Knowledge ManagementUnit-11. What is Knowledge?1. A justified true belief2. It is different from data & information3. Knowledge is at the highest level in a hierarchy with information at the middle level, and data to be at the lowest level 4. It is the richest, deepest & most valuable5. Information with direction 6. Knowledge as Objects7. Knowledge as Access to Information8. Knowledge as Capability9. Knowledge as State of Mind2. Types of Knowledge1. Individual, social, causal, conditional, relational and pragmatic2. Embodied, encoded and procedural3. Procedural and Declarative Knowledge4. Tacit and Explicit Knowledge5. General and Specific KnowledgeDeclarative knowledge (substantive knowledge) focuses on beliefs about relationships among variables Procedural knowledge focuses on beliefs relating sequences of steps or actions to desired (or undesired) outcomes Tacit knowledge includes insights, intuitions, and hunches Explicit knowledge refers to knowledge that has been expressed into words and numbersWe can convert explicit knowledge to tacit knowledgeGeneral knowledge is possessed by a large number of individuals and can be transferred easily across individuals Specific knowledge, or idiosyncratic knowledge, is possessed by a very limited number of individuals, and is expensive to transfer Technically and Contextually Specific Knowledge1. Technically specific knowledge is deep knowledge about a specific area2. Contextually specific knowledge refers to the knowledge of particular circumstances of time and place in which work is to be performedKnowledge and Expertise:1. Expertise can be defined as knowledge of higher quality 2. An expert is one who is able to perform a task much better than othersTypes of Expertise1. Associational Expertise 2. Motor Skills Expertise3. Theoretical (Deep) Expertise3. Different kinds of Knowledge:1. Simple knowledge focuses on one basic area 2. Complex knowledge draws upon multiple distinct areas of expertise 3. Support knowledge relates to organizational infrastructure and facilitates day-to-day operations 4. Tactical knowledge pertains to the short-term positioning of the organization relative to its markets, competitors, and suppliers 5. Strategic knowledge pertains to the long-term positioning of the organization in terms of its corporate vision and strategies for achieving that vision

Illustrations of the Different Types of Knowledge

5. What is Knowledge Management? Knowledge management (KM) may simply be defined as doing what is needed to get the most out of knowledge resources. In general, KM focuses on organizing and making available important knowledge, wherever and whenever it is needed. KM is also related to the concept of intellectual capital. 6. Concept of KM:1. Knowledge is first created in the peoples minds. KM practices must first identify ways to encourage and stimulate the ability of employees to develop new knowledge. 2. KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge. 3. KM should not distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization. 7. Definitions of KM1. Knowledge Management is the broad process of locating, organizing, transferring, and using the information and expertise within an organization. 2. The overall knowledge management process is supported by four key enablers: leadership, culture, technology, and measurement.3. Knowledge management is the strategy and processes to enable the creation and flow of relevant knowledge throughout the business to create organizational, customer and consumer value.4. Knowledge management is the process of capturing, developing, sharing, and effectively using organizational knowledge.5. It refers to a multi-disciplined approach to achieving organizational objectives by making the best use of knowledge. 6. Knowledge Management is the broad process of locating, organizing, transferring, and using the information and expertise within an organization. The overall knowledge management process is supported by four key enablers: leadership, culture, technology, and measurement7. Knowledge management is the process of capturing value, knowledge and understanding of corporate information, using IT systems, in order to maintain, re-use and re-deploy that knowledge.8. Knowledge management is a collection of activities, processes and policies, which enable organizations to apply knowledge to improve effectiveness, innovation and quality. 9. Knowledge Management (KM) refers to a multi-disciplined approach to achieving organizational objectives by making the best use of knowledge. KM focuses on processes such as acquiring, creating and sharing knowledge and the cultural and technical foundations that support them.10. Knowledge Management (KM) refers to a multi-disciplined approach to achieving organizational objectives by making the best use of knowledge. KM focuses on processes such as acquiring, creating and sharing knowledge and the cultural and technical foundations that support them.

