‘knowledge’ I have learnt so many things. Firstly regarding the elements, it is clear that to say anything is data, information or knowledge, there must be a context including the relationship the between the person making an expression and the person who is expected to read it; and the domain area or subject matter. In essence what is data, information or knowledge to a person in a particular situation, could be any other one of the 3 to another person in the same or different situation, or to the same person in a different scenario.
Regarding the definition of Knowledge management, the outcome of the research conducted by the facilitators of BIS 4410 (Aboubakr and Mark) throws a lot of light on what KM means, including the key elements of Knowledge creation, dissemination and utilisation. At the seminar there was a heated discussion on the role of knowledge storage which was not explicitly mentioned in the conceptual map developed by Aboubakr et al although the word ‘Capturing’ was mentioned. My take on this is that to convert tacit knowledge to explicit knowledge, and ensure its utilisation, there must be one form of storage or the other. In addition, the role of communication was also highlighted as this is the most important means of disseminating knowledge within an organisation. Another point worthy of note is the role of information technology in KM strategies and it was highlighted that Information systems are critical to KM as they provide an easy platform for knowledge sharing especially systems like decision support systems, expert systems, and the internet.
Regarding the definition of Knowledge management, the outcome of the research conducted by the facilitators of BIS 4410 (Aboubakr and Mark) throws a lot of light on what KM means, including the key elements of Knowledge creation, dissemination and utilisation. At the seminar there was a heated discussion on the role of knowledge storage which was not explicitly mentioned in the conceptual map developed by Aboubakr et al although the word ‘Capturing’ was mentioned. My take on this is that to convert tacit knowledge to explicit knowledge, and ensure its utilisation, there must be one form of storage or the other. In addition, the role of communication was also highlighted as this is the most important means of disseminating knowledge within an organisation. Another point worthy of note is the role of information technology in KM strategies and it was highlighted that Information systems are critical to KM as they provide an easy platform for knowledge sharing especially systems like decision support systems, expert systems, and the internet.
Thursday, 28 February 2008
Social Technology:Impact on Knowledge Creation
Introduction
The word ‘social’ is mostly associated with human beings and the ways they interact amongst themselves within the society. This paper discusses the subject of social technologies and their impact on Knowledge Management. During the research for this paper it was discovered that the term ‘social technologies’ is synonymous with other terms like social software, social computing, conversational technologies, and collaborative software. However a common characteristic to all these terms is the fact that they involve collaboration among human beings through the use of information systems especially the Internet and the World Wide Web.
Social Technologies
According to Wikipedia, social software are a range of web-based software programs that allow users to interact and share data with others and they have become popular with social network sites like MySpace and Facebook, media sites like Flickr and You Tube, and commercial sites like Amazon and Ebay. There are so many sites on the internet today that are built on social software that enable non-technical IT users to collaborate, make connections, share information and develop professional skills. The range of activities offered by these sites is endless. While some are just for socialising and meeting people with common social interests (MySpace and Facebook), others are geared towards enabling more professional connections to enable knowledge sharing by linking members to others who are experts in their area of interest (Linked In).
An important perspective to this discourse was found on Wikipedia where it was stated that while there have been older software technologies that enabled collaboration like mailing lists and Usenet, the term has more recently been restricted by users to refer to Blogs and Wikis. As stated on Wikipedia, others have come to suggest that the term ‘social software’ is more appropriate for products that combine the ‘‘use of two or more modes of computer mediated communication that result in community formation’’. Social network sites like Facebook fit this description as the mode of communication includes one-to-one (email and instant messaging), and one-to-many (web pages and Blogs). Another mode of communication is many-to-many (Wikis). Most of the social network sites available to day employ a combination of these modes enable users to communicate and /or interact. Other tools employed by the social network sites include Internet forums and chat rooms.
According to Wikipedia, the proliferation of the World Wide Web with web-based communities and hosted services such as social-networking sites, wikis, and blogs - which aim to facilitate creativity, collaboration and sharing among users - has lead to a new trend called Web 2.0. Although this term suggests a new version of the World Wide Web, it does not mean an update to any technical specification, but refers to changes in the way people use the web. There is a wide variety in the types and uses of social technologies and network including social network services (Facebook, Hi5, MySpace), Commercial social networks (Dell Ideastorm), Social bookmarking (del.icio.us, digg, stumbleupon), social libraries (LibraryThing, imdb.com), and Virtual Worlds (second life),
Impact on Knowledge Management
A major characteristic of these online communities is that most of them evolve. Although the idea might be that of certain individuals, it is the users who collaborate via these platforms that actually own them and they have power to determine who they want to collaborate with, what they are wiling to share and the mode of interaction. Another major characteristic of social technologies is that the enable conversations to take place. Since conversations form the bedrock on which organisational learning and knowledge creation and sharing occurs, these social networks are very strong tools that can boost knowledge management.
References
http://en.wikipedia.org/wiki/Social_software accessed on March 3 2008.
http://en.wikipedia.org/wiki/Web_2 accessed on March
The word ‘social’ is mostly associated with human beings and the ways they interact amongst themselves within the society. This paper discusses the subject of social technologies and their impact on Knowledge Management. During the research for this paper it was discovered that the term ‘social technologies’ is synonymous with other terms like social software, social computing, conversational technologies, and collaborative software. However a common characteristic to all these terms is the fact that they involve collaboration among human beings through the use of information systems especially the Internet and the World Wide Web.
Social Technologies
According to Wikipedia, social software are a range of web-based software programs that allow users to interact and share data with others and they have become popular with social network sites like MySpace and Facebook, media sites like Flickr and You Tube, and commercial sites like Amazon and Ebay. There are so many sites on the internet today that are built on social software that enable non-technical IT users to collaborate, make connections, share information and develop professional skills. The range of activities offered by these sites is endless. While some are just for socialising and meeting people with common social interests (MySpace and Facebook), others are geared towards enabling more professional connections to enable knowledge sharing by linking members to others who are experts in their area of interest (Linked In).
An important perspective to this discourse was found on Wikipedia where it was stated that while there have been older software technologies that enabled collaboration like mailing lists and Usenet, the term has more recently been restricted by users to refer to Blogs and Wikis. As stated on Wikipedia, others have come to suggest that the term ‘social software’ is more appropriate for products that combine the ‘‘use of two or more modes of computer mediated communication that result in community formation’’. Social network sites like Facebook fit this description as the mode of communication includes one-to-one (email and instant messaging), and one-to-many (web pages and Blogs). Another mode of communication is many-to-many (Wikis). Most of the social network sites available to day employ a combination of these modes enable users to communicate and /or interact. Other tools employed by the social network sites include Internet forums and chat rooms.
