chapter 9
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CHAPTER 9. Knowledge Management. Introduction. What do we mean by knowledge? Class Discussion Drucker (1994): “ The knowledge society will be more competitive than anything that we have seen so far. ” - PowerPoint PPT PresentationTRANSCRIPT
CHAPTER 9
Knowledge Management
IntroductionWhat do we mean by knowledge? Class Discussion
Drucker (1994): “The knowledge society will be more competitive than anything that we have seen so far.”
Why? With knowledge being universally accessible there will be no reason for por performance.
Cyert (1991): “The most crucial variable in economic development is Knowledge.”
Introduction
Leonard-Barton (1995): “Organizations that are successful innovators are those that build and manage knowledge effectively through activities as developing shared problem-solving skill, experimentation, integrating knowledge across functional boundaries, and importing expertise from external sources.”
Knowledge Management
Ancient Collaboration at the
organizational level Could revolutionize
collaboration and computing
Opening Vignette: Knowledge Management Gives
Mitre a Sharper Edge
Mitre - knowledge management system (KMS) to leverage organizational knowledge effectively throughout the organization
Internal marketing during development Supported at the highest level Provided an important application
Organizational culture shift was critical Saved $54.91 million / invested $7.19 million
Knowledge Management
Leverages intellectual assets Delivers appropriate solutions to
anyone, anywhere Good managers have always done
this Ancient concept
DSS Insights- GEM: A DSS for Workload-Planning Decisions
Overview:
. GEM a large stevedoring company
. Schedules developed a week ahead
. Each ship is expected to arrive within 10 days. Unexpected conditions cause the schedule to be re- written
DSS Insights- GEM: A DSS for Workload-Planning Decisions
System Description:* means very important variable
Ships
. ETA
. Cargo Information
. Ship’s workload per location
. DWT
. Permitted berths
. Maximum number of elevators
. ETD*
DSS Insights- GEM: A DSS for Workload-Planning Decisions
Berth
. Equipment information
. Availability of equipment
. Maximum permitted length
. Maximum permitted draught
. Maximum permitted DWT
DSS Insights- GEM: A DSS for Workload-Planning Decisions Other characteristics
.The planner can override the system
.Each ship has a max number of elevators which can be set by the planner
System operation.Run planning scenario with no penalties.Study results.If there are ships in an unfavorable position (ETD) - manipulate penalties to improve ships position.Repeat until satisfactory
Class discussion!!!!!!
Knowledge Management
Helps organizations Identify Select Organize Disseminate TransferImportant information and expertise
within the organizational memory in an unstructured manner
Knowledge
As a form of capital, must be exchangeable among persons, and must be able to grow
Intellectual Capital- as the competence of an individual and the commitment of the individual to the organization’s goals
(competence * commitment)
Knowledge Management
Requires a major transformation in organizational culture to
create a desire to share
Knowledge
Information that is contextual, relevant, and actionable
Knowledge is INFORMATION IN ACTION
Higher than data and information
Knowledge Types
Advantaged knowledge Base knowledge Trivial knowledge Explicit knowledge Tacit knowledge
Knowledge Types
Advantaged Knowledge- Knowledge that provides competitive advantageBase Knowledge- Knowledge that is integral to an organization, providing it with short-term solutions (i.e. best practices)Trivial knowledge- knowledge that has no impact on the organization
Explicit Knowledge
Objective, rational, technical Easily documented Easily transferred / taught /
learned
Tacit Knowledge
Subjective, cognitive, experiential learning
Hard to document Hard to transfer / teach / learn
Involves a lot of human interpretation
DATA
ProcessedINFORMATION
Relevant and actionable
KNOWLEDGE
Relevant and actionable data
Data, Information and Knowledge
Knowledge Has
Extraordinary leverage and increasing returns
Fragmentation, leakage, and the need to refresh
Uncertain value Uncertain value sharing
Organizational Learning and
Organizational Memory
Group memory Learning The learning organization Organizational memory Organizational learning Organizational culture
Organizational Memory
Individual wells Information well Culture well Transformation well Structural well Ecology well
Organizational Learning Focuses
Knowledge source Product-process focus Documentation mode Dissemination mode Learning focus Value chain focus Skill development focus
Organizational Culture
Culture is a pattern of shared basic assumptions
Most important aspect of KM success
Why don’t people share knowledge?
