Knowledge Management Lecture 1 PDF

Knowledge Management Lecture 1 Knowledge Management Learning outcome Explain the basic concepts of KM and its importance Describe the differences between data, information and knowledge, and Discuss nature and various types of knowledge Why the current interest in KM? “knowledge is at the heart of much of today’s global economy, and managing knowledge has become vital to companies’ success” Kluge, et al (2001) “this transformation from a world largely dominated by physical resources, to a world dominated by knowledge, implies a shift in the locus of economic power as profound as that which occurred at the time of the industrial revolution” Burton-Jones (1999) Key themes in the knowledge society literature Knowledge is of central importance to advanced economies Knowledge is key to organisational performance Organisations and work have become more knowledge intensive Hislop, D. (2005) KM in organisations, OUP Introducing knowledge management What is KM? Knowledge management (KM) is 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, composed of human (individual skill,capability), organizational (knowledge recites in db, docs, culture etc) and social capital (knowledge concerning interaction among individuals includes values, trust, participation). Knowledge management is essentially about getting the right knowledge to the right person at the right time. Chapter 1, Becerra et al. Why KM? Sharing knowledge, a company creates exponential benefits from the knowledge as people learn from it Building better sensitivity to “brain drain” Reacting instantly to new business opportunities Ensuring successful partnering and core competencies with suppliers, vendors, customers, and other constituents Shortens the learning curve KM justification Is current knowledge going to be lost? Is proposed system needed in several locations? Are experts available/willing? Can experts articulate how problem will be solved? Is there a champion in the house? Is KM for everyone? KM is important for all organizations Today’s decision maker faces the pressure to make better and faster decisions in an environment characterized by a high domain complexity and market volatility, even in light of lack of experience typically from the decision- maker outcome of those decisions could have such a considerable impact on the organization KM and IT 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 According to IBM, the build out of the “internet of things” will lead to the doubling of knowledge every 12 hours by 2020.(2013) Key reason for knowledge explosion: IOT, Big Data, Advancement of Sc and invention, as well as collaborative Knowledge sharing society The exponential growth of knowledge has cause the world and what we know about it becomes ever more complicated and unpredictable. KM and IT Knowledge management mechanisms are organizational or structural means used to promote knowledge management. The use of leading-edge IT (e.g., Web-based conferencing) to support KM mechanisms enables dramatic improvement in KM. knowledge management systems (KMS): the synergy between latest technologies and social/structural mechanisms Effective Knowledge Management 80% - Organizational culture and human factors 20% - Technology KM Benefits Reduction in loss of intellectual capital when people leave the company Reduction in costs by decreasing the number of times the company must repeatedly solve the same problem Economies of scale in obtaining information from external providers Reduction in redundancy of knowledge-based activities Increase in productivity by making knowledge available more quickly & easily Increase in employee satisfaction by enabling greater personal development and empowerment Strategic competitive advantage in the marketplace Issues in Knowledge Management To make employees feel compelled to participate in knowledge management initiatives “Effective KM is not about making a choice between “software vs. wetware, classroom vs. hands-on, formal vs. informal, technical vs. social…uses all the options available to motivated employees to put knowledge to work …[and] depends on recognizing that all of these options basically need each other” [Stewart, 2002]. One of the primary differences between traditional information systems and KM systems is the active role that users of KM systems play on building the content of such systems. Successful implementation of KM system requires employees not only “use” but also contribute to the knowledge base. Challenges Explaining what KM is and how it can benefit a corporate environment Evaluate the firm’s core knowledge, by employee, by department, and by division Learning how knowledge can be captured, processed, and acted on Addressing the still neglected area of collaboration Continue researching KM to improve and expand its current capabilities How to deal with tacit knowledge Essence of KM Knowledge is first created in the people’s minds. KM practices must first identify ways to encourage and stimulate the ability of employees to develop new knowledge. KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge. KM should not distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization. The Nature of Knowledge The nature of knowledge Understand the difference between knowledge, data, and information Explain the alternative views of knowledge Understand the different types of knowledge Recognize the various locations of knowledge Data Data represents unorganized and unprocessed facts. Raw numbers, images, words, sounds, derived from observations or measurements Usually data is static in nature. It can represent a set of discrete facts about events. An organization sometimes has to decide on the nature and volume of data that is required for creating the necessary information. Data in itself has no meaning; it is the raw material for information. What is information? Information: a collection of data within a context that provides meaning 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 Is data with a meaning assigned to it Example: raw data from survey analysed to produce structured results Information has meaning; it is organized for some purpose. Information can be considered as an aggregation of data (processed data) which makes decision making easier. It is the raw material for knowledge Information 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 Knowledge is the experience of using information to make judgements, and the ability to link them to decisions or actions Means to analyse/ understand information/data, belief about causality of events/actions, provides the basis to guide meaningful action and thought. Broader, deeper, richer than information Knowledge is a basis for making decisions A combination of information, instincts, rules, ideas, understanding, skills, procedures and experience that guide actions and decisions Knowledge Transformation of information to knowledge happens through the processes such as: 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? Data, Information and Knowledge Nonalgorithmic Nonprogrammable (Heuristic) W ISDOM KNOWLEDGE INFORMATION Algorithmic DATA Programmable From Data Processing to Knowledge-based Systems From Awad, p.41 Data / information/ knowledge Knowledge Value Zero Low Medium High Very High Data Information (Input) (output) Knowledge (stored in manuals or as an IS) helps convert data into information Example Knowledge Counting pH = nH/(nH+nT) EV=pH RH+ pT RT pT = nT/(nH+nT) HTHTT pH = 0.40 HHHTH nH = 40 pT = 0.60 … RH = +$10 EV = -$0.80 nT = 60 TTTHT RT = -$8 Data Information Value Zero Low Medium High Very High Knowledge - events Knowledge Knowledge Data Information Information System Use of information Knowledge Decision Events Knowledge “A fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories, but also in organizational routines, process, practices, and norms” (Davenport, 1998) Subjective View of knowledge Knowledge is viewed as an ongoing accomplishment that