According to Wikipedia, the proliferation of the World Wide Web with web-based communities and hosted services such as social-networking sites, wikis, and blogs - which aim to facilitate creativity, collaboration and sharing among users - has lead to a new trend called Web 2.0. Although this term suggests a new version of the World Wide Web, it does not mean an update to any technical specification, but refers to changes in the way people use the web. There is a wide variety in the types and uses of social technologies and network including social network services (Facebook, Hi5, MySpace), Commercial social networks (Dell Ideastorm), Social bookmarking (del.icio.us, digg, stumbleupon), social libraries (LibraryThing, imdb.com), and Virtual Worlds (second life),
Impact on Knowledge Management
A major characteristic of these online communities is that most of them evolve. Although the idea might be that of certain individuals, it is the users who collaborate via these platforms that actually own them and they have power to determine who they want to collaborate with, what they are wiling to share and the mode of interaction. Another major characteristic of social technologies is that the enable conversations to take place. Since conversations form the bedrock on which organisational learning and knowledge creation and sharing occurs, these social networks are very strong tools that can boost knowledge management.
References
http://en.wikipedia.org/wiki/Social_software accessed on March 3 2008.
http://en.wikipedia.org/wiki/Web_2 accessed on March
Social Networks and Community of Practice: Definitions and Comparison
Introduction
Due to the fact that today’s economy runs on knowledge, many organisations are working hard to capitalize on this by using cross-functional teams, customer or product-focused business units and work groups to capture and spread ideas and Know – how (Wenger et al, 2000). This paper attempts to define the concepts of Social Networks (SN) and Communities of Practice (CoP) and discuss how organisations have been using them to manage knowledge. The differences and similarities that exist between SN and CoP will also be discussed with examples of how organisations have employed these concepts to improve organisational performance.
Communities of Practice (CoP)
According to Wenger et al (2000), Communities of practice are informal group of people bound by shared expertise and a passion for a joint enterprise, and who share their experience and knowledge in free-flowing and creative ways that promote new approaches to solving problems. To enable a proper understanding of the CoP concept, Wenger et al (2000) differentiates between CoP and formal work teams. Formal work teams are formed by managers to complete specific projects and members are selected by managers based on their ability to contribute to achieving the team’s goals. The team is disbanded on completion of the project. CoPs on the other hand are informally established by members who select their own members, decide on their leadership and set their own agenda and the group’s interaction is continuous. p. In addition, CoPs are not developed for specific projects but the goal is to share experiences and expertise about a specific area of common interest and members decide to join based on their perception of whether they can contribute to the group or not.
A CoP can exist within a department of an organisation, across divisions within an organisation or even have members from different organisations. According to Wenger et al (2000), CoPs add value to organisations in many ways including driving strategy (CoP at the heart of World Bank’s knowledge management strategy); starting new lines of business (a group of consultants whose focus was retail marketing for banking but formed a COP that eventually led to a new line of business of marketing approaches for financial services firms); solving problems quickly (members of CoP within Buckman’s Lab respond to queries from other members around the world within 24 hours); transferring best practices (‘tech clubs’ within DaimlerChrysler helping the company to move to platforms which cut R&D costs by half); developing professional skills (IBM where CoP members hold their own conferences to sharpen their skills); and helping companies to recruit and retain talents (at American Management System, a consultant decided to stay after a community helped her to find project opportunities that suited her interests and expertise). Wenger et al (2000) also suggested that to derive maximum benefits from CoPs, organisations must cultivate them by identifying potential CoPs that will enhance the organisations strategic capabilities, providing infrastructures to support the CoPs in using their expertise effectively, and using non-traditional methods to assess the value of the organisation’s CoPs.
Social Networks
According to Wikipedia (accessed on March 4 2008), Social Networks refer to a social structure made up of nodes (individuals or organisations), that are tied by one or more specific type of interdependencies including values, visions, idea, friends, kinship, dislike, taste, conflict, trade, web links, sexual relations and so on. In its simplest form a social network is a map of the relevant ties between nodes. Social Networks (SN) occur at different levels, from individuals, to families and up to governments. In recent times, SN have come to mean Internet based communities where members set up their profiles to find old friends, meet new friends, start relationships, share interests, share personal information, and meet people who have similar interests. The most popular of such sites on the Internet today include Myspace and Facebook which account for most traffic in terms of online social networking. Within these social networks, there are facilities for people to form groups with divergent interests from fund raising for a cause, to old and current students of educational institutional institutions, supporters of sport clubs or political parties, human right activists and even people that have common interest in music, movies and art. It would not be out of place to say that the opportunities for networking provided by these social networks are endless. People have even been able to find jobs or lost relatives through them. These networks also have capacity to enable business people to work together and share ideas on business projects. In fact some organisations encourage their members to join these social networks to collaborate with members of the same organization located in the same or different geographic zones.
COMPARISON OF CoP and SN
Communities of practice and social network are similar in the sense that they both involve the interaction of people and they can be used as a platform for creating and sharing knowledge. The difference is in the purpose for which they are formed. CoPs are often formed within organisations and are encouraged by such organisations to foster knowledge creation and sharing amongst its members - who have the same passion or are experts in specific professional domains like engineering, software development, nursing, medicine or financial management - with the purpose of creating value for the organisation. Social Networks on the other hand, involve people and even organisations from all works of life interacting for the purpose of simply socialising. Looking at the 2 concepts, it is also possible for a CoP to employ a social network in carrying out its activities by forming a group within the social network. Members of the CoP can share personal information or domain specific knowledge through the social network. In essence a CoP can be called a form of Social Network given their informal nature but Social Networks cannot be regarded as CoP.
References
Wenger, E.C., Snyder, W.M. (2000), "Communities of practice: the organizational frontier", Harvard Business Review, Vol. 78 No.1, pp.139-45.
http://en.wikipedia.org/wiki/Social_network accessed on March 6, 2007.
Due to the fact that today’s economy runs on knowledge, many organisations are working hard to capitalize on this by using cross-functional teams, customer or product-focused business units and work groups to capture and spread ideas and Know – how (Wenger et al, 2000). This paper attempts to define the concepts of Social Networks (SN) and Communities of Practice (CoP) and discuss how organisations have been using them to manage knowledge. The differences and similarities that exist between SN and CoP will also be discussed with examples of how organisations have employed these concepts to improve organisational performance.
Communities of Practice (CoP)
According to Wenger et al (2000), Communities of practice are informal group of people bound by shared expertise and a passion for a joint enterprise, and who share their experience and knowledge in free-flowing and creative ways that promote new approaches to solving problems. To enable a proper understanding of the CoP concept, Wenger et al (2000) differentiates between CoP and formal work teams. Formal work teams are formed by managers to complete specific projects and members are selected by managers based on their ability to contribute to achieving the team’s goals. The team is disbanded on completion of the project. CoPs on the other hand are informally established by members who select their own members, decide on their leadership and set their own agenda and the group’s interaction is continuous. p. In addition, CoPs are not developed for specific projects but the goal is to share experiences and expertise about a specific area of common interest and members decide to join based on their perception of whether they can contribute to the group or not.
