
Knowledge Management
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Content
- Cover
- Half-Title Page
- Title Page
- Copyright Page
- Contents
- Preface
- PART 1. Theoretical Elements
- 1. A Knowledge Value Chain
- 1.1. Introduction
- 1.2. Different KVCs
- 1.3. The DIKW model
- 1.4. KVC and management
- 1.5. Transformation processes in the KVC
- 1.6. Practical application
- 1.7. Conclusion
- 2. The Knowledge Capital of a Company
- 2.1. Introduction
- 2.1.1. The accumulation of knowledge
- 2.1.2. The company as knowledge producer
- 2.2. Modeling a company as a knowledge producer
- 2.2.1. Systemic modeling
- 2.2.2. The "black box" model
- 2.2.3. The "division of labor" model
- 2.2.4. The informational model
- 2.2.5. The knowledge capital model
- 2.2.6. The knowledge capital and knowledge actors model
- 2.2.7. Integration of customer knowledge and external knowledge into the AIK model
- 2.3. The operators of the AIK model
- 2.3.1. The Wenger operator
- 2.3.2. The Nonaka operators
- 2.3.3. Integration of the Nonaka theory into the AIK model
- 2.4. Tacit/explicit knowledge and knowledge communities
- 2.5. Mapping as a modeling tool to steer the AIK system
- 2.6. Practical application
- 2.7. Conclusion
- 3. The Structure of Knowledge
- 3.1. Introduction
- 3.2. The semiotic triangle of knowledge
- 3.3. The systemic triangle of knowledge
- 3.4. The knowledge macroscope
- 3.4.1. Knowledge and information
- 3.4.2. Knowledge and meaning
- 3.4.3. Knowledge and context
- 3.5. Practical application
- 3.6. Conclusion
- 4. Shannon's Theory of Knowledge
- 4.1. Introduction
- 4.2. Some definitions and notations
- 4.2.1. The basic unit of knowledge
- 4.2.2. Measuring knowledge
- 4.2.3. Quantity of knowledge in a corpus
- 4.3. Measurement of the quantity of information in a corpus
- 4.4. Measurement of the quantity of meaning in a corpus
- 4.4.1. Definitions and notations
- 4.4.2. Quantitative characterization of semantic graphs: Gurevich entropy
- 4.5. Measurement of usage context in a corpus
- 4.5.1. Introduction
- 4.5.2. Social networks
- 4.5.3. Hierarchical small-world networks
- 4.5.4. Scale-free networks
- 4.5.5. Quantitative characterization of the usage graph of a corpus
- 4.6. Practical application
- 4.7. Conclusion
- PART 2. Practical Elements
- 5. A New Approach to KM
- 5.1 Introduction
- 5.2. Two examples of KM standardization
- 5.2.1. KM and international standardization
- 5.2.2. KM in the nuclear domain
- 5.3. The French Knowledge Management Club
- 5.4. Conclusion
- 6. A Framework for Knowledge-based KM
- 6.1. Introduction
- 6.2. The Daisy Model
- 6.3. Building a KM process framework
- 6.4. Conclusion
- 7. KM: From Strategy to Implementation
- 7.1. Introduction
- 7.2. Framing a KM project
- 7.2.1. The objectives
- 7.2.2. Responsibilities and roles
- 7.2.3. Resources
- 7.2.4. Internal communication
- 7.2.5. Connections between KM and other company issues
- 7.2.6. Other subjects of interest to consider
- 7.3. Implementing the KM project
- 7.4. Monitoring the KM system
- 7.5. Conclusion
- 8. Analyzing Knowledge Capitaland Elaborating a KM Plan
- 8.1. Introduction
- 8.2. Tools for analyzing knowledge capital
- 8.2.1. Maps
- 8.2.2. The knowledge criticality analysis grid
- 8.3. The knowledge capital analysis process
- 8.3.1. Step 1: analyzing critical capacities
- 8.3.2. Step 2: analyzing critical knowledge
- 8.3.3. Step3: strategic alignment
- 8.3.4. Step 4: elaborating a KM plan
- 8.4. Conclusion
- 9. Implementing the KM Plan
- 9.1. Introduction
- 9.2. Knowledge organization
- 9.2.1. Tangible resources (explicit knowledge)
- 9.2.2. Intagible resources (tacit knowledge)
- 9.2.3. New knowledge resource additions
- 9.3. Knowledge codification
- 9.3.1. Lessons learned
- 9.3.2. Knowledge-based documents
- 9.3.3. Knowledge books
- 9.4. Knowledge sharing
- 9.4.1. Knowledge communities or communities of practice
- 9.4.2. Knowledge transfer
- 9.5. Knowledge search
- 9.5.1. Knowledge search and information retrieval
- 9.5.2. The knowledge search process
- 9.5.3. The challenge of KM in knowledge search
- 9.6. Knowledge creation
- 9.6.1. Knowledge creation na innovation