Knowledge Management (KM)
A process of elicitation, transformation, and diffusion of knowledge throughout an enterprise so that it can be shared and thus REUSED
Helps organizations find, select, organize, disseminate, and transfer important information and expertise
Transforms data / information into actionable knowledge to be used effectively anywhere in the organization by anyone
How Core Competency is Linked to Explicit and Tacit Knowledge
TacitKnowledge
Policies, patents,decisions,stra tegies, IS, whitepapers, etc.
Conver t tacit knowledge intoarticulated and measurableexplicit knowledge
Core Competencies of the Organization
Explicit Knowledge
Expertise, know-how, ideas,organization culture, values, etc.
Process of explicationmay generate new tacitknowledge
TacitKnowledge
KM Objectives
Create knowledge repositories Improve knowledge access Enhance the knowledge
environment Manage knowledge as an asset
KMS Manage
Knowledge creation through learning Knowledge capture and explication Knowledge sharing and
communication through collaboration Knowledge access Knowledge use and reuse Knowledge archiving
Knowledge Repository
Not a database Not a knowledge base (like for
ES)
A collection of internal and external knowledge
Knowledge Repository Types
External Structured internal knowledge Informal internal knowledge
KM Activities
Externalization Internalization Intermediation Cognition
KM Features
Create a knowledge culture Capture knowledge Generate knowledge Explicate (and digitize)
knowledge Share and reuse knowledge Renew knowledge
Cyclic Model of KM
Create knowledge Capture knowledge Refine knowledge Store knowledge Manage knowledge Disseminate knowledge
Cyclic Model of KM
ManageKnowledge
StoreKnowledge
DisseminateKnowledge
RefineKnowledge
Create Knowledge
CaptureKnowledge
KM Examples Mitre Dow Chemical Company Xerox Chrysler Monsanto Chevron Buckman Laboratories KPMG Ernst & Young Arthur Andersen Andersen Consulting
Why Adopt KM
Cost savings Better performance Demonstrated success Share Best Practices Competitive advantage
Chief Knowledge Officer (CKO)
Maximize firm’s knowledge assets
Design and implement KM strategies
Effectively exchange knowledge assets
Promote system use
KM Development
Need a knowledge strategy Identify knowledge assets
KM Development
1. Identify the problem2. Prepare for change3. Create the team4. Map out the knowledge5. Create a feedback mechanism6. Define the building blocks7. Integrate existing information
systems
Strategies for Successful KM
Implementation
1. Establish a KM methodology2. Designate a pointperson3. Empower knowledge workers4. Manage customer-centric
knowledge5. Manage core competencies
More Strategies
6. Foster collaboration and innovation
7. Learn from best practices8. Extend knowledge sourcing9. Interconnect communities of
expertise (communities of practice)
10.Report the measured value of knowledge assets
KM Methods, Technologies, and
Tools Email or messaging Document management Search engines Enterprise information portal Data warehouse Groupware Workflow management Web-based training Others
How to KM
Integrate the technologies to manage knowledge effectively
KM Tool Categories
Information architecture Technical architecture Application architecture
KM Software Knowware still developing but…
DecisionSuite Wincite DataWare KnowledgeX Knowledge Share
KM Success
Economic performance Technical and organizational infrastructure Standard, flexible knowledge structure Knowledge-friendly culture Clear purpose and language Change in motivational practices Multiple channels for knowledge transfer Worthwhile level of process orientation Nontrivial motivational encouragement Senior management support
Measuring Success
Balanced Scorecard Skandia Navigator Economic Value Added Inclusive Valuation
Methodology
KM Failure Causes
1. Unclear definition of knowledge2. Overemphasis on knowledge
stock, not flow3. Belief that knowledge exists
outside people’s heads4. Not recognizing the importance
of managing knowledge5. Failure to manage tacit
knowledge
More Failure Causes
6. Failure to disentangle knowledge from its uses
7. Downplaying reason and thinking8. Focusing on the past and present, not
the future9. Failure to recognize the importance of
experimentation10.Substituting technology contact for
human interface11.Overemphasis on measuring
knowledge, not its outcomes
KM and AI
Can use AI in KM Can use KM in AI Data mining can create
knowledge
Electronic Document Management
A KM for documents Everyone is on the same page Documents are up to date Simple example: corporate
phonebook
Lower costs Better performance
The Knowledge-Based View of Decision Making
Accepting Messages: see next slide
A decision maker (human-being) can accept stimuli from the environment
The stimuli are messages that carry knowledge (information)
Some messages have a direct and immediate impact on the decisions being manufactured
Other messages can be:. discarded. passed along to others and or other places. stored for future use
The Knowledge-Based View of Decision Making
Issuing Messages
The decision maker can issue messages to the surroundings:
. other people
. documents/storage vessels
The message may also be the Manufactured Decision
The Knowledge-Based View of Decision Making
Assimilating Knowledge Figure 4.2, page 99.