8. Knowledge Management Systems (KMS): Information technology facilitates sharing as well as accelerated growth of knowledge. Information technology allows the movement of information at increasing speeds and efficiencies. Today, knowledge is accumulating at an ever increasing rate. It is estimated that knowledge is currently doubling every 18 months and, of course, the pace is increasing... Technology facilitates the speed at which knowledge and ideas proliferate Bradley [1996] Knowledge management mechanisms are organizational or structural means used to promote knowledge management. The use of leading-edge information technologies (e.g., Web-based conferencing) to support KM mechanisms enables dramatic improvement in KM. KMS is the synergy between latest technologies and social/structural mechanismsWhat is Data? Data comprises facts, observations, or perceptions Data becomes information when its creator adds meaning. We transform data into information by adding value in various ways: Contextualized: we know for what purpose the data was gathered Categorized: we know the units of analysis or key components of the data Calculated: the data may have been analyzed mathematically or statically Corrected: errors have been removed from the data Condensed: the data may have been summarized in a more concise form Knowledge guides us in the process of analyzing data and utilizing information. Data represents raw numbers or assertionsWhat is Information? Information is processed data Information is a subset of data, only including those data that possess context, relevance and purpose Information involves manipulation of raw data Information has meaning, relevance and purpose. Information is organized with purpose and it can potentially shape the receiver. Knowledge derives from information as information derives from data. This transformation happens through the following processes: Comparison: how does information about the situation compare to other situations we have known? Consequences: what implications does the information have for decisions and actions? Connections: how does this bit of knowledge relate to others? Conversation: what do other people think about this information?9. Knowledge Management Solutions Knowledge management solutions refer to the variety of ways in which KM can be facilitated KM processes KM systems KM mechanisms and technologies KM infrastructure Knowledge Management Processes:Knowledge management systems are the integration of technologies and mechanisms that are developed to support KM processes 1. Knowledge DiscoveryKnowledge discovery may be defined as the development of new tacit or explicit knowledge from data and information or from the synthesis of prior knowledge Combination.

2. Knowledge Capture Knowledge capture is defined as the process of retrieving either explicit or tacit knowledge that resides within people, artifacts, or organizational entities. Knowledge captured might reside outside the organizational boundaries, including consultants, competitors, customers, suppliers, and prior employers of the organizations new employees 3. Externalization and InternalizationExternalization It involves converting tacit knowledge into explicit forms such as words, concepts, visuals, or figurative language. A process of articulating tacit knowledge into explicit concepts A quintessential knowledge-creation process involving the creation of metaphors, concepts, analogies, hypothesis, or models Created through dialogue or collective reflection

Internalization A process of embodying explicit knowledge into tacit knowledge Learning by doing Shared mental models or technical know-how Documents help individual internalize what they experience It is the conversion of explicit knowledge into tacit knowledge. It represents the traditional notion of learning4. Knowledge Sharing Knowledge sharing is the process through which explicit or tacit knowledge is communicated to other individuals Effective Transfer Knowledge is shared and not recommendations based on knowledge It may take place across individuals, groups, departments or organizations

5. Direction & Routines Direction refers to the process through which individuals possessing the knowledge direct the action of another individual without transferring to that person the knowledge underlying the direction Routines involve the utilization of knowledge embedded in procedures, rules, and norms that guide future behavior 10. Knowledge Management Technologies Technologies that support KM include artificial intelligence (AI) technologies encompassing those used for knowledge acquisition and case-based reasoning systems, electronic discussion groups, computer-based simulations, databases, decision support systems, enterprise resource planning systems, expert systems, management information systems, expertise locator systems, videoconferencing, and information repositories encompassing best practices databases and lessons learned systems. Technologies supporting direction include experts knowledge embedded in expert systems and decision support systems, as well as troubleshooting systems based on the use of technologies like case-based reasoning Technologies that facilitate routines are expert systems, enterprise resource planning systems, and traditional management information systems 11. Knowledge Management Mechanisms: Mechanisms facilitating direction include traditional hierarchical relationships in organizations, help desks, and support centers Mechanisms supporting routines include organizational policies, work practices, and standards KM mechanisms are organizational or structural means used to promote KM Examples of KM mechanisms include learning by doing, on-the-job training, learning by observation, and face-to-face meetings KM systems utilize a variety of KM mechanisms and technologies to support the KM processes 1. Knowledge Management Discovery Systems2. Knowledge Management Capture System3. Knowledge Management Sharing System4. Knowledge Application SystemsKnowledge Discovery SystemsKnowledge discovery systems support the process of developing new tacit or explicit knowledge from data and information or from the synthesis of prior knowledge Support two KM sub-processes combination, enabling the discovery of new explicit knowledge socialization, enabling the discovery of new tacit knowledge Knowledge Capture Systems Knowledge capture systems support the process of retrieving either explicit or tacit knowledge that resides within people, artifacts, or organizational entities Technologies can also support knowledge capture systems by facilitating externalization and internalization Knowledge Sharing Systems Knowledge sharing systems support the process through which explicit or implicit knowledge is communicated to other individuals Discussion groups or chat groups facilitate knowledge sharing by enabling individuals to explain their knowledge to the rest of the group Knowledge Application Systems Knowledge application systems support the process through which some individuals utilize knowledge possessed by other individuals without actually acquiring, or learning, that knowledge Mechanisms and technologies support knowledge application systems by facilitating routines and direction.