continuously affects and is inﬂuenced by social practice Two possible perspectives Knowledge as State of Mind (Individual) knowledge as being a state of an individual’s mind. various individuals have differing experiences and backgrounds, their beliefs and hence knowledge, could differ from each other. Focus on enabling individuals to enhance their personal areas of knowledge Knowledge as Practice (collective) is viewed as being held by a group Knowledge is comprised of beliefs, but the beliefs themselves are collective rather than individual, Objective View of Knowledge knowledge can be located in the form of an object or a capability that can be discovered or improved by human agents. Three possible perspectives: Knowledge as Objects (stored) knowledge as something that can be stored, transferred, and manipulated. Knowledge as Access to Information knowledge is viewed here as something that enables access and utilization of information, emphasizing the accessibility of the knowledge objects. Knowledge as Capability (Action) knowledge can be applied to inﬂuence action. emphasis on knowledge as a strategic capability that can potentially be applied to seek a competitive advantage. objective view facilitates making practical recommendations about how organizations should manage knowledge, Kinds of knowledge Various classification of knowledge: Shallow (readily recalled) and deep (acquired through years of experience) Explicit (codified) and tacit (embedded in the mind) Individual, social, causal, conditional, relational and pragmatic(logical) Embodied, encoded and procedural Types of knowledge Procedural knowledge(Steps) – know how represents the understanding of how to carry out a specific procedure. sequences of steps or actions to desired (or undesired) outcomes. Example: process used to assemble a particular model of the car. Declarative knowledge (facts)- know what is routine knowledge about which the expert is conscious. It is shallow knowledge that can be readily recalled since it consists of simple and uncomplicated information. about relationships among variables Example: a) Identify the specific product features a specific customer likes b) Factors that affect the quality of the final product. Types of knowledge Semantic knowledge is highly organized, ``chunked'' knowledge that resides mainly in long-term memory. Semantic knowledge can include major concepts, vocabulary, facts, and relationships. Episodic knowledge represents the knowledge based on episodes (experimental information). Each episode is usually ``chunked'' in long-term memory. From Procedural to Episodic Knowledge Shallow Procedural Knowledge Knowledge Knowledge of how to do a task that is essentially motor in nature; the same knowledge is used over and over again. Declarative Knowledge Surface-type information that is available in short-term memory and easily verbalized; useful in early stages of knowledge capture but less so in later stages. Semantic Knowledge Hierarchically organized knowledge of concepts, facts, and relationships among facts. Episodic Knowledge Knowledge that is organized by temporal spatial means, not by concepts or relations; experiential information that is chunked by episodes. This knowledge is highly compiled Deep and autobiographical and is not easy to extract or capture. Knowledge Tacit vs Explicit Tacit knowledge usually gets embedded in human mind through experience Includes cultural beliefs, values, attitudes, insights, intuitions, and hunches (focus on know-how) Context dependent and personal in nature. It is difﬁcult to express and formalize, and therefore difﬁcult to share. Explicit knowledge refers to knowledge that is expressed into words and numbers. can be easily stored and shared formally and systematically in the form of data, speciﬁcations, manuals, drawings, audio- and videotapes, computer programs, patents, etc, (focus on know-what) We can convert explicit knowledge to tacit knowledge Easily transferable, reusable Requires effort to keep up-to-date Characteristics of tacit and explicit knowledge Tacit knowledge Explicit knowledge Inexpressive in a codifiable form Codifiable Subjective Objective Personal Impersonal Context specific Context independent Difficult to share Easy to share p.19 Hislop (2005) General and Specific Knowledge General knowledge is possessed by a large number of individuals and can be shared easily across individuals. Common policy and procedure Specific knowledge, or “idiosyncratic knowledge,” is possessed by a very limited number of individuals, and is expensive to transfer. Such as games strategic knowledge by a coach Technically and Contextually Specific Knowledge Technically specific knowledge is deep knowledge about a specific area It includes knowledge about the tools and techniques that may be used to address problems in that area. Examples knowledge about computer hardware possessed by a computer engineer. Contextually specific knowledge refers to the knowledge of particular circumstances of time and place in which work is to be performed Contextually speciﬁc knowledge cannot be acquired through formal training but instead must be obtained from within the speciﬁc context. Example: t knowledge of the mechanisms used to patent and license NASA- developed technology for public use Illustrations of the Different Types of Knowledge Expert Knowledge It is the information woven inside the mind of an expert for accurately and quickly solving complex problems. Knowledge Chunking Knowledge is usually stored in experts long-range memory as chunks. Knowledge chunking helps experts to optimize their memory capacity and enables them to process the information quickly. Chunks are groups of ideas that are stored and recalled together as an unit. Knowledge as an attribute of expertise In most areas of specialization, insight and knowledge accumulate quickly, and the criteria for expert performance usually undergo continuous change. In order to become an expert in a particular area, one is expected to master the necessary knowledge and make significant contributions to the concerned field. The unique performance of a true expert can be easily noticed in the quality of decision making. The true experts (knowledgeable) are usually found to be more selective about the information they acquire, and also they are better able in acquiring information in a less structured situation. They can quantify soft information , and can categorize problems on the basis of solution procedures that are embedded in the experts long range memory and readily available on recall. Expert knowledge Hence, they tend to use knowledge-based decision strategies starting with known quantities to deduce unknowns. If a first-cut solution path fails, then the expert can trace back a few steps and then proceed again. Non experts use means-end decision strategies to approach the problem scenario. Non experts usually focus on goals rather than focusing on essential features of the task which makes the task more time consuming and sometimes unreliable. Specific individuals are found to consistently perform at higher levels than others and they are labeled as experts. Types of Expertise Associational Expertise Expert based on his experience. i.e fix TV based on his exposure. Motor Skills Expertise Motor skill expertise is predominantly physical rather than cognitive Improve skills by practice. example: Sports related skill, cyclist, very rely on physical actions. Theoretical (Deep) Expertise Deep understanding of the theories in his domain acquired through formal training and hands-on problem-solving. Types of Knowledge Simple knowledge focuses on one basic area Complex knowledge draws upon multiple distinct areas of expertise Support knowledge relates to organizational infrastructure and facilitates day-to-day operations Tactical knowledge pertains to the short-term positioning of the organization relative to its markets, competitors, and suppliers Strategic knowledge pertains to the long-term