A CoP can exist within a department of an organisation, across divisions within an organisation or even have members from different organisations. According to Wenger et al (2000), CoPs add value to organisations in many ways including driving strategy (CoP at the heart of World Bank’s knowledge management strategy); starting new lines of business (a group of consultants whose focus was retail marketing for banking but formed a COP that eventually led to a new line of business of marketing approaches for financial services firms); solving problems quickly (members of CoP within Buckman’s Lab respond to queries from other members around the world within 24 hours); transferring best practices (‘tech clubs’ within DaimlerChrysler helping the company to move to platforms which cut R&D costs by half); developing professional skills (IBM where CoP members hold their own conferences to sharpen their skills); and helping companies to recruit and retain talents (at American Management System, a consultant decided to stay after a community helped her to find project opportunities that suited her interests and expertise). Wenger et al (2000) also suggested that to derive maximum benefits from CoPs, organisations must cultivate them by identifying potential CoPs that will enhance the organisations strategic capabilities, providing infrastructures to support the CoPs in using their expertise effectively, and using non-traditional methods to assess the value of the organisation’s CoPs.
Social Networks
According to Wikipedia (accessed on March 4 2008), Social Networks refer to a social structure made up of nodes (individuals or organisations), that are tied by one or more specific type of interdependencies including values, visions, idea, friends, kinship, dislike, taste, conflict, trade, web links, sexual relations and so on. In its simplest form a social network is a map of the relevant ties between nodes. Social Networks (SN) occur at different levels, from individuals, to families and up to governments. In recent times, SN have come to mean Internet based communities where members set up their profiles to find old friends, meet new friends, start relationships, share interests, share personal information, and meet people who have similar interests. The most popular of such sites on the Internet today include Myspace and Facebook which account for most traffic in terms of online social networking. Within these social networks, there are facilities for people to form groups with divergent interests from fund raising for a cause, to old and current students of educational institutional institutions, supporters of sport clubs or political parties, human right activists and even people that have common interest in music, movies and art. It would not be out of place to say that the opportunities for networking provided by these social networks are endless. People have even been able to find jobs or lost relatives through them. These networks also have capacity to enable business people to work together and share ideas on business projects. In fact some organisations encourage their members to join these social networks to collaborate with members of the same organization located in the same or different geographic zones.
COMPARISON OF CoP and SN
Communities of practice and social network are similar in the sense that they both involve the interaction of people and they can be used as a platform for creating and sharing knowledge. The difference is in the purpose for which they are formed. CoPs are often formed within organisations and are encouraged by such organisations to foster knowledge creation and sharing amongst its members - who have the same passion or are experts in specific professional domains like engineering, software development, nursing, medicine or financial management - with the purpose of creating value for the organisation. Social Networks on the other hand, involve people and even organisations from all works of life interacting for the purpose of simply socialising. Looking at the 2 concepts, it is also possible for a CoP to employ a social network in carrying out its activities by forming a group within the social network. Members of the CoP can share personal information or domain specific knowledge through the social network. In essence a CoP can be called a form of Social Network given their informal nature but Social Networks cannot be regarded as CoP.
References
Wenger, E.C., Snyder, W.M. (2000), "Communities of practice: the organizational frontier", Harvard Business Review, Vol. 78 No.1, pp.139-45.
http://en.wikipedia.org/wiki/Social_network accessed on March 6, 2007.
Monday, 18 February 2008
Report On Knowledge Cafe.
Introduction
This report presents the outcome of the knowledge Café held on February 15 2008. The facilitators asked each group to write down a list of the worst things that could prevent an organisation from being able to manage knowledge. Out of these initial list each group select the 3 worst things.
Group 2 list of the 3 ‘Worst’ things that could prevent Knowledge Management
1. No Communication Strategy - This is where the management of an organisation does not consciously put in place a plan to ensure effective communication amongst its members and also with the external environment. This might include lack of Information technology enabled communication techniques like Intranets, Internets, and E –mail; no means of manual communication like letters, hand-over notes, and other documentation; and the organisation does not promote social interaction amongst its members using restaurants, bars, or other social gathering amongst members both during working hours and after work.
2. No Learning and Development Strategy – The organisation does not promote organisational learning by making conscious effort to train its members. There are no plans to tap into the knowledge and skills of members and other external parties to train existing members on new and emerging ideas about doing things within its industry. There are no clear development paths for members and there are no policies regarding training and re-retraining of members.
3. No Identification of Required Knowledge - The organisation does not make a conscious effort to identify the knowledge it has and that which is required to achieve its goals. The organisation’s leaders are not aware of the difference between what members currently know and what they ought to know to improve performance or gain competitive advantage (called Knowledge Gap). In essence the organisation cannot identify the kind of knowledge it requires to achieve organisational goals.
The Important Things for an Organisation to do to Manage Knowledge
From the foregoing, the writer believes that to effectively manage knowledge and promote organisation learning, leaders in the organisation must take necessary steps to consciously and actively identify the knowledge required to achieve its goals; promote organisational learning through a well documented training and development plan for all its members; and encourage effective communication amongst its members using both information technology enabled tools as well as other informal means of socialization which are best for sharing tacit knowledge.
This report presents the outcome of the knowledge Café held on February 15 2008. The facilitators asked each group to write down a list of the worst things that could prevent an organisation from being able to manage knowledge. Out of these initial list each group select the 3 worst things.
Group 2 list of the 3 ‘Worst’ things that could prevent Knowledge Management
1. No Communication Strategy - This is where the management of an organisation does not consciously put in place a plan to ensure effective communication amongst its members and also with the external environment. This might include lack of Information technology enabled communication techniques like Intranets, Internets, and E –mail; no means of manual communication like letters, hand-over notes, and other documentation; and the organisation does not promote social interaction amongst its members using restaurants, bars, or other social gathering amongst members both during working hours and after work.
2. No Learning and Development Strategy – The organisation does not promote organisational learning by making conscious effort to train its members. There are no plans to tap into the knowledge and skills of members and other external parties to train existing members on new and emerging ideas about doing things within its industry. There are no clear development paths for members and there are no policies regarding training and re-retraining of members.
3. No Identification of Required Knowledge - The organisation does not make a conscious effort to identify the knowledge it has and that which is required to achieve its goals. The organisation’s leaders are not aware of the difference between what members currently know and what they ought to know to improve performance or gain competitive advantage (called Knowledge Gap). In essence the organisation cannot identify the kind of knowledge it requires to achieve organisational goals.
The Important Things for an Organisation to do to Manage Knowledge
From the foregoing, the writer believes that to effectively manage knowledge and promote organisation learning, leaders in the organisation must take necessary steps to consciously and actively identify the knowledge required to achieve its goals; promote organisational learning through a well documented training and development plan for all its members; and encourage effective communication amongst its members using both information technology enabled tools as well as other informal means of socialization which are best for sharing tacit knowledge.
Friday, 1 February 2008
Knowledge Management Definitions
Introduction
As noted by Malhotra (2000), despite the lack of ‘‘commonly agreed upon definition of knowledge management’’ organisations both in the public and private sectors are getting increasingly interested in the topic. This paper reviews a sample of definitions of Knowledge Management (KM) that have been proposed by various scholars who have conducted research on this emerging subject. To do this, various definitions of ‘knowledge’, especially in relation to ‘information’ and ‘data’ will be discussed to enable a holistic view of the concept of KM. At the end of this paper, an attempt will be made to describe knowledge management by combining elements of the various definitions that will be discussed.
Knowledge, Information and Data.
