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1 KNOWLEDGE MANAGEMENT Frankfurt FFFM MARCH- 2008, SEPT.- 2009, MARCH- 2013 Prof.Dr. Irene Martín-Rubio.

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Presentation on theme: "1 KNOWLEDGE MANAGEMENT Frankfurt FFFM MARCH- 2008, SEPT.- 2009, MARCH- 2013 Prof.Dr. Irene Martín-Rubio."— Presentation transcript:

1 1 KNOWLEDGE MANAGEMENT Frankfurt FFFM MARCH- 2008, SEPT , MARCH Prof.Dr. Irene Martín-Rubio

2 2 KM - OUTLINE Definitions  Data, Information, Knowledge  Knowledge components Knowledge A corporate Asset  Corporate Size & Knowledge Management  Tacit vs. Explicit Knowledge The Spiral of Knowledge  Socialization, Internalization, Combination and Articulation  From Metaphor to Model  From Chaos to Concept KNOWLEDGE MANAGEMENT  KNOWLEDGE GENERATION  KNOWLEDGE COORDINATION  KNOWLEDGE TRANSFER  KNOWLEDGE USE CKO vs. Knowledge Broker Innovation: Invent + Commercialization Protection explicit knowledge- Patent market

3 3 DEFINITIONS DATA INFORMATION KNOWLEDGE  COMPONENTES

4 4 DATA DISCRETE, OBJECTIVE FACTS ABOUT EVENTS STRUCTURE RECORDS OF TRANSACTIONS TOO MUCH DATA CAN MAKE IT HARDER TO IDENTIFY AND MAKE SENSE OF THE DATA THAT MATTERS. DATA DESCRIBES ONLY A PART OF WHAT HAPPENED; IT PROVIDES NO MEANING, NO JUDDGEMENT OR INTERPRETATION MODERN ORGANIZATIONS STORE DATA IN SOME SORT OF TECHNOLOGY SYSTEM  CENTRALIZED  OR  DECENTRALICED DATA MANAGEMENT  SPEED, COST AND CAPACITY How much does it cost to capture or retrieve a piece of data? How quickly can we get it into the system or call it up? How much will the system hold?  RELEVANCE AND CLARITY Do we have access to it when we need it? Is it what we need? Can we make sense out of it? DATA IS THE RAW MATERIAL FOR DECISION MAKING, BUT IT CANNOT TELL YOU WHAT TO DO.

5 5 INFORMATION IT IS A MESSAGE IT IS DATA ENDOWED WITH RELEVANCE AND PURPOSE. IT HAS MEANING. INFORM: “GIVE SHAPE TO”  INFORMATION IS MEANT TO SHAPE THE PERSON WHO GETS IT, TO MAKE SOME DIFFERENCE IN HIS OUTLOOK OR INSIGHT. SENDER RECEIVEER INFORMATIOIN

6 6 INFORMATION IT MOVES AROUND ORGANIZATIONS THROUGH  HARD NETWORKS: wires, satellite dishes, post offices, addresses, electronic mailboxes, delivery vans  SOFT NETWORKS: it is less formal and visible. Ex. Someone handing you a note or a copy of article marked “FYI”

7 7 INFORMATION DATA BECOMENS INFORMATION WHEN ITS CREATOR PROCESS BY:  CONTEXTUALIZED: PURPOSE  CATEGORIZED: KEY COMPONENTS, UNITS OF ANALYSIS  CALCULATED  CORRECTED  CONDENSED: SUMMARIZE

8 8 KNOWLEDGE COMPLEX CONCEPT, MANY PHILOSOFICAL & EPISTOMOLOGICAL DEFINITIONS WORKING DEFINITION, PRAGMATIC DESCRIPTION  Knowledge is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information.  In organizations, if often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices and norms. Depending on how scientifist track it, knowledge can be seen as  PROCESS: (ORGANIZATIONAL LEARNING)  STOCK: (KNOWLEDGE)

9 9 KNOWLEDGE Knowledge derives from information as information derives from data, by this transformations.  COMPARISON of this information to other situations  CONSEQUENCES of the information for decision and actions  CONNECTIONS  CONVERSATION: What do other people think about this information These knowledeg-creating activities take place within and between humans.  While we find data in records, and information in messages, we obtain knowledge from individuals or groups of knowers, or sometimes in organizational routines.  It is delivered through structured media such as books and documents, and person-to-person.