positioning of the organization in terms of its corporate vision and strategies for achieving that vision Characteristics of Knowledge Explicitness Measured based on a continuous scale, with explicit knowledge being high in explicitness and tacit knowledge being low in this regard. Codifiability reflects the extent to which knowledge can be articulated or codified, even if the resulting codified knowledge might be difficult to impart to another individual. Teachability reflects the extent to which the knowledge can be taught to other individuals, through training, apprenticeship Knowledge Specificity (Specific Knowledge) the knowledge can be acquired and/or effectively used only by individuals possessing certain prior knowledge possessed by a very limited number of individuals and is expensive to transfer (example:contextual knowledge, NASA) Reservoirs of Knowledge Knowledge Reservoirs /Locations People Artifacts Organizational Entities Individuals Organizational Units (department) Practices Technologies Repositories Organizations Inter-organizational Groups Networks (external) (CoP) Information mangagement (Info System) is useful tool for KM, but IS is not equal KM Source of reference Sophia Ananiadou Lecture slides Chapters 1, 2 from Becerra et al (2010) Thank You KM SOLUTION ICT608 SEMESTER OCT 2020 LEARNING OUTCOME Understand the concept of knowledge management and its impact on Organization Examine knowledge management solutions Describe four levels of knowledge management solutions: KM processes KM systems KM mechanisms and technologies KM infrastructure 2 IMPACT OF KM ON ORGANISATION to improved performance facilitates contributes creation, sharing to Improved and use performance Knowledge Organization KM ORGANISATIONAL IMPACTS OF KM AT FOUR LEVELS Business Organizational People Products Processes Performance KNOWLEDGE MANAGEMENT IMPACT ON PEOPLE Knowing & KM Knowledge Learning KM facilitates people to learn  organisational growth KM causes people to become more flexible  enhances job satisfaction Adaptability  increasing ability to learn Accomplished through:  Externalisation : tacit->Explicit  Internalisation : Explicit -> Tacit  Socialisation : tacit -> tacit Job Satisfaction  Exchange : Explicit -> explicit IMPACT ON ADAPTABILITY AND JOB SATISFACTION Individual Team Organizational learning learning learning People interact and share knowledge with one another, enhancing the knowledge assets of an organisation Learn better Aware about new ideas KM provides people with solutions to problems they face in case those same problems have been encountered earlier and effectively addressed People are better prepared to accept and respond to change IMPACT ON BUSINESS PROCESSES Process Effectiveness Fewer mistakes Adaptation to changed circumstances KM Knowledge Process Efficiency Productivity improvement Cost savings KM enables improvements in Process Innovation organisational processes Improved brainstorming Better exploitation of new ideas  Provisions for workable solution  Impart practicable knowledge to people Accomplished through:  Direction : help desk; call centre  Routine : policies and standards  Socialisation : tacit to tacit  Exchange : explicit to explicit IMPACT ON PROCESS IMPROVEMENT Process Effectiveness KM enables organisations to become more effective by helping them to select and perform the most appropriate processes KM enables organisations to quickly adapt their processes according to the circumstances, in changing times Process Efficiency and Productivity KM allows easy access to knowledge resources, performing the process quickly in a low-cost fashion Process Innovation KM enables the performance of processes in a creative and novel way … “breed ideas that ignite value”, which helps to improve effectiveness, efficiency and/ or the marketability IMPACT ON PRODUCTS Value-added products; KM Knowledge Knowledge-based products KM processes help organisations to offer new products or improved products that provide a significant additional value as compared with earlier products (e.g. Understand customer wants; Redesign products that better suit customers’ needs; Internal collaboration, Knowledge sharing with partners and suppliers, Best practices replication) KM has impact on product that are knowledge based (e.g. consultation; software development) Knowledge-based products also play a role in manufacturing (e.g. incorporation of `expertise’ into machine functionalities) IMPACT ON VALUE-ADDED PRODUCTS KM processes can help organizations offer new products or improved products that provide a significant additional value as compared with earlier products Value-added products also benefit from KM due to the effect the latter has on organizational process innovation IMPACT ON KNOWLEDGE-BASED PRODUCTS KM can have a significant impact on product that are knowledge based like those in consulting or software development etc. Knowledge based products can sometimes play a significant role in traditional manufacturing firms IMPACT ON ORG. PERFORMANCE Business Strategy Organizational Performance Revenue Scale of economies KM Knowledge Cost Scope of economies Vision Sustainable Competitive Strategy advantages  Direct Impacts  Knowledge is used to create innovative products that generate revenue and profit  Indirect Impacts  Use of KM to demonstrate intellectual leadership within the industry, which, in turn, might enhance customer loyalty  Use of knowledge to gain an advantageous negotiating position with respect to competitors or partner organizations ECONOMY OF SCALE AND SCOPE A company’s output is said to exhibit economy of scale if the average cost of production per unit decreases with increase in output A company’s output is said to exhibit economy of scope when the total cost of that same company producing two or more different products is less than the sum of the costs that would be incurred if each product had been produced separately by a different company A SUMMARY OF ORGANIZATIONAL IMPACTS OF KNOWLEDGE MANAGEMENT NONAKA & TAKEUCHI’S SECI MODEL: KNOWLEDGE CREATION & TRANSFORMATION O Socialization: O Tacit  Tacit Tacit Explicit O Externalization O Tacit  Explicit Tacit S E O Combination O Explicit  Explicit Explicit I C O Internalization O Explicit  Tacit NONAKA & TAKEUCHI’S SECI MODEL: KNOWLEDGE CREATION & TRANSFORMATION TACIT TO TACIT TACIT TO EXPLICIT (SOCIALIZATION) (EXTERNALIZATION) E.G., TEAM MEETINGS AND E.G., DIALOG WITHIN TEAM DISCUSSIONS ANSWER QUESTIONS EXPLICIT TO TACIT EXPLICIT TO EXPLICIT (INTERNALIZATION) (COMBINATION) E.G., LEARN FROM A REPORT E.G., E-MAIL A REPORT KNOWLEDGE MANAGEMENT Knowledge management can be defined as performing the activities involved in : discovering, capturing, sharing, and applying knowledge so as to enhance, in a cost-effective fashion, the impact of knowledge on the unit’s goal achievement. “Doing what is needed to get the most out of knowledge resources” 17 KNOWLEDGE RESOURCES The term knowledge resources refers not only to i the knowledge currently possessed by : the individual or the organization ii the knowledge that can potentially be obtained (at some cost if necessary) from other individuals or organizations 18 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 19 KNOWLEDGE MANAGEMENT SYSTEMS Knowledge management systems are the integration of technologies and mechanisms that are developed to support KM processes 20 AN OVERVIEW OF KNOWLEDGE MANAGEMENT SOLUTIONS KM Processes KM Systems KM Mechanisms and Technologies KM Infrastructure 21 KNOWLEDGE MANAGEMENT PROCESSES Discovery Combination Socialization Sharing Application Socialization Direction Exchange Routines Capture Externalization Internalization 22 KNOWLEDGE DISCOVERY Development of new tacit or explicit knowledge from data and information or from the synthesis of prior knowledge 2 main ways Combination (Explicit-Explicit) Socialization (Tacit-Tacit) 23 KNOWLEDGE DISCOVERY: COMBINATION The process of synthesizing explicit knowledge - create new, more complex