- 9.6.2. Knowledge-based innovation
- 9.6.3. Evaluating the maturity of the innovation process
- 9.7. Conclusion
- Bibliography
- Index
- Other titles from iSTE in Innovation, Entrepreneurship and Management
- EULA
1
A Knowledge Value Chain
1.1. Introduction
This chapter introduces the notion of knowledge through the concept of a value chain.
Its purpose is to clarify the relationships between the concepts of data, information, knowledge and skill, by relying on the abundant literature that has been written on these subjects. All of these concepts, which are rarely formalized and often conflated, are related and dependent, and they need to be better defined. In this chapter, this clarification results in a guidance tool to help managers understand the added value produced by knowledge and act to develop this resource.
In the "knowledge economy" [FOR 09], knowledge is viewed as a resource that is a key factor in success and the basis for a company's competitive advantage. The objective of knowledge management (KM) is to optimize this new resource. It is therefore important to analyze the added value that KM can bring to a company. This is a difficult problem to address. For example, cost/benefit analyses for KM have never really been completed successfully. The approach proposed here is not based on the unpromising cost analysis, but on the value analysis. It is based on the nature of knowledge and its use in a company. We will see that knowledge is the result of closed-loop, continuous and simultaneous transformations within a company. We can, however, distinguish several formal transformation steps that are known as the knowledge value chain (KVC) [ERM 12]. This value chain is conceptual and does not presume any complexity in its implementation within a company. It is very useful for managers to locate potential sources of value of KM. The objective of the KVC is to provide an analysis and action framework that will make it possible to act on this value chain and thereby improve the company's performance.
1.2. Different KVCs
The value chain is a management concept that was developed and popularized by Michael Porter [POR 85]. A value chain is a chain of production activities in a company, from the input to the end user. The products or services pass successively through all of the activities in the chain and, with each step, the products and services acquire value. A value chain is a breakdown of a company's approach into activities that produce value. These components are the basic elements on which a company relies to create a product or provide a valuable service for their customers. The activity chain confers more added value to the products or services than the sum of the values added by each activity.
Identifying the value generated through this chain is the approach chosen by top management. The differences between the value chains of competitors are the key factors of competitiveness. In terms of competitiveness, the value is what customers are willing to pay for what the company provides them. A company is profitable if the value that it generates is greater than the costs to create the product or the service. Creating such a value is the goal of all competitive strategy. The value, instead of the cost, must be used to analyze competitive standing. The value chain characterizes the generic activities that add value to a company: the "primary activities" including logistics, production, marketing and sales and services; and the "secondary activities" including infrastructure, human resources management, R&D and supply. The vectors of cost and value are identified for each activity.
Classic value chains do not include knowledge, although it is now seen as a company's most important strategic resource [DAV 98, DRU 93, HAL 93, STA 92]. The value incorporated in products or services is essentially due to the development of resources derived from organizational knowledge [QUI 92]. In fact, a company's ability to produce can be considered to be the integration and application of specialized knowledge collectively generated by the individuals in the company [GRA 91].