KM Processes, Mechanisms, and Technologies

12. Knowledge Management Infrastructure3 main forms of infrastructure: Managerial Technical SocialManagerial Infrastructure Managerial support for knowledge workers Formal management processes which are applied Impact strongly on the resourcing, decision-making and innovative practices which are allocated to knowledge management Management can facilitate or hinder knowledge management Managerial Infrastructure (cont'd) Human resource management (HRM) The processes which facilitate effective recruitment, retention, development and nurturing of staff Align individual staff members efforts with the organizational priorities through appropriate practices and strategies HRM operates at all levels within organizations

Technological Infrastructure Technical and information management systems Assist with the recording, transmitting and sharing of information and knowledge Includes library and information services and records management strategiesSocial Infrastructure Enabling social and professional interchange between organizational members and other stakeholders Strongly influenced by the values which are emphasized within the organization Knowledge management can assist with developing social capital across the organization The impact of KM infrastructure on organization:1. Organizational Culture2. Organizational Structure3. Information Technology Infrastructure4. Common Knowledge5. Physical EnvironmentOrganizational Culture: Organizational culture reflects the norms and beliefs that guide the behavior of the organizations members Attributes of an enabling organizational culture include understanding of the value of KM practices, management support for KM at all levels, incentives that reward knowledge sharing, and encouragement of interaction for the creation and sharing of knowledge Organizational Structure: Hierarchical structure of the organization affects the people with whom individuals frequently interact, and to or from whom they are consequently likely to transfer knowledge Organizational structures can facilitate KM through communities of practice Organization structures can facilitate KM through specialized structures and roles that specifically support KMKM Infrastructure

13. Information Technology Infrastructure:The IT infrastructure includes data processing, storage, and communication technologies and systems One way of systematically viewing the IT infrastructure is to consider the capabilities it provides in four important aspects: Reach Depth Richness Aggregation Common Knowledge: Common knowledge also refers to the organizations cumulative experiences in comprehending a category of knowledge and activities, and the organizing principles that support communication and coordination Common knowledge helps enhance the value of an individual experts knowledge by integrating it with the knowledge of others Physical Environment Physical environment includes the design of buildings and the separation between them; the location, size, and type of offices; the type, number, and nature of meeting rooms A 1998 study found that most employees thought they gained most of their knowledge related to work from informal conversations around water coolers or over meals instead of formal training or manuals 14. Knowledge Management Principles KM is expensive (but so is stupidity!) Effective management of knowledge requires hybrid solutions of people and technology. KM is highly political. KM requires knowledge managers. KM benefits more from map than models, more from markets than from hierarchies. Sharing and using knowledge are often unnatural acts. KM means improving knowledge work processes. Knowledge access is only the beginning. KM never ends. KM requires a knowledge contract. The more your share, the more you gain. The knowledge acquisition process should be part of the work process. Integration of knowledge from multiple disciplines has the highest probability of creating new knowledge and value-added. Knowledge valuation should be conducted from customers perspective. KM focus should be on core knowledge critical to sustaining companys competitive edge. 15. Technologies roughly correlate to four main stages of the KM life cycle:1. Knowledge is acquired or captured using intranets, extranets, groupware, web conferencing, and document management systems.2. An organizational memory is formed by refining, organizing, and storing knowledge using structured repositories such as data warehouses.3. Knowledge is distributed through education, training programs, automated knowledge based systems, expert networks.4. Knowledge is applied or leveraged for further learning and innovation via mining of the organizational memory and the application of expert systems such as decision support systems. All of these stages are enhanced by effective workflow and project management.16. History of KM:First generation knowledge management: Focus on knowledge management (limited concept of knowledge lifecycle) Better and faster storage, indexing and retrieving of content to help knowledge sharing Improving individual performance and learning capability Origins in information retrieval, intranet and internet Technology focus sometimes obsessiveSecond generation knowledge management Focus is knowledge process management (full use of knowledge lifecycle concept) Better and faster knowledge creation and innovation plus the sharing of such knowledge Improving organizational performance and learning Origins in first generation knowledge management plus organizational learning and systems thinking (with ideas from complexity theory still to come) May or may not use technology information being evaluated. 17. Knowledge Services: To explain how knowledge is discovered To describe knowledge discovery systems, including design considerations, and how they rely on mechanisms and technologies To explain data mining (DM) technologies To discuss the role of DM in customer relationship management Knowledge Synthesis through Socialization To discover tacit knowledge Socialization enables the discovery of tacit knowledge through joint activities between masters and apprentices between researchers at an academic conference