10 10 KNOWLEDGE - COMPONENTS EXPERIENCE  Knowledge develops over time, through experience that includes what we absorb from courses, books, and mentors as well as informal learning.  It provides a historical perspective from which to view and understand new situations and events.  Knowlege born of experience recognizes familiar patterns and can make connections between what is happening now and before. GROUND TRUTH  It means knowing what really works and what doesn’t, on the ground, rather than from the heights of theory or generalization.  Knowledge of the everyday, complex, often messy reality of work is generally more valuable than theories about it. COMPLEXITY  Knowledge is not a rigid structure that excludes what doesn’t fit, it can deal with Certainty and clarity often come at the price of ignoring essential factors (Being both certain and wrong is a common occurrence).  In a dynamic, competitive, changing environment, ullusions of accuracy are short-lived, they live to nonadaptive-action  Fuzzy logic. JUDGMENT Knowlegde contains judgment. Not only can it judge new situations and information in light of what is already known, it judges and refines itself in response to new situations. RULES OF THUMB: Heuristics  They are shortcuts to solutions to new problems that resemble problems previously solved. They are efficent guides to complex situations.  AS veterans drivers of cars, rapidly accomplishing a series of complex actions without having to thing about them, as a beginner would The veteran driver develops an INTUITIVE sense of what to expect on the road. VALUES AND BELIEFS  They determine what the knower see, absorbs, and concludes from his observations.  Ex. : Someone who values the bustle of urban life may find energy and variety in a crowded city street. Someone who prefers rural quiet may see only chaos and danger in the same scene. A publishing executive who values risk and change may see a new opportunity in the same on-line technology than a competitor views as a threat to traditional successful print products.

11 11 KNOWLEDGE Nonaka & Takeuchi: KNOWLEDGE, UNLIKE INFORMATION IS ABOUT BELIEFS AND COMMITMENT. THE POWER OF KNOWLEDGE TO ORGANIZE, SELEC, LEARN AND JUDGE COMES FROM VALUES AND BELIEFS AS MUCH AS, AND PROBABLY MORE THAN, FROM INFORMATION AND LOGIC.

12 12 DATA, INFORMATION, KNOWLEDGE SIGN DATA INFORMATION KNOWLEDGE ACTION COMPETENCE + sintaxis +PROCESS + EXPERIENCE, VALUES + WILL MANAGEMENT +PROPER + OUTSTANDING ACTION

13 A CORPORATE ASSET CORPORATE SIZE & KNOWLEDGE MANAGEMENT TACIT KNOWLEDGE VS. EXPLICIT K. KNOWLEDGE 13

14 14 KNOWLEDGE AS A CORPORATE ASSET Knowledge is not new.  Studies have shown that managers get two-thirds of their information and knowledge from face-to-face meetings or phone converstations.  Only one-third comes from documents Explicitic recognizing knowledge as a corporate asset is new.  INVEST, MANAGE, GET VALUE FROM IT KNOWLEDGE can provide a sustainable advantage. It generates new leves of quality, creativity or efficiency. Unlike material assets, which decrease as they are used, knowledge assets increase with use:  Ideas breed ideas, and shared knowledge stays with the giver while it enriches the receiver.  Only knowledge resources have unlimited potential for growth In a world with physical limits, it is the discovery of big idea together with the discovery of millions of little ideas that makes persistent economic growth possible. Ideas are the cues that let us to combine limited physical resources in arrangements that are ever more valuable.

15 15 CORPORATE SIZE AND KM In a small, localized company  a manager probably knows who has the experience in a particular aspect of the business and can walk across the hall and talk to him. The maximum size of an organization in which people know one another well enough to have a reliable grasp of collective organizational knowledge is people The stock of knowledge in a global enterprise with scattered offices and plants and a complex mix of products and functions is vast, but “How do you find what you need?  COMPUTER NETWORKS AND KNOWLEDGE EXCHANGE This new information technology is only the pipeline and storage system for knwoelde exchange, it can not guarantee or even promote knowledge generation or knowledge sharing  CORPORATE CULTURE for knowledge sharing A CASE: BRIHIS PETROLEUM’S VIRTUAL TEAMWORK PROGRAM