Once the Decision maker has established the meaning of an incoming message it can be assimilated with the DM’s knowledge store
When new knowledge is assimilated, it alters the knowledge store:. just be added. cause existing knowledge to be altered, discarded, or marked as being obsolete. It may cause fundamental alterations of
the knowledge store
The Knowledge-Based View of Decision Making
Recognizing the Need for a Decision
May be very obvious: . Highly structured . Happens frequently
May be take many repetitions of the event/stimuli to initiate action, thus it is:. unstructured. novel. by observing conditions (economic, political, mechanical) we may come to recognize that: - a problem exits - a solution is required
The Knowledge-Based View of Decision Making
Manufacturing a Decision: The manufacturing process produces new knowledge from knowledge.
The sources of raw materials is the decision maker’s storehouse of knowledge (experience, facts, rules, etc).
Knowledge is extracted on an as needed basis and manipulated by Cognitive abilities to produce solutions for the flow of problems that constitutes the KNOWLEDGE Manufacturing Process.
The solution that is the product of the process is the NEW KNOWLEDGE.
1.
A Manufacturing AnalogyMaterial Product Decision1. The process begins in reaction to a customer order or anticipated order.
The process begins in reaction to a recognizedneed or opportunity.
2. The process draws on an inventory of raw materials.
The process draws on an inventory ofKNOWLEDGE.
3. Items entering inventory are subject to quality testing controls.
Knowledge is assimilated into inventory only ifit is expected to be usable.
4. Abilities for manipulating materials transform/assemble raw materials into final products.
Abilities for manipulating knowledgetransformation/assemble existing knowledgeinto new knowledge about what to do.
5. During the process may yield material by- products that are stored in inventory or discarded.
During the process there are intermediatepieces of knowledge called problem solutions.
6. The process may yield material by-products that are stored in inventory or are discarded.
The process may yield knowledge by-productsthat are stored in inventory or are discarded.
7. The manufacture may be an individual or have multiple participants.
The decision maker may be an individual or consist of multiple participants
8. The finished product is packaged fordistribution.
The decision is packaged for distribution.
From Holsapple & Whinston, 1996, page 100.
Defining KnowledgeThree Views of Knowledge
Knowledge Representations:If a system has and can use a representation of somethingthen the system itself can also be said to have KNOWLEDGE.
The textbook can be a representation of knowledge if it can be read.
Representation is pattern of Symbols => an abstraction
It embodies knowledge:
Defining Knowledge
A useable representation of something
From a DSS point of view we must be concerned with
the computer memory and how it
processes knowledge represents knowledge
Clean data and defined objects are required
Knowledge States
A set of states ranging from raw data to decisions
Six states of Knowledge:
data
Information
structured information
insight
judgment
decision: The highest state
Defining Knowledge
One state of knowledge can be used to generate different states of knowledge
DSS help in: Acquiring knowledge
deriving knowledge
Knowledge Production
The result of a productivity activity (i.e. LEARNING) involving acquisition and/or derivation The flows and stock of knowledge
Figure 4.3, page 106
Stocks are the inventories of knowledge
The flows are the messages that tell the stock to do something
Knowledge Sources
The decision makers store house of Knowledge: Internal & External
The DM can be active or Passive about acquiring knowledge
Active: Message can be emitted to invoke a response
Passive the DM observes without invoking reactions
Knowledge Sources
The Decision to Acquire/ Derive Knowledge
General a mixture of acquiring and derivation of knowledge
Acquiring knowledge may tax:cognitive abilities, time, economic limits
There are tradeoffs
DSS tens to promote greater reliance on internal production of knowledge
Knowledge Sources
Reliability of Knowledge: Do we get the same knowledge from internal and external sources?