Knowledge Discovery service from Data: Data mining another name for Knowledge Discovery in Databases is data mining (DM). Data mining systems have made a significant contribution in scientific fields for years. The recent proliferation of e-commerce applications, providing reams of hard data ready for analysis, presents us with an excellent opportunity to make profitable use of data mining. Data Mining Techniques Applications: Marketing Predictive DM techniques have been used for target marketing including market segmentation. Direct marketing customers are likely to respond to new products based on their previous consumer behavior. Retail DM methods have likewise been used for sales forecasting. Banking Trading and financial forecasting are used to determine derivative securities pricing, futures price forecasting, and stock performance. Insurance DM techniques have been used for segmenting customer groups to determine premium pricing and predict claim frequencies. Designing the Knowledge Discovery System: Business Understanding To obtain the highest benefit from data mining, there must be a clear statement of the business objectives. 1. Data Understanding Knowing the data can permit the designer or tools used for data mining to his/her specific problem. 2. Data Preparation Data selection, variable construction and transformation, integration, and formatting3. Model building and validation Building an accurate model is a trial and error process. Evaluation and interpretation Once the model is determined, the validation dataset is fed through the model. 4. Deployment Involves implementing the live model within an organization to aid the decision making process. 1. Business Understanding process: a. Determine Business objectives To obtain the highest benefit from data mining, there must be a clear statement of the business objectives.b. Situation Assessment The majority of the people in a marketing campaign, who receive a target mail, do not purchase the product. c. Determine Data Mining Goal Identifying the most likely prospective buyers from the sample, and targeting the direct mail to those customers, could save the organization significant costs. d. Produce Project Plan This step also includes the specification of a project plan for the DM study. 2. Data Understanding process: a. Data collection Defines the data sources for the study, including the use of external public data, and proprietary databases.b. Data description Describes the contents of each file or table. Some of the important items in this report are: number of fields (columns) and percent of records missing. c. Data quality and verification Define if any data can be eliminated because of irrelevance or lack of quality. d. Exploratory Analysis of the Data Use to develop a hypothesis of the problem to be studied, and to identify the fields that are likely to be the best predictors. 3. Data Preparation process: a. Selection Requires the selection of the predictor variables and the sample set. b. Construction and transformation of variables Often, new variables must be constructed to build effective models. c. Data integration The dataset for the data mining study may reside on multiple databases, which would need to be consolidated into one database. d. Formatting Involves the reordering and reformatting of the data fields, as required by the DM model. 4. Model building and Validation process:a. Generate Test Design Building an accurate model is a trial and error process. The data mining specialist iteratively try several options, until the best model emerges. b. Build Model Different algorithms could be tried with the same dataset. Results are compared to see which model yields the best results. c. Model Evaluation In constructing a model, a subset of the data is usually set-aside for validation purposes. The validation data set is used to calculate the accuracy of predictive qualities of the model. 5. Evaluation and Interpretation process:a. Evaluate Results Once the model is determined, the predicted results are compared with the actual results in the validation dataset. b. Review Process Verify the accuracy of the process. c. Determine Next Steps List of possible actions decision. 6. Deployment process:a. Plan Deployment This step involves implementing the live model within an organization to aid the decision making process.. b. Produce Final Report Write a final report. c. Plan Monitoring and Maintenance Monitor how well the model predicts the outcomes, and the benefits that this brings to the organization.d. Review Project Experience, and documentation. Data Mining Techniques: 1. Predictive Techniques Classification: Data mining techniques in this category serve to classify the discrete outcome variable. Prediction or Estimation: DM techniques in this category predict a continuous outcome (as opposed to classification techniques that predict discrete outcomes). 2. Descriptive Techniques Affinity or association: Data mining techniques in this category serve to find items closely associated in the data set. Clustering: DM techniques in this category aim to create clusters of input objects, rather than an outcome variable. The Effect of Strategic Knowledge Management on Databases: Multiple corporate databases will merge into large, integrated, multidimensional knowledge bases that are designed to support competitive intelligence and organizational memory. These centralized knowledge repositories will optimize information collection, organization, and retrieval. They will offer knowledge enriching features that support the seamless interoperability and flow of information and knowledge. 35