Consequently, the notion of value is not directed by the customer, as in Porter's chain, but by the incorporation of knowledge in products or services in the company's production process. This raises the question of defining more precisely what this "cognitive resource" is and how it is incorporated into the activity of a company. The goal of KM is to manage this resource integration in the company's process. KM is a fairly new perspective on companies. Its philosophy, which must still be strengthened of course, is that a company produces value for its customers when it best manages the incorporation of its cognitive resources in its products and services. Thus, very simply, KM supposes that the production of knowledge implies the production of value. KM is interested in knowledge as a strategic resource that optimizes the production processes of a company.
To support the success of KM, it is useful to analyze the chain of knowledge integration in a company in order to identify and manage the different fundamental stages of enrichment for this cognitive resource and its incorporation into company activities. This is the KVC, viewed from a global point of view in a company.
The definition of a KVC based on a financial analysis of performance is problematic [CHO 00, MPH 94]. The competence-based view business theory offers an alternative approach. This theory considers the company as a portfolio of competences. Its competitiveness is based on the creation and development of competences and on its realization of a strategy capable of creating a link between goals, resources and objectives [PRA 90]. These competences have a cognitive nature, and this allows managers to identify the basic processes, like knowledge creation and organizational learning [LEO 95, NEL 91, PRA 90]. Carlucci et al. [CAR 04, p. 579] assert that the cognitive perspective of competence can be summarized by the interpretation that defines the competence of a company as a combination of knowledge assets, which make up what is called the company's knowledge capital, and knowledge processes, which allow a company to successfully complete its operational processes. This provides a foundation for the definition of a KVC.
Following the considerable development of KM in the past few years, the concept of the KVC appeared and was recently debated. The authors [CAR 04, EUS 03, HOL 01, LEE 00, WAN 05] define a KVC as a set of KM processes. A KVC is therefore a KM framework organizing the basic KM processes, such as the knowledge process wheel described in Carlucci et al. [CAR 04]. The main processes in these different KVCs are as follows:
- - knowledge creation: this is definitely the most important process, because it creates knowledge capital, the purpose of all knowledge-based companies;
- - knowledge codification: this process concerns the appropriation of tacit knowledge, which is a very complex problem;
- - knowledge sharing: once a knowledge corpus is identified and a knowledge repository is elaborated, sharing this knowledge in a community is not really a standard task. This requires a lot of effort starting from the construction of the appropriate community to the implementation of access infrastructure;
- - knowledge dissemination: access to knowledge for most people concerned ("the right information, the right person, the right time") is the famous problem of the "last kilometer", it involves information and communication infrastructure, and specialized designs of dedicated systems;
- - knowledge portfolio analysis: the company, to implement a KM strategy, must implement a continuous process of analyzing and characterizing its knowledge portfolio: what is its strategic knowledge? What is its available knowledge? What are the risks associated with its knowledge? etc.;
- - knowledge assessment: to carry out effective KM processes, it is necessary to have an evaluation matrix for their performance.
The KVC provides a KM framework to analyze the value added by each KM process. Figure 1.1 shows an example of a KVC (from [WAN 05]), with a series of KM processes in the form of a Porter-like model.
Figure 1.1. An example of a KVC based on KM processes
Figure 1.2. An example of a KVC based on cognitive tasks
Figure 1.2, from Powell [POW 01], proposes another type of KVC, which is a sequence of tasks whereby knowledge workers transform data into decisions and actions to construct the unique competitive advantage of their employer and/or social and environmental benefits. These tasks are intellectual tasks, which we call "cognitive tasks", that successively enrich available information to act in line with the company's objectives. Here, the value chain is not a sequence of KM processes that act on the knowledge capital of the company, but a sequence of cognitive tasks, realized by Knowledge Workers, that initially rely on the available information capital in the company to gradually give it a strategic value resulting in decision and action.
In this chapter, we will develop a KVC based on cognitive tasks. The objective is to use a chain of information transformations, to identify the cognitive tasks associated with each step and to define a transformation sequence whose management makes it possible to add value to the knowledge capital in a manner aligned with the company's strategy.
A well-known transformation chain, partially taken up in [POW 01], exists in the domain of information management. It is the...
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