The distinction between Knowledge, information and data has always been a subject of much interest in the academia due to the lines that exist between the definitions of each word, especially between knowledge and information. Chaba (2008), suggests a distinction by giving an example where ‘£150’ is just data, ‘£150 pounds on gas bill’ is information, and ‘If I have £150, I have got enough money to pay my Gas Bill’ is knowledge. This example seems to suggest that ‘information’ is ‘data’ with some meaning, and knowledge is a combination of some information and a context. Implicit in this example is the ‘knowledge’ that having £150 pounds means that the gas bill can be paid, that is having £150 and knowing that this amount can pay the gas bill.
The distinction provided by the example given above is similar to that given by Kock Jr et al (1996), where its was suggested that although Knowledge, Information and Data are not synonymous, they are interrelated and have no useful existence without each other. To compare the three words within an organisational context, Kock Jr et al (1996) gave an example of a situation where a division manager interprets data (e.g. Productivity figures) in a context (e.g. in a meeting with a manager in one of the division’s plant), as information (e.g. the productivity figures are low). This information is then combined with knowledge (e.g. if we have a new lathe in operation the production will go up), within a domain (e.g. the plant’s assembly line), to produce effective action (e.g. introduce a new lathe into the plant’s assembly line). Another useful distinction made by Kock Jr et al (1997) is that while ‘information’ is descriptive – relating to the past and the present - , ‘knowledge’ is mostly predictive as it provides the basis for predicting the future, with a degree of certainty, using information about the past and the present.
According to Stenmark (2002), Figure 1 below is commonly used to describe the relationship between these terms but the arguments are flawed as they are based on wrong assumptions that the relationship between data, information and knowledge is linear, asymmetric (data is transformed into information, and information is transformed into knowledge), and that knowledge is superior to information and information is superior to data.
Fig 1 Data, Information and Knowledge
Source: Stenmark (2002)
Toumi 1999 (cited in Stenmark 2002) , challenged this view by suggesting that ‘knowledge’ embedded in the human mind can be instantiated to form explicit ‘information’ which can subsequently be coded into pure data which has the highest value from an IS/IT perspective; and since computers can only effectively process data, it should be on top of the value hierarchy.
Stenmark (2002) however argues that both arguments presented above are erroneous and that data, information and knowledge are interwoven in more complex ways because they influence each other and the value of any of them is dependent on the purpose for which it is being used. ‘Data’ and ‘information’ requires ‘knowledge’ to be interpretable and likewise, new ‘knowledge’ is constructed using existing ‘data’ and ‘information’. In the words of Stenmark (2002), ‘‘since a piece of text itself is not sufficient to exhaustively describe the knowledge to which it refers, the reader's tacit knowledge must be compatible with that of the writer in order to interpret and fully comprehend the implications of the information. Hence, what one conceives as information another sees as data’’
In essence the relationship between ‘data’, ‘information’ and ‘knowledge’ is very complicated and to understand any one of them, there must be a context and a purpose. What is regarded as mere ‘data’ may be seen as ‘information’ by another person or even by the same person in a different context or situation. From the arguments put forward so far in this paper, ‘knowledge’ can thus be likened to an understanding or cognition of a specific domain area or subject exhibited by an individual as a result of his experience or just gut feeling; can either be expressed in form of information or data or which the individual may not be able to make explicit; and which can enable effective action. Having put ‘knowledge’ in a proper perspective in relation to ‘data’ and ‘information’, this paper progresses with an analysis of various definitions of ‘Knowledge’ and Knowledge Management (KM).
Knowledge Management (KM) Definitions
Beijerse (2000), defined knowledge as follows;
‘‘knowledge is seen here as information; the capability to interpret data and information through a process of giving meaning to these data and information; and an attitude aimed at wanting to do so’’.
This definition is based on other definitions where knowledge is seen as ‘something more than information’. As suggested by Beijerse (1999), a popular distinction - first made by Michael Polanyi – is that made between tacit and explicit knowledge. Polanyi (1966), cited in Beijerse (1999), stated that because people acquire knowledge by active (re)creation and organisation of their own experience, tacit or personal knowledge is crucial to human cognition and knowledge that can be expressed in words and numbers is just a tip of the iceberg. Implicit in this definition is the distinction between tacit and explicit knowledge which complement and influence each other in the creative actions of people.
KM, Beijerse (1999) also came up with a derived definition of managements as follows;
‘‘Management is the strategy-driven motivation and facilitation of people, aimed at reaching the organizational goals’’
This definition according to Beijerse (1999) is predicated on the central elements of management including the formulation of a strategy, ensuring that the strategy is realized, organization as a tool fulfilling the first two elements and the people who manage and are managed within the organisation.
Looking at the two definitions above, Beijerse (1999) suggests that KM is more specific than management in that while management is about motivating and stimulating people to achieve specified goals, KM focuses more on one aspect of people – their knowledge.
Different authors have defined KM in different ways. Some focus on reference to KM as the process of managing organisations’ intangible assets. An example of these is Sveiby (cited by Beijerse, 1999), who defined KM as ‘‘the art of creating value from an organization's intangible assets’’. Den Hertog and Huizinga, (1997), as cited by Beijerse (1999), placed emphasis on the choice organisations make regarding their core competencies referred to as ‘knowledge ambition’ and thus defined KM as ‘‘using instruments to realize the knowledge ambition’’. Beijerse (1999) also cited the work of Mathieu Weggeman (1997) who focused on the ‘knowledge value chain involving four successive constituent processes. These are first, determination of the strategic need for knowledge; second, determination of the knowledge gap which is quantitative and qualitative difference between needed and available knowledge in the organisation; third, narrowing of the knowledge gap by developing knowledge, buying knowledge, improving on existing knowledge, or getting rid of outdated or irrelevant knowledge; and fourth, dissemination and application of available knowledge to serve the interest of customers and other stakeholders. Weggeman (1997), (according to Beijerse, 1999) pays less attention to information technology and more attention to the strategic, personal, organisational and cultural aspects of KM and thus defined KM as
‘‘arranging and managing the operational processes in the knowledge value chain in such a way that realizing the collective ambition, the targets and the strategy of the organization is being promoted’’.
Beijerse (1997) put more emphasis on the importance of tacit knowledge, seeing this as added value, and having the earlier definition of ‘knowledge’ and ‘management’ in mind, defined KM as
‘‘achieving organizational goals through the strategy-driven motivation and facilitation of (knowledge-) workers to develop, enhance and use their capability to interpret data and information (by using available sources of information, experience, skills, culture, character, personality, feelings, etc.) through a process of giving meaning to these data and information.’’
In explaining this definition of KM, Beijerse (1999) put the giving of meaning to data and information to create knowledge as the core of the KM process. Beijerse (1999) also agreed with Nonaka and Takeuchi (1995), and Van der Spek and Spijkervet (1996) that knowledge is a vibrant human process in which truth is created; and with the implied conclusion that there is no such thing as one truth or one possibility of knowing the truth. According to Beijerse (1999), knowledge should be judged on its true merit and what is knowledge for one organisation could be worthless data for another.
