Becerra-Fernandez & Sabherwal: Chapter 1 Introducing Knowledge Management What is Knowledge Management?  Knowledge management (KM) may simply be defined as doing g what is needed to g 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. Forces Driving Knowledge Management Increasing Domain Complexity: • Intricacy of internal and external processes, increased competition, and the rapid advancement of technology all contribute to increasing domain complexity. Accelerating Market Volatility: • The pace of change, or volatility, within each market Th f h g l tilit ithi h k t domain has increased rapidly in the past decade. Intensified Speed of Responsiveness: • The time required to take action based upon subtle changes within and across domains is decreasing. Diminishing Individual Experience: • High employee turnover rates have resulted in individuals with decision‐making authority having less tenure within their organizations than ever before. 1 Knowledge Management Systems  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 Systems Knowledge management mechanisms are organizational or structural means used to promote knowledge management. The use of information technologies to support KM mechanisms enables dramatic improvement in KM. Knowledge Management Systems  KM systems classification based on observations on the KM systems implementations:     Knowledge Application Systems (Chapter 6) Knowledge Capture Systems (Chapter 7) Knowledge Sharing Systems (Chapter 8) Knowledge Discovery Systems (Chapter 9) 2 Knowledge Management Systems  Artificial intelligence and machine learning technologies g ((Chapters p 7-12)) important p role in the KM processes, enabling the development of KMS  Experience management basically experience develops over time, to coalesce into more general experience, which then combines into general knowledge Issues in Knowledge Management  “Effective KM is not about making a choice between “software vs. wetware, classroom vs. hands-on, formal vs informal, vs. informal technical vs. vs social…uses 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. Effective Knowledge Management  80% - Organizational culture and human factors  20% - Technology 3 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. Text Overview  13 chapters divided into 3 parts  Part a t I - Principles c p es o of Knowledge o edge Management a age e t  Part II: Knowledge Management Technologies and Systems.  Part III: Management and the Future of Knowledge Management. Becerra-Fernandez: Chapter 2 The Nature of Knowledge 4 What is Data?  Data comprises facts, observations, or perceptions  Data represents raw numbers or assertions What 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 What is Knowledge?  A justified true belief (Nonaka and Takeuchi)  It is different from data & information  Knowledge is at the highest level in a hierarchy with information at the middle level, and data to be at the lowest level  It is the richest, deepest & most valuable of the three  Information with direction 5 Data, Information, and Knowledge Knowledge Value Zero Low Medium Data High Very High Information Data, Information, Knowledge and Events Knowledge Information System Information Use of information Knowledge K Data Decision Events Procedural and Declarative Knowledge  Declarative knowledge (substantive knowledge) focuses on beliefs about relationships p among g variables  Procedural knowledge focuses on beliefs relating sequences of steps or actions to desired (or undesired) outcomes 6 Tacit and Explicit Knowledge  Tacit knowledge includes insights, intuitions, and hunches  Explicit knowledge refers to knowledge that has been expressed into words and numbers  We can convert explicit knowledge to tacit knowledge General and Specific Knowledge  General knowledge is possessed by a large number of individuals and can be transferred easilyy 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 Knowledge  Technically specific knowledge is deep knowledge about a specific p area  Contextually specific knowledge knowledge refers to the knowledge of particular circumstances of time and place in which work is to be performed 7 Different Types of Knowledge Reservoirs of Knowledge Knowledge Reservoirs Artifacts People Organizational Entities Organizational Units Individuals Practices Technologies Repositories Groups Organizations Inter-organizational Networks Different views of knowledge  Subjective View of knowledge  Knowledge as State of Mind  Knowledge as Practice  Objective View of knowledge  Knowledge as Objects  Knowledge as Access to Information 8 Knowledge in Ancient Greece  Episteme  Knowledge o edge (as co content) e )  Epistemology (theory of knowledge)  Techné  Technique / Know-how (knowing as action)  Technology (theory of technique)  Phronesis  Practical/social wisdom Shift in the meaning of the concept knowledge Knowledge Beliefs Beliefs ACTION Truth Truth Knowledge ACTION 9 Continuum Know-how Kogut & Zander (1992) Know-how Nonaka (1994) Tacit Blackler (1995) Embodied Spender (1998) Individual/Social Implicit Brown & Duguid (1998) Know-how Davenport & D Prusak (1998) Experience Cook & Brown (1999) Knowing (tacit) Pfeffer (1999) Knowing-Doing Hassard & Kelemen (2002) Newell (2002) Orlikowski (2002) Know-that Information Explicit Embrained Encultured Embedded Encoded Individual/Social Explicit Social Knowledge Know-that Insight Processual – knowing the world Values Data Information Knowledge (explicit) Discourse Knowledge Cultural Practices Being-in-the-World Processual perspective Structurual perspective Knowing Knowledge Jashapara: Knowledge Management © Pearson Education (2004) Knowledge Management genres  Organizational Learning  Moving from not-knowing to knowing  Senge – 5th Discipline  Knowledge Logistics  Getting the right knowledge to the right place at the right time.  