sets of explicit knowledge multiple bodies of explicit knowledge also involve data and information Existing explicit knowledge, information, and data are reconfigured, recategorized, and recontextualized incremental – e.g., “new” proposal Example: data mining Data mining techniques may be used to uncover new relationships among explicit data, to produce predictive or categorization models that create new knowledge 24 KNOWLEDGE DISCOVERY: SOCIALIZATION The process of synthesis of tacit knowledge across individuals usually through joint activities/practice instead of written or verbal instructions E.g. chatting about how to find a good job Facilitation by technologies Groupware Web 2.0 – forums, chat-room, face-book… 25 KNOWLEDGE CAPTURE The process of retrieving either explicit or tacit knowledge that resides within people, artifacts, or organizational entities. Knowledge might reside within an individual’s mind, without that individual having the ability to recognize it and share it with others. (tacit knowledge) Knowledge might reside in an explicit form in a manual, but few people might be aware of it. (explicit knowledge) Knowledge captured might reside outside the organizational boundaries, including consultants, competitors, customers, suppliers, and prior employers of the organization’s new employees. Externalization vs Internalization 26 EXTERNALIZATION VS INTERNALIZATION Externalization converting tacit knowledge into explicit forms such as words, concepts, visuals, or figurative language. Created through dialogue or collective reflection Internalization conversion of explicit knowledge into tacit knowledge. traditional notion of “learning”. Documents help individual internalize what they experience E.g., after reading a book, you learn in your mind Discussion: How does IT help? 27 KNOWLEDGE SHARING the process through which explicit or tacit knowledge is communicated to other individuals. effective transfer - so that the recipient of knowledge can understand it well enough for actions. may take place across individuals, groups, departments or organizations. Knowledge is shared (internalized) and not recommendations (no internalization occurs) based on knowledge. Socialization vs Exchange. 28 KNOWLEDGE SHARING: SOCIALIZATION focuses on the sharing of tacit knowledge among individuals, groups, and organizations e.g., talking to a senior year student about how to finish your degree course with minimal amount of effort in the orientation camp. e.g., apprenticeships Note: one may also use socialization to synthesize tacit knowledge for knowledge discovery. 29 KNOWLEDGE SHARING: EXCHANGE focuses on the sharing of explicit knowledge. communicate or transfer explicit knowledge between individuals, groups, and organizations. e.g., passing a computer manual from one to another. Discussion: How does IT help? 30 KNOWLEDGE APPLICATION The process of applying explicit or tacit knowledge to carry out some tasks or to guide action or decision. The knowledge may have been internalized (exist in one’s mind) or not (e.g., work according to a manual). Direction vs Routines. 31 DIRECTION Individuals possessing the knowledge direct the action of another individual without transferring to that person the knowledge underlying the direction. Direction involves the transfer of instructions or decisions and not the transfer of the knowledge. This has been labeled as knowledge substitution (Conner and Prahalad 1996) E.g., calling the help desk to solve your PC problems. Experts’ knowledge embedded in knowledge-base, expert systems and decision support systems. Troubleshooting systems based on the use of technologies like case-based reasoning. 32 ROUTINES involve the utilization of knowledge embedded in procedures, rules, and norms that guide future behavior. economize on communication more than directions because they are embedded in procedures or technologies. e.g., inventory management system for automatic re-ordering. general information systems and automation helps: Enterprise resource planning systems Management information systems … Discussion: How does IT help? 33 FOUR MODES OF KNOWLEDGE CONVERSION To Tacit knowledge Explicit knowledge Socialization Externalization Tacit knowledge From Internalization Combination 1+1 Explicit knowledge 3 Source: Knowledge-Creating Company, p. 62. 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 never ends. KM requires a knowledge contract. Source: Thomas Davenport, "Some Principles of Knowledge Management," http://www.utexas.edu/kman/kmprin.htm KNOWLEDGE MANAGEMENT PRINCIPLES 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 company’s competitive edge. KM SOLUTIONS (SUMMARY) Knowledge Knowledge Knowledge Knowledge Discovery Capture Sharing Application KM Processes Combination Socialization Internalization Externalization Exchange Direction Routines Knowledge Knowledge Knowledge Knowledge KM Systems Discovery Capture Sharing Application Systems Systems Systems Systems KM Mechanisms Analogies and metaphors Decision support systems KM Technologies Brainstorming retreats Web-based discussion groups On-the-job training Repositories of best practices Face-to-face meetings Artificial intelligence systems Apprenticeships Case-based reasoning Employee rotation Groupware Learning by observation Web pages …. … Organization Organization IT Common Physical KM Infrastructure Culture Structure Infrastructure Knowledge Environment 37 KM Processes, Mechanisms, and Technologies 38 ASSIGNMENT 1. Knowledge in your chosen organization: a) Determine the various locations of knowledge within your chosen organization. Classify them appropriately. b) Now speculate on the negative effects of not having one or more of those knowledge repositories and accordingly determine which repository is the most critical to the organization. Which is the least? KM SOLUTION – PART B ICT608 : INTRODUCTION TO KNOWLEDGE MANAGEMENT LEARNING OUTCOME Understand the concept of knowledge management Examine knowledge management solutions Describe four levels of knowledge management solutions: KM processes KM systems KM mechanisms and technologies KM infrastructure 2 RECAP: KNOWLEDGE MANAGEMENT PRINCIPLES The more you 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 company’s competitive edge. RECAP: FOUR MODES OF KNOWLEDGE CONVERSION To Tacit knowledge Explicit knowledge Socialization Externalization Tacit knowledge From Internalization Combination 1+1 Explicit knowledge 3 Source: Knowledge-Creating Company, p. 62. KNOWLEDGE SPIRAL The model is a spiral, not a Dialogue cycle, because as one (Collective Reflection) “learns” around the cycle, understanding moves to Socialization Externalization deeper and deeper levels Linking Field Explicit Building Knowledge Internalization Combination Learning by Doing Nonaka and Takeuk theorized that the creation of knowledge is the result of a continuous cycle of four integrated processes: externalization, internalization, combination, and socialization RECAP: KM SOLUTIONS Knowledge Knowledge Knowledge Knowledge Discovery Capture Sharing Application KM Processes Combination Socialization Internalization Externalization Exchange Direction Routines Knowledge Knowledge Knowledge Knowledge KM Systems Discovery Capture Sharing Application Systems Systems Systems Systems KM Mechanisms Analogies and metaphors Decision support systems KM Technologies Brainstorming retreats Web-based discussion groups On-the-job training Repositories of best practices Face-to-face meetings Artificial intelligence systems Apprenticeships Case-based reasoning Employee rotation Groupware Learning by observation Web pages …. … Organization Organization IT Common Physical KM Infrastructure Culture Structure Infrastructure Knowledge Environment 6 KNOWLEDGE MANAGEMENT MECHANISMS KM mechanisms are organizational or structural means used to promote KM KM mechanisms may or may not utilize electronic technology KM mechanisms involve some kind of  organizational arrangement, or  social means, or  