16 16 TACIT VS. EXPLICIT KNOWLEDGE EXPLICIT K.: It is formal and systematic. For this reason, it can be easily communicated and shared, in product specificaions or a scientific formula or a computer program. TACIT K.: It is highly personal. It is hard to personalize and, therefore, difficult to communicate to others.  “We can know more than we can tell”  It is deeply rooted in action in an individual’s commitment to a specific context –a craft or profession, a particular technology or product market, or the activities of a work group or team.  Constis partly of technical skills: informal, hard-to-pin skills captured in the term “know how”, but unable to articulate the scientific or technical principles behind what he knows.  It has a cognitive dimension: Mental models, beliefs taked from granted, and therefore cannot easily articulaate them. This implicit models profoundly shape how we perceive the world around us.

17 THE SPIRAL OF KNOWLEDGE 17

18 18 THE SPIRAL OF KNOWLEDGE SPIRAL OF KNOWLEDGE FROM METAPHOR TO MODEL FROM CHAOS TO CONCEPT

19 19 SPIRAL OF KNOWLEDGE INTERNALIZATIONSOCIALIZATION ARTICULATIONCOMBINATION INDIVIDUAL COLLECTIVE TACIT KNOWLEDGE EXPLICIT KNOWLEDGE

20 20 SPIRAL OF KNOWLEDGE 4 fasic patterns for creating knowledge: From tacit to tacit: SOCIALIZATION 1. From explicit to explicit: ARTICULATION 2. From tacit to explicit: COMBINATION 3. From Explicit to tacit: INTERNALIZATION

21 21 SPIRAL OF KNOWLEDGE 1. FROM TACIT TO TACIT Sometimes, one individual shares tacit knowledge directly with another. SOCIALIZATION:The apprentice learns the master’s skills. Example: When an apprentice in an Hotel baker learn tacit skills through observation, imitation and practice. Because their knowledge never becomes explicit, it cannot easily be leveraged by the organization as a whole.

22 22 SPIRAL OF KNOWLEDGE 2. FROM TACIT TO EXPLICIT ARTICULATION The individual is able to articulate the foundations of his tacit knowledge Ex: The apprentices translates these secrets into explicit knowledge that he can communicate to her team members and others at the company.

23 23 SPIRAL OF KNOWLEDGE 3. FROM EXPLICIT TO EXPLICIT An individual can also combine discrete pieces of explicit knowledge into a new whole: COMBINATION Example: The team standardizes this knowledge, putting it together in a new product, or into a manual.

24 24 SPIRAL OF KNOWLEDGE 4. FROM EXPLICIT TO TACIT INTERNALIZATION As new explicit knowledge is shared through an organization, other employees begin to internalize it – that is, they use it to broaden, extend and reframe their own tacit knowledge. Example: Through the experience of creating a new product, the apprentices and his team members enrich their own tacit knowledge base. In particular, they come to understand in an extremely intuitive way that products like the home bread-making machine can provide genuine quality.

25 25 SPIRAL OF KNOWLEDGE SOCIALIZATION ARTICULATION COMBINATION INTERNALIZATION

26 26 From Metaphor to Model To convert tacit knowledge into explicit knowledge means finding a way to express the inexpresible. Tool: the store of figurative language and symbolism that anybody cand draw from to articulate their intuitions and insights.  METAPHORS: Distintive method of perception It is a way for individuals grounded in different contexts and with different experiences to understand something intuitively through the use of imaginations and symbols People put together what they know in new ways and begin to express what they know but can not yet say. Metaphors merges two different and distant areas of experience ito a single, inclusive image or symbol “Two ideas in one phrasse”  ANALOGY Whereas metaphor is mostly driven by intuition and links images that a t first glance seem remote from each other,analogy is a more structured process of reconciling contradictions and making distinctions. Analogy is an intermediate step betweem pure imagination and logical thinking.  MODEL The last step is to create a Model. In the model, contradictions get resolved and concepts become transferable throug consistent and systematic logic.