If there are multiple external sources- to they yield the same result
DSS
Without a DSS it may be infeasible to produce the it internally
Use the DSS in parallel with the knowledge acquisition to check the source reliability
Knowledge Sources
Knowledge Qualities DSS
accurately retaining knowledge
flagging inconsistencies
analyzing uncertainties
tracking multiple sets of knowledge
Knowledge Sources
Utility of Knowledge: Usefulness
Knowledge can be useful to different people
To a history professor knowledge about particle physics is probably not useful
Figure 4.4
DSS: Present what is relevant to a specific DM
Provide high quality knowledge
Knowledge Management
Techniques Text ManagementForms ManagementBusiness GraphicsSolver ManagementRule ManagementDatabase ManagementReport GenerationSpreadsheet AnalysisProgrammingMessage Management
Knowledge ManagementReasons for Understanding Knowledge
ManagementPosition or integrate Knowledge into a decisionExtend the role of supporting participants “from mere production to the processing, storage, retrieval, dissemination, utilization and general management of knowledge.”Facilitate and develop a philosophy and methodologies for handling knowledgeShift the role of supporting participants “from producing certainty and complete knowledge to structuring ignorance and managing uncertainty
Lohuizen & Kochen, 1986 in Holsapple & Whinston, 1996, page 112
Knowledge Management
Five types of Knowledge
1. Practical2. Intellectual3. Pastime4. Spiritual5. Unwanted
Knowledge Management
Three Primary Types of Knowledge
1. Descriptive: Includes descriptions of past, present, future, and hypothetical situations. DATA and INFORMATION- To Know What
2. Procedural Knowledge: The how to do; Step-by-Step
3. Reasoning Knowledge: To know Why- Approaches to problem solving
Knowledge Management
Three Secondary Types of Knowledge
1. Linguistic: Vocabulary and grammar, body language, meaning of gestures.
2. Assimilation Knowledge: The basis for controlling changes to the knowledge store.
A filtering mechanism
3. Presentation Knowledge: The basis for packaging outgoing responses
Knowledge Management
The Decision Maker possess knowledge
The DSS has processing abilities that can supplement the Decision Maker
The Cognitive Basis for Knowledge
Declarative Knowledge factual information that is static in
nature it is usually describable to us history- events, facts flexible- it can be reorganized to suite
our purposes Knowing That
Cognitive- Knowledge
Some knowledge can be encoded in a declarative format which can later be transformed into a procedural format as we become familiar with the information.Examples: Reading Windows for Dummies Reading a Golf technique book then truing on the PC/ Play golf
Cognitive Knowledge
Attention: the concentration and focusing of mental activityPaying attention seems to accentuate, or enhance, sensory input that has been focused on
The Cognitive Basis for Knowledge
Procedural Knowledge the underlying skillful actions we possess it is dynamic it is not very describable the acquisition of a skill involves making
and detecting errors (skiing, bike riding, ballet)
with additional experience we improve Knowing How
Information ProcessingSensory system: where specific aspects of the environment are detected and organized-into cognitive codeThe code is passed into memoryMemory Working memory: a workbench for
cognitive codes (short term memory) Permanent memory: long term storage of
declarative and procedural knowledge
Memory
External InputSensory RegisterShort-term StorageLong-term Storage
Sensory Register
Where our feature detection and pattern recognition process produce a cognitive code that can be stored for a short time.The Sensory register does not depend on resource allocation- we do not have to pay attention to incoming stimuli in order to have this cognitive code created.
Sensory Register
It must have a large storage capacityIt is modality specific: has difference storages for audio, visual
The code in storage Decays over timeResources must be allocated to transfer the code to STM or LTM
Short-term Memory
Limited capacity (RAM)Storage is organized by sensory component: acoustic, verbal, linguistic
Storage duration of unrehearsed material is about 30 secondsMaterial that is not elaborated or transferred decays.