structural means of facilitating KM Examples:  Near-term: learning by doing, on-the-job training, learning by observation, face-to-face meetings, …  Long-term: hiring a Chief Knowledge Officer, cooperative projects across departments, traditional hierarchical relationships, organizational policies, standards, initiation process for new employees, employee rotation across departments, … Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE MANAGEMENT TECHNOLOGIES Technologies that support KM include:  artificial intelligence (AI) technologies encompassing:  those used for knowledge acquisition  case-based reasoning systems  expert systems  … and many others  electronic discussion groups  computer-based simulations  databases  decision support systems  enterprise resource planning systems  management information systems  expertise locator systems  videoconferencing  information repositories encompassing best practices databases and lessons learned systems Many of these technologies are now being “rebranded” as Web 2.0 Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE MANAGEMENT TECHNOLOGIES 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 9 KNOWLEDGE MANAGEMENT TECHNOLOGIES Examples:  World Bank: uses a combination of video interviews and hyperlinks to documents and reports to systematically record the knowledge of employees who are close to retirement [Lesser & Prusak 2001]  British Petroleum (BP): desktop videoconferencing has improved communication and enabled many problems at offshore oil fields to be solved without extensive traveling [Skyrme 2000] Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE MANAGEMENT SYSTEMS KM systems utilize combinations of a variety of KM mechanisms and technologies, in order to support the KM processes:  Knowledge Management Discovery Systems  Knowledge Management Capture Systems  Knowledge Management Sharing Systems  Knowledge Application Systems Typical KM systems focus primarily on supporting one KM process.  In reality, a more sophisticated KM system may actually be designed to support more than one of the KM processes simultaneously. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE DISCOVERY SYSTEMS Knowledge 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 Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE DISCOVERY SYSTEMS: MECHANISMS FOR COMBINATION Mechanisms that facilitate combination:  Collaborative problem solving  Joint decision making  Collaborative creation of documents Example:  At senior management level, new explicit knowledge is created by sharing documents and information related to midrange concepts (eg, product concepts) augmented with grand concepts (eg, corporate vision) to produce new knowledge about both areas.  This newly created knowledge might be a better understanding of products and a corporate vision [Nonaka & Takeuchi 1995]. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE DISCOVERY SYSTEMS: MECHANISMS FOR SOCIALIZATION Mechanisms that facilitate socialization:  Apprenticeships  Employee rotation across areas  Conferences  Brainstorming retreats  Cooperative projects across departments  Initiation process for new employees Example:  Honda “sets up brainstorming camps (tama dashi kai) – informal meetings for detailed discussions to solve difficult problems in development projects” [Nonaka & Takeuchi 1995] Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE DISCOVERY SYSTEMS: TECHNOLOGIES FOR COMBINATION Technologies that facilitate combination:  Knowledge discovery systems  Databases  Web-based access to data “Reconfiguration of existing information through sorting, adding, combining, and categorizing of explicit knowledge (as conducted in computer databases) can lead to new knowledge” [Nonaka& Takeuchi 1995]. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE DISCOVERY SYSTEMS: TECHNOLOGIES FOR SOCIALIZATION Technologies that facilitate socialization:  Instant messaging  Social chat groups  VOIP  Video-conferencing  Electronic support for communities of practice (COPs)  Wikis  Forums, BBS systems, newsgroups  Blogs, especially those that allow comments and discussions Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu 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 Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE CAPTURE SYSTEMS: MECHANISMS FOR EXTERNALIZATION Examples of mechanisms that facilitate externalization, from the consulting company Viant [Stewart 2000]:  Before every project, consultants are required to complete a “quicksheet” describing:  the knowledge they need  what aspects of knowledge can be leveraged from prior projects  what they need to create  the lessons they hope to learn that they can share with others later  After every project, the team is required to meet to produce a sunset review to document what worked and what did not work well. Forgetting these reports is hard for several reasons:  “Almost every document ends up on Viant’s internal website, hot-linked every which way.”  “Sunset reviews are done with a facilitator who wasn’t on the team, which helps keep them honest.”  “Every six weeks [the] knowledge-management group prepares, posts, and pushes a summary of what’s been learned.” Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE CAPTURE SYSTEMS: MECHANISMS FOR INTERNALIZATION Mechanisms that facilitate internalization:  Learning by doing  On-the-job training  Learning by observation  Face-to-face meetings Example:  At one firm “the product divisions also frequently send their new-product development people to the Answer Center to chat with the telephone operators or the 12 specialists, thereby `re-experiencing’ their experiences” [Nonaka & Takeuchi 1995]. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE CAPTURE SYSTEMS: TECHNOLOGIES Technologies that facilitate externalization:  Knowledge elicitation is needed for implementation of intelligent technologies such as:  expert systems  case-based reasoning systems Technologies that facilitate internalization:  Computer-based training technologies  Communication technologies  eg, an individual can internalize knowledge from a message sent by another expert, an AI- based knowledge capture system, computer-based simulations, … Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE SHARING SYSTEMS Knowledge sharing systems support the process through which explicit or implicit (tacit) knowledge is communicated to other individuals Knowledge sharing systems operate by supporting socialization (which promotes sharing of tacit knowledge) and exchange (ie, sharing of explicit knowledge) subprocesses Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE SHARING SYSTEMS: MECHANISMS & TECHNOLOGIES FOR SOCIALIZATION Mechanisms and technologies facilitating socialization (tacit knowledge): many play an equally important role for knowledge sharing as in knowledge discovery Topically focused discussion groups (or technology-enabled chat groups) facilitate knowledge sharing by enabling individuals to explain their knowledge to the rest of the group Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE SHARING SYSTEMS: MECHANISMS & TECHNOLOGIES FOR EXCHANGE Mechanisms facilitating exchange (explicit knowledge):  memos & letters  manuals  progress reports  presentations Technologies facilitating exchange:  Web 2.0, groupware & other team collaboration mechanisms  web-based access to data & databases  repositories of information, including best practice databases, lessons learned systems, and expertise locator systems Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu 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. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE APPLICATION SYSTEMS: KM MECHANISMS Mechanisms facilitating direction(transfer of instruction/decision) include:  traditional hierarchical relationships in organizations  help desks  support centers Mechanisms supporting routines include:  organizational policies  work practices  standards For both direction and routines, these mechanisms can be implemented either:  within an organization (eg, organizational hierarchies)  across organizations (eg, software support help desks) Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KNOWLEDGE APPLICATION SYSTEMS: KM TECHNOLOGIES Technologies supporting direction include:  experts’ knowledge embedded in expert systems and decision support systems  troubleshooting systems based on the use of technologies like case-based reasoning Technologies that facilitate routines include:  expert systems  enterprise resource planning systems  traditional management information systems Again, for both direction and routines, these technologies can be implemented either:  within an organization  across organizations Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM Processes, Mechanisms, and Technologies 27 KNOWLEDGE MANAGEMENT INFRASTRUCTURE Things that combine to facilitate the flow of information and knowledge in support of actions and decisions that comprise organizational activity. Main components:  Organizational Culture  Organizational Structure  Communities of Practice  Information Technology Infrastructure  Common Knowledge  Physical environment Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2010 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: ORGANIZATIONAL CULTURE Organizational culture reflects the norms and beliefs that guide the behavior of the organization’s members Attributes of a KM-enabling organizational culture include:  Understanding of the value and benefits of KM practices  Management support for KM at all levels, including allocation of time and adequate funding resources  Incentives that reward knowledge sharing, and encouragement of interaction for the creation and sharing of knowledge  Willingness to tackle the inability to directly measure the financial benefits from KM Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: ORGANIZATIONAL CULTURE OBSTACLES Typically, the most important challenges in KM are nontechnical in nature – and have to do with lack of the above organizational culture characteristics [Dyer and McDonough 2001]. Less than 10% of companies trying to implement KM have succeeded in making it part of their culture [estimate by Carla O’Dell, as reported by Koudsi 2000]. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: 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  Traditional reporting relationships influence:  the flow of data and information  the groups who make decisions together  and thus, the sharing and creation of knowledge  By decentralizing or flattening the organizational structure, companies often seek to eliminate organizational layers, so as to:  place more responsibility with each individual  increase the size of groups reporting to each individual  and thus, increase likelihood of knowledge sharing across a larger group of individuals Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: ORGANIZATIONAL STRUCTURE Organizational structures can facilitate KM through communities of practice A community of practice (COP) is an organic and self- organized group of individuals who are dispersed geographically or organizationally but communicate regularly to discuss issues of mutual interest [Lave & Wenger 1991]. Examples:  A tech club at DaimlerChrysler includes a group of engineers who do not work in the same unit but meet regularly, on their own initiative, to discuss problems related to their area of expertise  At Xerox, a strategic community of IT professionals, involving frequent informal interactions among them, promotes knowledge sharing [Storck & Hill 2000] Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: ORGANIZATIONAL STRUCTURE COPs are usually not part of a company’s formal organization COPs provide access to a larger group of individuals than is possible within traditional departmental boundaries  So there are more potential helpers, increasing the probability that at least one can provide useful knowledge in any given situation COPs provide access to external knowledge sources  An organization’s external stakeholders (eg, customers, suppliers, partners) provide a far greater knowledge reservoir than just its own [Choo 1998].  Example: relationships with university researchers can help new biotechnology firms to maintain their innovativeness. How executives can facilitate COPs:  Legitimize COPs by supporting participation  Enhance perceived value of participation by seeking advice from COPs  Provide resources, either financial or via connections to external experts Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: ORGANIZATIONAL STRUCTURE Organization structures can facilitate KM through specialized structures and roles that specifically support KM Examples:  Appoint a Chief Knowledge Officer  Establish a separate department for KM  R&D department supports KM about the latest or future developments  Corporate library supports business units by serving as a repository of historical information Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: IT INFRASTRUCTURE The information technology 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 [Daft & Lengel 1986; Evans & Wurster 1999]:  Reach  Depth  Richness  Aggregation Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: IT INFRASTRUCTURE (REACH) Reach pertains to access and connection, and the efficiency of such access Network:  reach reflects the number and geographic locations of the nodes that can be efficiently accessed  Internet has greatly enhanced inexpensive reach Standardization of cross-firm communication standards (eg, meta-languages like XML) make it easier for firms to communicate with a wider array of trading partners  including those with whom they do not have long-term relationships Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: IT INFRASTRUCTURE (DEPTH) Depth focuses on the detail and amount of information that can be effectively communicated over a medium Closely corresponds to the aspects of bandwidth and customization in Evans & Wurster’s characterization of richness  Communicating deep and detailed information requires high bandwidth, which is now cheap  Again, advances in cross-firm communication standards greatly enhance the possible depth Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: IT INFRASTRUCTURE (RICHNESS) Communication channels can be arranged along a continuum representing their “relative richness” [Carlson & Zmud 1999] Richness of a medium is based on its ability to:  Provide multiple cues simultaneously, eg:  body language  facial expression  tone of voice  Provide quick feedback  Personalize messages  Use natural language to convey subtleties [Daft & Lengel 1984] Traditionally, IT has been viewed as a lean communication medium  But this is rapidly changing with today’s technology! Consider YouTube, Skype Video, etc… Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: IT INFRASTRUCTURE (AGGREGATION) Rapid advances in IT have greatly enhanced the ability to store and quickly process information Enables the aggregation of large volumes of information drawn from multiple sources Examples:  Data mining and data warehousing together enable the synthesis of diverse information from multiple sources, potentially to produce new insights  Enterprise resource planning (ERP) systems present a natural platform for aggregating knowledge across different parts of an organization Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: COMMON KNOWLEDGE Common knowledge refers to the organization’s cumulative experiences in comprehending a category of knowledge and activities, and the organizing principles that support communication and coordination [Zander & Kogut 1995] Provides unity to the organization:  Common language and vocabulary  Recognition of individual knowledge domains  Common cognitive schema  Shared norms  Elements of specialized knowledge that are common across individuals sharing knowledge Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: COMMON KNOWLEDGE Common knowledge