Davenport and Prusak – Working Knowledge  Intellectual Capital  Measuring the value of knowledge  Stewart – Intellectual Capital 10 Becerra-Fernandez: Chapter 3 & 4 Knowledge Management Foundations and Knowledge Management Solutions Knowledge Management Solutions and Systems  Knowledge Management Solutions  Ways in which KM can be facilitated  4 Levels of KM solutions:     KM processes KM systems KM mechanisms and technologies KM infrastructure  Knowledge Management Systems  Integration of technologies and mechanisms that are developed to support KM processes An Overview of Knowledge Management Solutions KM Processes KM Systems KM Mechanisms and Technologies KM Infrastructure 11 Knowledge Management Processes Discovery • Combination • Socialization Sharing • Socialization • Exchange Application • Direction • Routines Capture • Externalization • Internalization Knowledge Discovery Knowledge Capture Knowledge Sharing Knowledge Application KM Processes Combination Socialization KM Systems Knowledge Capture Systems Knowledge Discovery Systems KM Mechanisms KM Infrastructure Internalization Externalization Analogies and metaphors Brainstorming retreats On-the-job training Face-to-face meetings Apprenticeships Employee rotation Learning by observation …. Organization Culture Organization Structure Exchange Direction Knowledge Sharing Systems Knowledge Application Systems Decision support systems Web-based discussion groups Repositories of best practices Artificial intelligence systems Case-based reasoning Groupware Web pages … IT Infrastructure Common Knowledge Routines KM Technologies Physical Environment Processes, Mechanisms, and Technologies 12 Knowledge Discovery Knowledge Capture Knowledge Sharing Knowledge Application KM Processes Combination Socialization Internalization Externalization Knowledge Discovery Systems KM Systems KM Mechanisms KM Infrastructure Knowledge Capture Systems Organization Structure Direction Knowledge Sharing Systems IT Infrastructure Common Knowledge Routines Knowledge Application Systems Decision support systems Web-based discussion groups Repositories of best practices Artificial intelligence systems Case-based reasoning Groupware Web pages … Analogies and metaphors Brainstorming retreats On-the-job training Face-to-face meetings Apprenticeships Employee rotation Learning by observation …. Organization Culture Exchange KM Technologies Physical Environment KM Infrastructure Knowledge Discovery Knowledge Capture Knowledge Sharing Knowledge Application KM Processes Combination Socialization KM Systems y Knowledge Discovery Systems KM Mechanisms KM Infrastructure Internalization Externalization Knowledge Capture Systems Analogies and metaphors Brainstorming retreats On-the-job training Face-to-face meetings Apprenticeships Employee rotation Learning by observation …. Organization Culture Organization Structure Exchange Direction Knowledge Sharing Systems Knowledge Application Systems Decision support systems Web-based discussion groups Repositories of best practices Artificial intelligence systems Case-based reasoning Groupware Web pages … IT Infrastructure Common Knowledge Routines KM Technologies Physical Environment 13 Becerra-Fernandez: Chapter 11 Factors Influencing Knowledge Management Universal vs Contingency Universal view of KM Contingency view of KM  There is a single best approach of  managing knowledge, which should be adopted by all organizations in all circumstances   Knowledge sharing is recommended as useful to all organizations, although we believe that direction may sometimes represent an equally effective but more efficient alternative. Contingency view suggests that no one approach is best under all circumstances Contingency perspective considers the path to success to include multiple alternative paths, with success achieved only when the appropriate path is selected Contingency Factors & KMS Contingency Factors 3 2 KM Solutions KM Infrastructure • • • • • Organization Culture Communities Of Practice Organization Structure IT Infrastructure Organizing Knowledge 1 KM Systems KM Mechanisms 4 KM Technologies 5 • • • • Knowledge Knowledge Knowledge Knowledge Discovery Systems Capture Systems Sharing Systems Application Systems KM Processes 6 • • • • Knowledge Knowledge Knowledge Knowledge Discovery Capture Sharing Application 7 14 Categories of Contingency Factors Environmental Characteristics Organizational Characteristics Task Characteristics Knowledge Management Knowledge Characteristics Task Characteristics  KM processes that are appropriate for an organizational g subunit depend p on the nature of its tasks  Task Uncertainty  Task Interdependence Task Uncertainty  Task uncertainty is argued to reduce the organization’s ability to develop routines, and h hence kknowledge l d application li ti would ld d depend d on direction  When task uncertainty is high, externalization and internalization would be more costly due to changing problems and tasks  When task uncertainty is low routines can be developed for the knowledge supporting them 15 Effects of Task Characteristics on KM Processes Internalization Externalization Direction Routines High Task In nterdependence Exchange Combination Socialization Direction Routines Exchange Combination Routines I t Internalization li ti Externalization Routines Direction Socialization Direction Low Low Task Uncertainty Routines Internalization Externalization Exchange Combination High Direction Socialization Task Interdependence  Indicates the extent to which the subunit’s achievement of its g goals depends p on the efforts of other subunits  Performance of interdependent tasks relies mainly on dynamic interaction in which individual units of knowledge are combined and transformed through communication and coordination across different functional groups Knowledge Characteristics  Explicit vs. tacit  Procedural vs. declarative  General vs. specific 16 Effects of Knowledge Characteristics on KM Processes Procedural or Declarative Procedural Discovery • Explicit: Combination • Tacit: Socialization Sharing • Tacit: Socialization • Explicit: Exchange Application • Tacit/Explicit: Direction • Tacit/Explicit: Routines Capture • Tacit: Externalization • Explicit: Internalization Procedural and Declarative Knowledge  Procedural knowledge focuses on the processes or means that should be used to p perform the required q tasks, such as how to perform the processes needed to achieve the specific product design  Declarative knowledge focuses on beliefs about relationships among variables Effects on KM Processes 17 Identification of Appropriate KM Solutions  Assess the contingency factors.  Identify the KM processes based on each contingency factor.  Prioritize the needed KM processes.  Identify the existing KM processes.  Identify the additional needed KM processes.  Assess the KM infrastructure.  Develop additional needed KM systems, mechanisms, and technologies. Appropriate Circumstances for Various KM Processes Prioritizing KM Processes for Doubtfire Computer Corporation 18