Beijerse (2000) goes ahead to identify nine possible knowledge streams in KM which essential for business leaders to think about in using knowledge to achieve organisational goals. These are determination of necessary knowledge, determination of available knowledge, determination of knowledge gap, knowledge development, knowledge acquisition, knowledge lock (changing developed or purchased knowledge into a systematic or structural form made available to everyone), knowledge sharing, knowledge utilization and knowledge evaluation. As noted by Beijerse (2000) the output from knowledge evaluation process forms an input into the process of identifying knowledge gap, thus the whole KM process becomes cyclical.
Another major view of what KM should be was presented by Malhotra (2000), who presented a new perspective on how organisations should view knowledge management. This is necessitated by transition in the last quarter of the twentieth century from Information technology as a lever of competitive advantage to information being viewed as a ‘utility’ and more recently the ‘e-everything phenomena’ where the Internet and electronic commerce have become key factors in business and IT strategy. According to Malhotra (2000), there has been a paradigm shift from Total Quality Management (TQM) – focusing on continuous improvement in existing business processes – to Business Process Reengineering (BPR) which emphasized IT intensive radical redesign of business process. However, according to Malhotra (2000), BPR could not measure up to the Networked paradigm enabled by the Internet and WWW as its focus was on co-ordination of companies internal function and it scope could not cover information flows with an organisation’s customers and supplier whose roles were becoming increasingly more important.
Malhotra (2000) further stated that given the unpredictable nature of the new era there was need for new paradigm shift from transformation at the level of business processes to a radical rethinking of the overall business model as well as information flows between organisations and industries. Organisations’ survival will depend on their ability to continuously adapt the programmed logic supporting their business models and business process to the continual dynamic and radical changes in the business environment. Bearing this argument in mind Malhotra (2000) came up with the following definition of KM,
‘‘Knowledge management caters to the critical issues of organizational adaptation, survival, and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information-processing capacity of information technologies, and the creative and innovative capacity of human beings.’’
According to Malhotra (2000), this definition is predicated on the need to have a synergy between the capabilities of advanced technologies and human creativity and innovation to realize the agility demanded by emerging business environment.
Conclusions
From the definitions given above KM can be described as a process by which organizations strategize to achieve their goals through the creation, dissemination and application of the relevant knowledge. This is achieved by motivating and inspiring the members of the organization to continue to exploit their human innovative capabilities to develop new ways of achieving the goals of the organization or develop new goals (business model rethinking) for the organization given the constant and dynamic changes in the operating environment. The process of knowledge creation, dissemination and application is actively supported by the use of emerging advanced information systems to enhance knowledge sharing within the organization and with other external stakeholders.
The concepts described in this article can be - and are being applied (albeit unconsciously) - to influence management practice relating to the management of knowledge within organizations. The paper by Malhotra (2000) offers a fundamentally new perspective to KM by suggesting that organizations must be prepared to continuously rethink their business models (not just business processes) to survive in today’s Internet age given the increased awareness by all stakeholders, especially customers and suppliers and the unpredictable changes occurring in the business environment. To do this, Knowledge workers must be encouraged and motivated to innovate and come up with new products and services to meet the ever changing and increasing demands of customers.
Organizations need to create a learning environment to ensure that its members are well informed, understand, and share the need for a radical rethinking of the business models. This argument was supported by real –life organizations like Royal Dutch Shell where the strategy session focused on differences in the perception of different managers to enable an understanding of the multiple world views of the future. Another example is dynamic pricing models and comparison-shopping agents such as mySimon who take dynamically changing market prices into consideration.
References
Beijerse, R.P (1999), ‘‘Questions in knowledge management: defining and conceptualizing a phenomenon.’’. Journal of Knowledge Management. Vol. 3 No. 2 pp 94 – 109
Beijerse, R.P (2000), ‘‘Knowledge management in small and medium sized companies: knowledge management for entrepreneurs.’’ Journal of knowledge management, Vol. 4 No. 2 pp 162 – 179.
Chaba, A, 2008, ‘‘data, information and knowledge’’, Knowledge Management Blog available at http://abouyounesmdx.blogspot.com accessed on March 3, 2008.
Kock, N.F, McQueen, R.J. and Corner, J.L. (1997), ‘‘the nature of data, information and knowledge exchanges in business processes: implications for process improvement and organizational learning’’, The Learning organization, Vol. 3, No. 2, pp.70-80
Kock, N.F, McQueen, R.J. and Baker, M. (1996), ‘‘Learning and Process improvement in knowledge organisations: a critical analysis of four contemporary myths’’. The learning organisation, Vol.3, No.1, pp.31-41.
Malhotra, Y (2000), ‘‘Knowledge management for E-business performance: advancing information strategy to internet time’’ Information Strategy, the executives journal, Vol 16, No 4 pp 5 – 16 available at http://www.brint.com/members/online/200503/kmebiz.pdf
Stenmark, D. (2002), ‘‘Information Vs Knowledge: The role of Intranets in Knowledge Management’’. In proceedings of HICSS 35, IEEE Press, Hawai, January 7-10, 2002.
As noted by Malhotra (2000), despite the lack of ‘‘commonly agreed upon definition of knowledge management’’ organisations both in the public and private sectors are getting increasingly interested in the topic. This paper reviews a sample of definitions of Knowledge Management (KM) that have been proposed by various scholars who have conducted research on this emerging subject. To do this, various definitions of ‘knowledge’, especially in relation to ‘information’ and ‘data’ will be discussed to enable a holistic view of the concept of KM. At the end of this paper, an attempt will be made to describe knowledge management by combining elements of the various definitions that will be discussed.
Knowledge, Information and Data.
The distinction between Knowledge, information and data has always been a subject of much interest in the academia due to the lines that exist between the definitions of each word, especially between knowledge and information. Chaba (2008), suggests a distinction by giving an example where ‘£150’ is just data, ‘£150 pounds on gas bill’ is information, and ‘If I have £150, I have got enough money to pay my Gas Bill’ is knowledge. This example seems to suggest that ‘information’ is ‘data’ with some meaning, and knowledge is a combination of some information and a context. Implicit in this example is the ‘knowledge’ that having £150 pounds means that the gas bill can be paid, that is having £150 and knowing that this amount can pay the gas bill.
The distinction provided by the example given above is similar to that given by Kock Jr et al (1996), where its was suggested that although Knowledge, Information and Data are not synonymous, they are interrelated and have no useful existence without each other. To compare the three words within an organisational context, Kock Jr et al (1996) gave an example of a situation where a division manager interprets data (e.g. Productivity figures) in a context (e.g. in a meeting with a manager in one of the division’s plant), as information (e.g. the productivity figures are low). This information is then combined with knowledge (e.g. if we have a new lathe in operation the production will go up), within a domain (e.g. the plant’s assembly line), to produce effective action (e.g. introduce a new lathe into the plant’s assembly line). Another useful distinction made by Kock Jr et al (1997) is that while ‘information’ is descriptive – relating to the past and the present - , ‘knowledge’ is mostly predictive as it provides the basis for predicting the future, with a degree of certainty, using information about the past and the present.