27 27 FROM CHAOS TO CONCEPT The confusion created by the inevitable discrepancies in meaning that occur in any organization might seen like a problem. In fact, it can be a rich source of new knowledge –if a company knows how to manage it. The key to doing so is continuously challenging employees to reexamine what they take for granted. Ambiguity can prove extremely useful as a source of alternative meanings, a fresh way to think about things, a nes sense of direction. New knowledge is born in chaos.

28 28 FROM CHAOS TO CONCEPT Orient this chaos: VISION AND PURPOSE  What are we try to learn? What do we need to know? Where should we be going? Who are we? Vision of senior managers As team leaders, middle managers are the intersection of the vertical and horizontal flows of information in the company.  They serve as a bridge between the visionary ideals of the top and the often chaotic market reality of those of the front line of the business Middle managers syntesized the tacit knowledge of both frontline employees and senior executives, made it explicit, and incorporated it into new technologies and products. In this respect, they are the true “knowledge engineers” of the knowledge- creating company.

29 Knowledge Generation Knowledge Codification & Coordination Knowledge Transfer Knowledge Use CKO vs. Knowledge Brokers KNOWLEDGE MANAGEMENT 29

30 30 KNOWLEDGE MANAGEMENT KNOWLEDGE GENERATION KNOWLEDGE CODIFICATION AND COORDINATION KNOWLEDGE TRANSFER KNOWLEDGE USE CKO: Chief Knowledge Officer Knowledge Brokers

31 31 KNOWLEDGE GENERATION SPECIFIC ACTIVITIES AND INITIATIVES FIRMS UNDERTAKE TO INCREASE THEIR STOKC OF CORPORATE KNOWLEDGE: ACQUISITION:  PURCHASE ANOTHER FIRM WITH THE KNOWLEDGE  HIRE PEOPLE WITH THE KNOWLEDGE,  RENTAL (SUPPORT AN UNIVERSITY) !!! RETAIN THE KNOWLEDGE DEDICATED RESOURCES  STABLISH UNITS OR GROUPS SPECIFICALLY FOR THE PURPOSE R&D Dpt. FUSION  It brings together people with different perspectives to work on a problemor project, forcing them to come up with a joint answer.  It introduces complexity and even conflict to create new knowledge: CREATIVE CHAOS ADAPTATION  “Adapt or die”: Instill a sense of crisis before it exists  The crisis in the environment act as catalysts for knowledge generation  Employees who are willing and able to learn new things are vital to an adapting company KNOWLEDGE NETWORKING  Communities of knowers, brought together by common interests, usually talk together in person, on the telephone, and via and groupware to share expertise and solve problems together.  When networks of this kind share enough knowledge in common to be able to communicate and colloborate effectively, their ongoing conversation often generates new knowledge within firms.

32 32 KNOWLEDGE CODIFICATION & COORDINATION The aim of codification is to put organizational knowledge into a form that makes it accesible to those who need it (explicit, portable and easy to unerstand). The codification process for the richest tacit knowledge in organizations is generally limited to locating someone with the knowledge, pointing the seeker to it, and encouraging them to interact. MAP OF KNOWLEDGE goes beyond conventional department boundaries. That means that can lead to political tensions in the organization EXPERT SYSTEMS represents an explicit attepmt to capture or imitate human knowledge by transferring it to a formalized rules-based system. But,even with advances in fuzzy logic, computers are not yet well suited to ambiguous and intuitive operations where the rules, if they exist at all, are much harder to define. EMBEDDED KNOWLEDGE: Some knowledge that is quite complex and initially tacit can be externalized and embedded in a company’s products or services.

33 33 KNOWLEDGE TRANSFER Spontaneous, unstructured knowledge transfer is vital to a firm’s success. Although the term “KM” implies formalizzed transfer,one of its essential elements is developing specific strategies to encourages such spontaneous exchanges. METHODS FOR KNOWLEDGE SHARING should suit the organizational (and national) culture TRANSFER= TRANSMISSION+ABSORPTION

34 34 KNOWLEDGE USE KNOWING IS NOT THE SAME AS DOING. Transmission and Absorption have no useful value  if the knowlede does not lead to some change in behavior,  or the development of some idea that leads to new behavior Resistance to change is powerful, even in the face of indisputable objective evidence that a particular change makes sense.