helps enhance the value of an individual expert’s knowledge by integrating it with the knowledge of others Common knowledge is common only to the particular organization  Increases value in that particular organization  Does not transfer to its competitors  Thus… common knowledge supports knowledge transfer within the organization, but impedes transfer (or leakage) of knowledge outside the organization [Argote & Ingram 2000] Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: PHYSICAL ENVIRONMENT (1) 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 study found that most employees reported they gained most of their knowledge related to work from informal conversations around water coolers or over meals instead of formal training or manuals [Wensley 1998] Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM INFRASTRUCTURE: PHYSICAL ENVIRONMENT (2) Examples:  London Business School created an attractive space between two major departments, which were earlier isolated, to enhance knowledge sharing between them  Reuters News Service installed kitchens on each floor to foster discussions  A medium-sized firm in the US focused on careful management of office locations to facilitate knowledge sharing, developing open-plan offices with subtle arrangements to encourage knowledge accidents [Stewart 2000]  Locations were arranged so as to maximize the chances of face-to-face interactions among people who might be able to help each other  eg, snack areas and vending machines were carefully positioned Example : University  Café / Coffeeshop?  Student Union?  Faculty offices versus laboratories?  University Center? Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu Knowledge Management Infrastructure Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu KM SOLUTIONS (SUMMARY) Knowledge Knowledge Knowledge Knowledge Discovery Capture Sharing Application KM Processes Combination Socialization Internalization Externalization Exchange Direction Routines Knowledge Knowledge Knowledge Knowledge KM Systems Discovery Capture Sharing Application Systems Systems Systems Systems KM Mechanisms Analogies and metaphors Decision support systems KM Technologies Brainstorming retreats Web-based discussion groups On-the-job training Repositories of best practices Face-to-face meetings Artificial intelligence systems Apprenticeships Case-based reasoning Employee rotation Groupware Learning by observation Web pages …. … Organization Organization IT Common Physical KM Infrastructure Culture Structure Infrastructure Knowledge Environment 45 EXERCISE 1. KM processes in an organization: Observe and describe at least one (preferably more) examples of knowledge discovery, knowledge capture, knowledge sharing, and knowledge application in your organization. Identify strengths and weaknesses of your organization’s KM, with respect to the mechanisms and technologies as well as the infrastructure.  Note: you may wish to extend/refine work you did in Assignment 1. 2. Suggest reasons why a knowledge sharing system could be established between rival organizations (eg, Mastercard and Visa) for the mutual benefit of both organizations. 3. Critique the following statement: “We have implemented several IT solutions: expert systems, chat group, and best practices and lessons learned databases. These powerful solutions can surely get our employees to internalize knowledge.” Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall / Additional material © 2008 Dekai Wu EXERCIXE 3. Knowledge in your chosen organization: a) Determine the various locations of knowledge within your chosen organization. Classify them appropriately. b) Now speculate on the negative effects of not having one or more of those knowledge repositories/portals and accordingly determine which repository is the most critical to the organization. Which is the least? Knowledge TOPIC 3 Management System OUTLINE Challenges in building KM systems Knowledge Management System Components Knowledge Management System Life Cycle INTRODUCTION KMSLC centers around 3 questions: What is the problem that warrants a solution by KM? What development strategy should be considered? What process will be used to build the system? 3 CHALLENGES IN BUILDING KMS Changing Organizational Culture  Involves changing people's attitudes and behaviours.  Sharing Knowledge and not hoarding Knowledge Evaluation:  Involves assessing the worth of information  Reward system for employees generating best knowledge 4 CHALLENGES Knowledge Processing:  Involves the identification of techniques to acquire, store, process and distribute information.  Sometimes it is necessary to document how certain decisions were reached. Knowledge Implementation:  An organization should commit to change, learn, and innovate.  It is important to extract meaning from information that may have an impact on specific missions.  Lessons learned from feedback can be stored for future to help others facing the similar problems 5 KNOWLEDGE MANAGEMENT SYSTEM Knowledge management systems refer to any kind of IT system that :  stores and retrieves knowledge,  improves collaboration,  locates knowledge sources,  mines repositories for hidden knowledge,  captures and uses knowledge,  enhances the KM process. KMS COMPONENTS Technologies  Communication  Access knowledge  Communicates with others  Collaboration  Perform groupwork for organizing meetings and supporting group interaction  and decision-making.  Synchronous or asynchronous  Same place/different place  Storage and retrieval  Capture, storing, retrieval, and management of both explicit and tacit knowledge through collaborative systems  ensure that acquired or shared knowledge is readily accessible to others.  The documents and information in databases could be retrieved through the Internet or the organization’s intranet portal/websites. KMS COMPONENTS Supporting technologies  Artificial intelligence  Expert systems, neural networks, fuzzy logic, intelligent agents  Intelligent agents  Systems that learn how users work and provide assistance  Knowledge discovery in databases  Process used to search for and extract information  Internal = data and document mining  External = model marts and model warehouses  XML  Extensible Markup Language  Enables standardized representations of data  Better collaboration and communication through portals CONVENTIONAL VERSUS KM SYSTEM LIFE CYCLE Key differences: Systems analysts deal with information from the user; knowledge developers deal with knowledge for company specialists Users know the problem but not the solution; company specialists know the problem and the solution System development is primarily sequential; KMSLC is incremental and interactive System testing normally at end of cycle; KM system testing evolves from beginning of the cycle CONVENTIONAL VERSUS KM SYSTEM LIFE CYCLE System development more extensive than for KMSLC Conventional system life cycle is process-driven “specify then build”; KMSLC is result-oriented “start slow and grow” Conventional system life cycle does not support rapid prototyping; KMSLC does CONVENTIONAL VERSUS KM SYSTEM LIFE CYCLE Key similarities: Both begin with a problem and end with a solution Both begin with information gathering or capture Testing is essentially the same to make sure the system is right and it is the right system Both developers must choose the appropriate tool(s) for designing their respective systems COMPARISON OF USERS AND EXPERTS Attribute User Expert Dependence on system High Low to nil Cooperation Usually cooperative Cooperation not required Tolerance for ambiguity Low High Knowledge of problem High Average/low Contribution to system Information Knowledge/expertise System user Yes No Availability for system Readily available Not readily available builder KM SYSTEM DEVELOPMENT LIFE CYCLE Evaluate existing infrastructure Form the KM team Knowledge capture Design KM blueprint (master plan) Test the KM system Implement the KM system Manage change and reward structure Post -system evaluation KM SYSTEM DEVELOPMENT LC Stage Key Qs Outcome Evaluate existing What is the problem? Statement of infrastructure objectives Is system justifiable? Performance criteria Is system feasible? Strategic plan Form the KM team Who should be on Standardised team? procedure for system How will the team development function? Knowledge capture What and whose K Acquisition of K core should be captured? How would K capture proceed? 