According to Stenmark (2002), Figure 1 below is commonly used to describe the relationship between these terms but the arguments are flawed as they are based on wrong assumptions that the relationship between data, information and knowledge is linear, asymmetric (data is transformed into information, and information is transformed into knowledge), and that knowledge is superior to information and information is superior to data.
Fig 1 Data, Information and Knowledge
Source: Stenmark (2002)
Toumi 1999 (cited in Stenmark 2002) , challenged this view by suggesting that ‘knowledge’ embedded in the human mind can be instantiated to form explicit ‘information’ which can subsequently be coded into pure data which has the highest value from an IS/IT perspective; and since computers can only effectively process data, it should be on top of the value hierarchy.
Stenmark (2002) however argues that both arguments presented above are erroneous and that data, information and knowledge are interwoven in more complex ways because they influence each other and the value of any of them is dependent on the purpose for which it is being used. ‘Data’ and ‘information’ requires ‘knowledge’ to be interpretable and likewise, new ‘knowledge’ is constructed using existing ‘data’ and ‘information’. In the words of Stenmark (2002), ‘‘since a piece of text itself is not sufficient to exhaustively describe the knowledge to which it refers, the reader's tacit knowledge must be compatible with that of the writer in order to interpret and fully comprehend the implications of the information. Hence, what one conceives as information another sees as data’’
In essence the relationship between ‘data’, ‘information’ and ‘knowledge’ is very complicated and to understand any one of them, there must be a context and a purpose. What is regarded as mere ‘data’ may be seen as ‘information’ by another person or even by the same person in a different context or situation. From the arguments put forward so far in this paper, ‘knowledge’ can thus be likened to an understanding or cognition of a specific domain area or subject exhibited by an individual as a result of his experience or just gut feeling; can either be expressed in form of information or data or which the individual may not be able to make explicit; and which can enable effective action. Having put ‘knowledge’ in a proper perspective in relation to ‘data’ and ‘information’, this paper progresses with an analysis of various definitions of ‘Knowledge’ and Knowledge Management (KM).
Knowledge Management (KM) Definitions
Beijerse (2000), defined knowledge as follows;
‘‘knowledge is seen here as information; the capability to interpret data and information through a process of giving meaning to these data and information; and an attitude aimed at wanting to do so’’.
This definition is based on other definitions where knowledge is seen as ‘something more than information’. As suggested by Beijerse (1999), a popular distinction - first made by Michael Polanyi – is that made between tacit and explicit knowledge. Polanyi (1966), cited in Beijerse (1999), stated that because people acquire knowledge by active (re)creation and organisation of their own experience, tacit or personal knowledge is crucial to human cognition and knowledge that can be expressed in words and numbers is just a tip of the iceberg. Implicit in this definition is the distinction between tacit and explicit knowledge which complement and influence each other in the creative actions of people.
KM, Beijerse (1999) also came up with a derived definition of managements as follows;
‘‘Management is the strategy-driven motivation and facilitation of people, aimed at reaching the organizational goals’’
This definition according to Beijerse (1999) is predicated on the central elements of management including the formulation of a strategy, ensuring that the strategy is realized, organization as a tool fulfilling the first two elements and the people who manage and are managed within the organisation.
Looking at the two definitions above, Beijerse (1999) suggests that KM is more specific than management in that while management is about motivating and stimulating people to achieve specified goals, KM focuses more on one aspect of people – their knowledge.
Different authors have defined KM in different ways. Some focus on reference to KM as the process of managing organisations’ intangible assets. An example of these is Sveiby (cited by Beijerse, 1999), who defined KM as ‘‘the art of creating value from an organization's intangible assets’’. Den Hertog and Huizinga, (1997), as cited by Beijerse (1999), placed emphasis on the choice organisations make regarding their core competencies referred to as ‘knowledge ambition’ and thus defined KM as ‘‘using instruments to realize the knowledge ambition’’. Beijerse (1999) also cited the work of Mathieu Weggeman (1997) who focused on the ‘knowledge value chain involving four successive constituent processes. These are first, determination of the strategic need for knowledge; second, determination of the knowledge gap which is quantitative and qualitative difference between needed and available knowledge in the organisation; third, narrowing of the knowledge gap by developing knowledge, buying knowledge, improving on existing knowledge, or getting rid of outdated or irrelevant knowledge; and fourth, dissemination and application of available knowledge to serve the interest of customers and other stakeholders. Weggeman (1997), (according to Beijerse, 1999) pays less attention to information technology and more attention to the strategic, personal, organisational and cultural aspects of KM and thus defined KM as
‘‘arranging and managing the operational processes in the knowledge value chain in such a way that realizing the collective ambition, the targets and the strategy of the organization is being promoted’’.
Beijerse (1997) put more emphasis on the importance of tacit knowledge, seeing this as added value, and having the earlier definition of ‘knowledge’ and ‘management’ in mind, defined KM as
‘‘achieving organizational goals through the strategy-driven motivation and facilitation of (knowledge-) workers to develop, enhance and use their capability to interpret data and information (by using available sources of information, experience, skills, culture, character, personality, feelings, etc.) through a process of giving meaning to these data and information.’’
In explaining this definition of KM, Beijerse (1999) put the giving of meaning to data and information to create knowledge as the core of the KM process. Beijerse (1999) also agreed with Nonaka and Takeuchi (1995), and Van der Spek and Spijkervet (1996) that knowledge is a vibrant human process in which truth is created; and with the implied conclusion that there is no such thing as one truth or one possibility of knowing the truth. According to Beijerse (1999), knowledge should be judged on its true merit and what is knowledge for one organisation could be worthless data for another.
Beijerse (2000) goes ahead to identify nine possible knowledge streams in KM which essential for business leaders to think about in using knowledge to achieve organisational goals. These are determination of necessary knowledge, determination of available knowledge, determination of knowledge gap, knowledge development, knowledge acquisition, knowledge lock (changing developed or purchased knowledge into a systematic or structural form made available to everyone), knowledge sharing, knowledge utilization and knowledge evaluation. As noted by Beijerse (2000) the output from knowledge evaluation process forms an input into the process of identifying knowledge gap, thus the whole KM process becomes cyclical.
Another major view of what KM should be was presented by Malhotra (2000), who presented a new perspective on how organisations should view knowledge management. This is necessitated by transition in the last quarter of the twentieth century from Information technology as a lever of competitive advantage to information being viewed as a ‘utility’ and more recently the ‘e-everything phenomena’ where the Internet and electronic commerce have become key factors in business and IT strategy. According to Malhotra (2000), there has been a paradigm shift from Total Quality Management (TQM) – focusing on continuous improvement in existing business processes – to Business Process Reengineering (BPR) which emphasized IT intensive radical redesign of business process. However, according to Malhotra (2000), BPR could not measure up to the Networked paradigm enabled by the Internet and WWW as its focus was on co-ordination of companies internal function and it scope could not cover information flows with an organisation’s customers and supplier whose roles were becoming increasingly more important.