35 35 CKO:Chief Knowledge Officers CLO Chief Learning Officers Director of Intellectual Capital Senior Management Roles on the level of Chief Information Officers, heads of the human resource organization and other funcitional and business unit leaders. Responsibilities  Building a knowledge culture: education, incentive programs and management example  Creating a knowledge management infrastructure Workstations,networks, dabases, search engines,deskt-publishing tools, Web- based intranet Human resources issues Deveolopment and maintenancce of knowledge bases in different functions and departments.  Making it all pay off economically Figures and stories, about how knowledge sharing increase sales, are the weapons to justify budget Intellectual capital report

36 NASA KNOWLEDGE MANAGEMENT AND CKO Ex.: NASA: ome/index.html ome/index.html NASA’s Knowledge Imperative By Ed Hoffman “Like all large, knowledge-intensive organizations, NASA faces continuous challenges identifying, capturing, and sharing what it knows effectively. Knowledge is the coin of the realm at NASA. Need to understand something about engine cutoff sensors, the physiological impact of extended stays in low-Earth orbit, or how to drive a rover on Mars? That kind of specialized expertise.” … I will remain the director of the Academy of Program/Project and Engineering Leadership as I assume the responsibilities of serving as NASA’s first CKO. This is a logical extension of the knowledge services the Academy began providing over a decade ago. I look forward to engaging deeply with the community of dedicated professionals that gathered in February to ensure that our technical workforce has the knowledge it needs to achieve mission success. As always, please feel free to contact me if you would like to share thoughts or ideas” 36

37 KNOWLEGE BROKER Knowledge brokers: bridging the gap: data-information-knowledge- competence- intermediary activity that takes place between and within the spheres of science, policy and civil society in order to bridge the research ‐ to ‐ practice gap They are not inside the organization as CKO, they are intermiediaries. Brokerage roles The roles of individuals/groups/organisation performing KB could be quite divergent. With reference to a knowledge broker typology framework (Gould & Fernandez ) the brokers’ roles could be categorised as ‘representatives’, ‘gatekeepers’, ‘liaison brokers’, ‘coordinators’, or ‘itinerant brokers’ – according to which domain they belong to. In the ‘co ‐ ordinator’ framework all the actors including the broker and the source of knowledge are in the same group. In the ‘itinerant broker’ type the broker mediates between actors in the same group, but the broker is not part of this group. The ‘gatekeeper’ screen external knowledge to distribute it within their own group. ‘Representative’ role is given if a group delegates the brokering role of external knowledge to someone in the group. ‘Liaison’ is when they knowledge is brokered across different groups, neither of which the brokers are members of. oadHP_March2012.pdf 37

38 The Rise of the Knowledge Broker “ Knowledge brokers are people or organizations that move knowledge around and create connections between researchers and their various audiences. This commentary reviews some of the literature on knowledge brokering and lays out some thoughts on how to analyze and theorize this practice. Discussing the invisibility and interstitiality of knowledge brokers, the author argues that social scientists need to analyze more thoroughly their practices, the brokering devices they use, and the benefits and drawbacks of their double peripherality. The author also argues that knowledge brokers do not only move knowledge, but they also produce a new kind of knowledge: brokered knowledge.” (Meyer,M, 2010) contents/publications/D2.1_Synthesis_report_DRAFT_uploadHP_M arch2012.pdf contents/publications/D2.1_Synthesis_report_DRAFT_uploadHP_M arch2012.pdf 38

39 INNOVATION Innovation Invent + Commercialization Commercialization: patent, technology ->Knowledge Brokers Open innovation:  the use of purposive inflows and outflows of knowledge to accelerate internal innovation and to expand the markets for external use of innovation, respectively”. (Chesbrought 2003) Geographical Clusters 39

40 CLUSTERS – open innovation FIRMS & LOCATION  GEOGRAPHICALLY CONCENTRATED NETWORKS WHERE NEW KNOWLEDGE IS CREATED AND ORGANIZATIONAL LEARNING DEVELOPED Ex: 40

41 TECHNOLOGY, PATENT MARKET – Protection explicit knowledge “Just as it is often said that patent information is a gold mine of technology, it would be helpful if people wanting to use patents had a map of what is where” Law for Intellectual property –history 41

42 42 THANK YOU FOR YOUR ATENTION. Suggestions? Ideas? Questions?


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