14 KM SYSTEM DEVELOPMENT LC Stage Key Qs Outcome Design KM blueprint How will K be Design of KM system represented? Hardware/ software implementation details Test plan Security Test the KM system How reliable is the Peer reviews system? Implement KM system What is the actual User friendly system operation? Training program How easy is it to use? 15 KM SYSTEM DEVELOPMENT LC Stage Key Qs Outcome Manage change and Does the system Satisfied users reward structure provide the intended solutions? Post-system evaluations Should the system be Reliable and up-to- modified? date system 16 EVALUATE EXISTING INFRASTRUCTURE System justification: Will current knowledge be lost through retirement, transfer, or departure to other firms? Is the proposed KM system needed in several locations? Are experts available and willing to help in building a KM system? Does the problem in question require years of experience and cognitive reasoning to solve? EVALUATE EXISTING INFRASTRUCTURE: System Justification (cont’d) When undergoing knowledge capture, can the expert articulate how problem will be solved? How critical is the knowledge to be captured? Are the tasks nonalgorithmic?   heuristic:learn discover, experimental, trial and error Is there a champion in the house? THE SCOPE FACTOR Consider breadth and depth of the project within financial, human resource, and operational constraints Project must be completed quickly enough for users to foresee its benefits Check to see how current technology will match technical requirements of the proposed KM system THE FEASIBILITY QUESTION A feasibility study addresses several questions: Is the project doable/achievable? Is it affordable? Is it appropriate? Is it practicable? THE FEASIBILITY QUESTION (CONT’D) Areas of feasibility: Economic feasibility determines to what extent a new system is cost-effective Technical feasibility is determined by evaluating hardware and supportive software within company’s IT infrastructure Behavioral feasibility includes training management and employees in the use of the KM system THE FEASIBILITY QUESTION (CONT’D) Traditional approach to conducting a feasibility study: Form a KM team Prepare a master plan Evaluate cost/performance of proposed KM Quantify system criteria and costs Gain user support throughout the process ROLE OF STRATEGIC PLANNING Risky to plunge with a new KM system without strategizing. Consider the following:  Vision — Foresee what the business is trying to achieve, how it will be done, and how the new system will achieve goals  Resources — Check on the affordability of the business to invest in a new KM system  Culture — Is the company’s political and social environment amenable or responsive to adopting a new KM system? MATCHING BUSINESS STRATEGY WITH KM STRATEGY Business Strategic Environment Plan Competitive threats; Impacts Regarding products or government regulations; services, market, customer threats customers, suppliers, etc. Enables Impacts Drives KM KM Strategy Technology Quality and reliability Focus on competitive of the infrastructure advantage, role of IT, and IT staff and and level of creativity resources and knowledge innovation KM TEAM FORMATION Identify the key stakeholders in the prospective KM system. Team success depends on:  Caliber of team members  Team size  Complexity of the project  Leadership and team motivation  Promising more than can be realistically delivered KNOWLEDGE CAPTURE Explicit knowledge captured in repositories from various media Tacit knowledge captured from company experts using various tools and methodologies Knowledge developers capture knowledge from experts in order to build the knowledge base Knowledge capture and transfer often carried out through teams, not just individuals KNOWLEDGE CAPTURE AND TRANSFER THROUGH TEAMS Team performs Evaluate relationship Outcome a specialized task between action and Achieved outcome Knowledge Feedback Knowledge Developer Knowledge transfer method stored in a form selected usable by others in the organization KNOWLEDGE CAPTURE ACTIVITIES IN KMSLC 1. Seek out champion 2. Locate cooperative expert 3. Apply tools to capture expert’s K 4. Design KM architecture 5. Correct for K integrity and work closely with expert for rapid prototyping 6. Work with user 7. Reinforce change 28 SELECTING AN EXPERT Knowledge base should represent expertise rather than the expert Questions facing knowledge developer:  How does one know the expert is in fact an expert?  How would one know that the expert will stay with the project?  What backup should be available in case the project loses the expert?  How would the knowledge developer know what is and what is not within the expert’s area of expertise? ROLE OF THE KNOWLEDGE DEVELOPER The architect of the system Job requires excellent communication skills, knowledge capture tools, conceptual thinking, and a personality that motivates people Close contacts with the champion Rapport with top management for ongoing support CENTRAL ROLE OF THE KNOWLEDGE DEVELOPER KNOWLEDGE WORKER CHAMPION Progress Reports Prototypes Demos Support Feedback Solutions Interactive Interface KNOWLEDGE DEVELOPER User Acceptance Rules Knowledge Testing KNOWER KNOWLEDGE BASE DESIGN OF THE KM BLUEPRINT The KM system design (blueprint) addresses several issues: System interoperability and scalability with existing company IT infrastructure Finalize scope of proposed KM system with realized net benefits Decide on required system components Develop the key layers of the KM architecture to meet company requirements. Key layers are:  User interface  Authentication/security layer  Collaborative agents and filtering  Application layer  Transport Internet layer  Physical layer TESTING THE KM SYSTEM Verification procedure: ensures that the system is right Validation procedure: ensures that the system is the right system Validation of KM systems is not foolproof IMPLEMENTING THE KM SYSTEM Converting a new KM system into actual operation This phase includes conversion of data or files This phase also includes user training Quality assurance is paramount, which includes checking for:  Reasoning errors  Ambiguity  Incompleteness  False representation (false positive and false negative) MANAGE CHANGE & REWARD STRUCTURE Goal is to minimize resistance to change Resisters of Change include the following:  Experts  Regular employees (users)  Troublemakers  Narrow-minded superstars  Resistance via projection, avoidance, or aggression POSTSYSTEM EVALUATION Assess system impact in terms of effects on:  People  Procedures  Performance of the business Areas of concern  Quality of decision making  Attitude of end users  Costs of Knowledge processing and update POSTSYSTEM EVALUATION How has KM system changed accuracy and timeliness of decision making? Has the new system caused organisational changes? How constructive have they been? How has the new KM system affected the attitude of the end users? In what way? How has the new KM changed the cost of operating the business? In what way KM affected relationships between end users in the organisation? 37 SUMMARY Building a KM system can be viewed as a life cycle Conventional and KM systems’ development life cycles differ Conventional and KM systems’ development life cycles are also similar K capture involves elicitation, analysis, and interpretation of the K that a human expert uses Rapid prototyping Verification and validation after KM blueprint Update and modify system as new K is captured Most barriers to KM are non technical 38

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