Malhotra (2000) further stated that given the unpredictable nature of the new era there was need for new paradigm shift from transformation at the level of business processes to a radical rethinking of the overall business model as well as information flows between organisations and industries. Organisations’ survival will depend on their ability to continuously adapt the programmed logic supporting their business models and business process to the continual dynamic and radical changes in the business environment. Bearing this argument in mind Malhotra (2000) came up with the following definition of KM,
‘‘Knowledge management caters to the critical issues of organizational adaptation, survival, and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information-processing capacity of information technologies, and the creative and innovative capacity of human beings.’’
According to Malhotra (2000), this definition is predicated on the need to have a synergy between the capabilities of advanced technologies and human creativity and innovation to realize the agility demanded by emerging business environment.
Conclusions
From the definitions given above KM can be described as a process by which organizations strategize to achieve their goals through the creation, dissemination and application of the relevant knowledge. This is achieved by motivating and inspiring the members of the organization to continue to exploit their human innovative capabilities to develop new ways of achieving the goals of the organization or develop new goals (business model rethinking) for the organization given the constant and dynamic changes in the operating environment. The process of knowledge creation, dissemination and application is actively supported by the use of emerging advanced information systems to enhance knowledge sharing within the organization and with other external stakeholders.
The concepts described in this article can be - and are being applied (albeit unconsciously) - to influence management practice relating to the management of knowledge within organizations. The paper by Malhotra (2000) offers a fundamentally new perspective to KM by suggesting that organizations must be prepared to continuously rethink their business models (not just business processes) to survive in today’s Internet age given the increased awareness by all stakeholders, especially customers and suppliers and the unpredictable changes occurring in the business environment. To do this, Knowledge workers must be encouraged and motivated to innovate and come up with new products and services to meet the ever changing and increasing demands of customers.
Organizations need to create a learning environment to ensure that its members are well informed, understand, and share the need for a radical rethinking of the business models. This argument was supported by real –life organizations like Royal Dutch Shell where the strategy session focused on differences in the perception of different managers to enable an understanding of the multiple world views of the future. Another example is dynamic pricing models and comparison-shopping agents such as mySimon who take dynamically changing market prices into consideration.
References
Beijerse, R.P (1999), ‘‘Questions in knowledge management: defining and conceptualizing a phenomenon.’’. Journal of Knowledge Management. Vol. 3 No. 2 pp 94 – 109
Beijerse, R.P (2000), ‘‘Knowledge management in small and medium sized companies: knowledge management for entrepreneurs.’’ Journal of knowledge management, Vol. 4 No. 2 pp 162 – 179.
Chaba, A, 2008, ‘‘data, information and knowledge’’, Knowledge Management Blog available at http://abouyounesmdx.blogspot.com accessed on March 3, 2008.
Kock, N.F, McQueen, R.J. and Corner, J.L. (1997), ‘‘the nature of data, information and knowledge exchanges in business processes: implications for process improvement and organizational learning’’, The Learning organization, Vol. 3, No. 2, pp.70-80
Kock, N.F, McQueen, R.J. and Baker, M. (1996), ‘‘Learning and Process improvement in knowledge organisations: a critical analysis of four contemporary myths’’. The learning organisation, Vol.3, No.1, pp.31-41.
Malhotra, Y (2000), ‘‘Knowledge management for E-business performance: advancing information strategy to internet time’’ Information Strategy, the executives journal, Vol 16, No 4 pp 5 – 16 available at http://www.brint.com/members/online/200503/kmebiz.pdf
Stenmark, D. (2002), ‘‘Information Vs Knowledge: The role of Intranets in Knowledge Management’’. In proceedings of HICSS 35, IEEE Press, Hawai, January 7-10, 2002.
Thursday, 31 January 2008
Article on Knowledge Management Models
This article presents the writer’s commentary on the subject of Knowledge Management and the models that have been proposed for adoption by organisations to effectively manage knowledge. According to Earl (2001), the concepts and practices of knowledge management evolved in the 1990s as business managers in the post industrial era began to realize that knowledge was ‘the’ critical resource in improving business performance and their organisations have been poor at managing it. Consequently, Knowledge Management (KM) started to emerge as an area of interest both within organisations as well as in the academia giving rise to the development of a variety of KM models and approaches to managing knowledge by different scholars. McAdam and McCreedy (1999) suggested that there are unresolved issues relating to the emergence, definition, classification, and emancipatory elements of KM which has far reaching implications in choosing approaches to identify and distribute knowledge within organisations. Others have also attempted to classify and criticise models and approaches to KM with the effect that there is so much confusion surrounding the concept and so many questions remain unanswered. Knowledge Management Models
In providing a critique of KM models, McAdam and McCreedy (1999) concluded that all models must be treated with caution as ‘‘they are only useful so long as they are critiqued to understand the underlying assumptions in the representation, rather than accepting them as objective representations of reality’’. This point buttresses the fact in adopting any model, organisations must understand the background assumptions of such with a view to matching it to its own peculiar circumstance or situation. McAdam and McCreedy (1999) categorised KM models into knowledge category models, intellectual capital models and social constructed models.
According to McAdam and McCreedy (1999), knowledge category models classify knowledge into discrete elements. An example is Nonaka’s Model which considers KM as a knowledge creation process. Nonaka (1991) suggested that Managers of highly successful Japanese corporations have become famous for innovation and creation of new products and markets because of their ability to effectively manage the creation of new Knowledge. According to Nonaka (1991), the main point of the Japanese approach is the understanding that new knowledge creation depends on how an organisation taps the tacit and often subjective insights, intuitions and gut feeling of individual employees and making these available for use by the whole organisation. Furthermore, as suggested by Nonaka (1991), the main drivers of this process is personal commitment and employees’ sense of identity with the enterprise and its mission. According to McAdam and McCreedy (1999), Nonaka, model assumes tacit knowledge can be transferred into tacit knowledge in other through socialisation; tacit knowledge can be turned to explicit through externalisation; the process of internalisation can turn explicit knowledge to tacit knowledge in people; and explicit knowledge can be turned to more explicit knowledge through combination.
McAdam and McCreedy (1999) mentioned Boisot’s Model under the Knowledge category models where knowledge is considered as either codified or uncodified and also as diffused or undiffussed within an organisation. Under this model codified and undiffused knowledge is referred to as proprietary; uncodified and undiffused knowledge is referred to as personal knowledge; codified and diffused knowledge is called public knowledge; and diffused but uncodified knowledge is referred to as common sense. Finally McAdam and McCreedy (1999) concluded that knowledge categories models focus on knowledge transformation through socialisation and suggests that categorisation of knowledge in these models are mechanistic.
McAdam and McCreedy (1999) cited the Skandia IC model under the intellectual capital models category. This model is predicated on the assumption that knowledge can be broken down into human, customer process and growth elements contained in two categories of human capital and organisational capital. The model adopts a very scientific approach where knowledge is treated and managed as intangible assets assuming that KM can be decomposed into objective elements rather than being social or political in nature. McAdam and McCreedy (1999) concluded that intellectual capital models – in assuming that knowledge can be treated as an asset - are mechanistic in nature and can result in simplistic approaches to complex social related issues.