Long-term Memory
To go from STM to LTM requires rehearsalRehearsal: procedures that maintain the vitality of the
code STS code will last indefinitely if it is
occasionally refreshed by rehearsal. Rehearsal duplicates and augments the
code for long-term storage (associations/links are created),
Technology Infrastructure
Organizational Infrastructure
The Architecture of Knowledge Repositories --- "Pipeline"
Repository* Content
* Structure
Knowledge Views
Knowledge Repository
* Content* Packaging/Format
* Accessing/Distribution
Aquisition RefinementStorage
RetrievalDistributed Presented
SUPPLIERS
USERS
Process Platform
Discussion Participants
The Architecture of Interactive Knowledge Repositories --- "Virtual"
Repository* Content
* Structure
Knowledge Views
Knowledge Repository
* Content* Packaging/Format
* Accessing/Distribution
Aquisition RefinementStorage
RetrievalDistributed Presented
Knowledge Engineering and Acquisition
Taxonomy of Knowledge Types
Primary Descriptive: data, information, descriptions of past,
present, and future situations Procedural: how to do something Reasoning: codes of conduct, regulations, policies,
diagnostic rules
Secondary Linguistic: vocabulary, grammar, knowledge of
gestures Assimilative: permissible contents, retention cycles,
relevancy filters Presentation: modes of communication, graphing,
messaging, inverse of Linguistic knowledge
Conceptual Model of Knowledge Engineering Process
Validation and Verification Feedback of Performance
and Knowledge
Knowledge ElicitationTools
Knowledge Structuring
Tools
Knowledge ModelingTools
PERSONExpert performance of
some task in some domain
COMPUTEREmulation of expert
performance of some task in some domain
Psychology of person
Personal construct psychology of person as an anticipatory system
Ontology of computer
knowledge representation and operationalizing an
anticipatory system
Psychological model of skilled
performanceRepresentation of skill in
terms of conceptual structures
Computational model of skilled
performanceRepresentation of skill in
terms of logicalstructures
Required Expertise Transfer
Elicitation
Feedback
Unification of psychological and
computational representation
Knowledge Acquisition Dimensions
StrategicStrategicKE-driven
Expert-drivenMachine-driven
InterviewsProtocol analysis
Repertory Grid
TacticalTactical
Five-Stage General Process of Knowledge Acquisition
Identification
Identify Problem Characteristics Conceptualization
Find ConceptsTo
RepresentKnowledge
Formalization
Design Structure to Organize Knowledge
Implementation
Formulate Rules, Frames, etc., to
Embody Knowledge
Testing
Validate Rules that Organize Knowledge
Refinements
Redesigns
Reformulations
Requirements
Concepts
Structure
Rules
Basic Pre-Interview Checklist
Decide what you need to know. Ask yourself why this information is
needed. Determine that an interview is the best
method for obtaining this information. Determine the appropriate degree of
structure for the interview. Consider the method in which the
answers to your questions will be coded and analyzed.
Necessary Task Conditions for Successful Concurrent Protocols
The sample of cases employed must be highly representative of the task under study.
Each task must have a clearly defined conclusion or point of completion.
The task must be able to be completed in one protocol session.
All data must be presented to the expert in a familiar form.
A test case should be given to the expert prior to the collection of protocols so that he or she may become familiar and comfortable with the verbalization process.
Typical Repertory Grid Structure
Constructs Element 1 Element 2 Element 3Distinction 1Constraint 1,1Constraint 1,2Constraint 1,3Distinction 2Constraint 2,1Constraint 2,2Constraint 2,3Distinction 3Constraint 3,1Constraint 3,2Constraint 3,3Distinction 4Constraint 4,1Constraint 4,2Constraint 4,3Distinction 5Constraint 5,1Constraint 5,2Constraint 5,3
Individual Individual Individual Individual Individual Individual Individual
Concept
Concept
Concept
Concept
ConceptConcept
ConceptConcept
Concept
Concept Concept
Concept Concept Concept
Concept
Knowledge Base Validation Measures and Techniques
Accuracy: How well does the system reflect reality. How correct is the knowledge in the knowledge base.
Adaptability: Possibilities for future development or changes. Adequacy: The portion of the necessary knowledge that is included in the knowledge base. Appeal: How well the knowledge base matches intuition and stimulates thought and
practicability Breadth: How well is the domain covered. Depth: The degree of the detailed knowledge. Face Validity: How credible is the knowledge. Generality: Capability of a knowledge base to be used with a broad range of similar
problems. Precision: Capability of the system to replicate particular system parameters. Consistency
of advice and coverage of variables in the knowledge base. Realism: Accounting for the relevant variables and relations. Similarity to reality. Reliability: The frequency of system predictions that are correct. Robustness: Sensitivity of conclusions to model structure. Sensitivity: The impact of changes in the knowledge base on the quality of outputs. Technical/Operational: Goodness of the assumptions, context, constraints, and conditions. Turing test: Ability of a human evaluator to identify if a given conclusion is made by a real
expert or a computer. Usefulness: How adequate the knowledge is (in terms of parameters and relationships) for
solving correctly. Validity: The capability of the knowledge base for producing empirically correct predictions.
KM – The Future
Not a fad Impact is immense Research on organizational
culture How to do each step Are they the right steps?
Knowledge Management
The definition is clear The concepts are clear The challenges are
Clear Surmountable
The benefits are clear (and can be huge)
The tools and technologies are viable
Knowledge ManagementKey Issues
Organizational culture Executive sponsorship Measuring success
The future: Comprehensive standardized KM packages
Knowledge Mangement“The wise see knowledge and action
as one” (Bhagvad Gita)Intelligent organizations recognize
that knowledge is an asset, perhaps the only one that grows over time, and when harnessed effectively can sustain the ability to continuously compete and innovate.