Socially constructed models of KM assume a wide definition of knowledge and it is seen as being inherently linked with social and learning processes within the organisation according to McAdam and McCreedy (1999). These models are similar to those models representing the learning organisation and organisational learning. McAdam and McCreedy (1999) cited Demerest’s (1997) adaptation of Clark and Staunton’s (1989) model which stresses that knowledge creation is not merely scientific but includes social construction of knowledge and that constructed knowledge is embodied not just through explicit programs but through a process of social interchange. This is followed by dissemination of adopted knowledge throughout the organisation and its environs and knowledge is eventually seen as being of economic use in terms of organisational outputs. According to McAdam and McCreedy (1999), this model is similar to others that talk about knowledge acquisition, problem solving, dissemination ownership and storage (Jordan and Jones, 1997); knowledge policy, infrastructure and culture (Kruizinga et al 1997); and strategic knowledge, structural and cultural knowledge, systems knowledge, and community of practice and routines (Scarborough, 1996).
Finally McAdam and McCreedy (1999) concluded by suggesting a model – based on socially constructed models - which takes a balanced approach between scientific and socially constructed knowledge; views the use of KM as both emancipatory and business oriented; and where knowledge flows are recursive rather than sequential.
Another perspective on Knowledge management is that provided by Earl (2001) which focuses on suggesting taxonomy for KM strategies. Earl (2001) identified 7 schools of knowledge management which were categorised under 3 headings as follows,
Technocratic Schools
System School – where knowledge is captured via databases and others can use them by applying judgement. Here the knowledge captured is domain specific and as it captures knowledge by domain experts which is used by other experts. Key success factors here include validation of codified knowledge through peer review and incentives and rewards for contributors. Examples include Web-based knowledge systems used by Xerox and Airbus for maintenance of printing equipment and aircrafts respectively.
Cartographic school – where organisational knowledge is mapped by linking people and knowledge (Yellow pages) . Directories are signposts or gateways to knowledge rather than repositories and they lead knowledge seekers to knowledge providers. People connectivity is supported by IT tools like Intranets or special directory applications
Process School – which is an outgrowth of BPR and is based on the ideas that; business processes can be enhanced by providing personnel with task-specific knowledge; and that management processes are more knowledge intensive than business processes meaning that contextual and best practice knowledge are important. The success factor is the use of technology to provide information executives and operating staff.
Economic school
Commercial School – which is based on commercial exploitation and protection of knowledge assets (intellectual property) such as patents, copyrights or trademarks. Dow Chemicals is an example of where knowledge is treated as an asset or commodity. The approach requires dedicated and special teams developing techniques to manage intellectual property as a routine.
Behavioural Schools
Organisational School - involving the use of communities to facilitate knowledge creation and exchange. These communities can be Inter or Intra organisational and are often interdisciplinary. In all cases there is an informal element to community life such as face-to-face exchange and events and organisations sometimes use technology to support communities. Examples are in BP and Shell Corporations.
Spatial School - involving the use of space or spatial design to facilitate knowledge creation and sharing. Examples are metaphors like Water coolers as a meeting place, open style coffee bars or kitchen as knowledge café, and open plan office as a knowledge building. It involves the use of co-presence and socialism as a means of knowledge creation and exchange. In other words, the approach facilitates the creation of social capital by offering sociable spaces. An example is the BA head office at Waterside near Heathrow and Skandia’s Future Centre in Stockholm.
Strategic School – where KM is seen as a dimension of competitive strategy. Examples include Skandia which has declared intellectual capital as the company’s core capability; and Buckman laboratories. The aim is to build nurture and truly exploit knowledge assets through a variety of means. Action that follows from this can encompass measures that come under the other schools.
According to Earl (2001), this taxonomy can help firms to select a knowledge management strategy based on the main themes, objects (units of intervention) and success factors. In this wise, the identification and analysis of performance gaps (productivity, quality and innovation) can be instrumental to select the KM approach with the highest pay-off at a given point in time.
Conclusion
As concluded by McAdam and McCreedy (1999) their suggested model could act as a guide for further research in the area of knowledge management. Looking at the critique of KM models presented above, it can be said that the work of McAdam and McCreedy (1999) is a relevant piece from which an understanding of the assumptions behind these models can be developed to assist an organisation in adopting an approach to managing knowledge. In the same vein, organisations can also use the taxonomy suggested by Earl (2001) to decide on the best approach to KM based on their organisational goals and available resources.
As stated earlier models just present high level representation of a concept like KM, but organisations are at liberty to either adopt a model in its entirety or develop an ‘hybrid’ which include elements of several models depending on their peculiar environment, circumstances or situation. This would inform the specific method or approach to be adopted in exploiting organisational knowledge to achieve organisational goals. An important learning point in this discourse is that KM should not merely be seen as only scientific or mechanistic process but the social or cultural aspects must also be emphasized since most knowledge is derived from the mental ability of people, and humans are generally social animals.
REFERENCES
Earl, M. (2001), ‘‘Knowledge Management Strategies: Towards a Taxonomy’’, Journal of Management Information Systems. Vol. 8, No. 1, pp. 215-233
McAdam, R and McCreedy, S. (1999), ‘‘A critical review of knowledge management models’’, The Learning Organisation. Vol. 3, No. 3, pp. 91-100.
As stated earlier models just present high level representation of a concept like KM, but organisations are at liberty to either adopt a model in its entirety or develop an ‘hybrid’ which include elements of several models depending on their peculiar environment, circumstances or situation. This would inform the specific method or approach to be adopted in exploiting organisational knowledge to achieve organisational goals. An important learning point in this discourse is that KM should not merely be seen as only scientific or mechanistic process but the social or cultural aspects must also be emphasized since most knowledge is derived from the mental ability of people, and humans are generally social animals.
REFERENCES
Earl, M. (2001), ‘‘Knowledge Management Strategies: Towards a Taxonomy’’, Journal of Management Information Systems. Vol. 8, No. 1, pp. 215-233
McAdam, R and McCreedy, S. (1999), ‘‘A critical review of knowledge management models’’, The Learning Organisation. Vol. 3, No. 3, pp. 91-100.
Nonaka, I (1991), ‘‘the Knowledge-Creating Company’’, Harvard Business Review. July-August 2007.
Sunday, 20 January 2008
Welcome to Knowledge Management Strategies
Hello all,
The objective of this blog is to learn about knowledge management which is somewhat a new fad amongst organisations who recognise that knowledge is power and wish to learn more about and managing internal and external; and tacit and explicit knowledge
Knowledge is a critical success factor in gaining competitive advantage and those organisations that are efficient and effective at using it will get to and remain at the top of their Game.
You are welcome to post articles and make comments about articles posted on this blog.
Please do not hesitate to share your knowledge on how organisations have embraced and successfully deployed Knowledge management strategies.
Welcome to Knowledge!
The objective of this blog is to learn about knowledge management which is somewhat a new fad amongst organisations who recognise that knowledge is power and wish to learn more about and managing internal and external; and tacit and explicit knowledge
Knowledge is a critical success factor in gaining competitive advantage and those organisations that are efficient and effective at using it will get to and remain at the top of their Game.
You are welcome to post articles and make comments about articles posted on this blog.
Please do not hesitate to share your knowledge on how organisations have embraced and successfully deployed Knowledge management strategies.
Welcome to Knowledge!
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