Knowledge Comp3503 Management and Business Intelligence
Daniel L. Silver, Ph.D.
Outline
Introduction Background on Knowledge, KM and BI
Knowledge versus Information Two Perspectives on Knowledge Management
Integrating the Perspectives The Knowledge Management Cycle
Individuals versus Organizations
Important Areas for Research based on Insights from the KM Cycle
Daniel L. Silver 2
Apr 22, 2009
Introduction
Considerable interest in KM and BI (2005: $10 50B
US)
Hardware and software venders eager to use the term or associated terms However there is debate as to what KM is or should be ...
New organization strategy/ management style Latest Information Technology (IT) Latest name for business information processing
Critics argue that it is a fad (M. Schrage `01)
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Apr 22, 2009
Introduction
KM is not a fad ! KM is an important new area of research and application in response to new organizational problems Necessarily going through a period of definition Must consider a composite of people and information technology issues
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Introduction
Why should KM and BI matter to you? Knowledge becoming substantial asset Maximum sharing of information Employees leave, business value remains Betterment of internal and external structures, personal competencies Competitive advantage - leading organizations now adopting
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Introduction
Key Technology Components of KM and BI:
Internet / Intranet & Groupware "Content" management systems Objected oriented distributed methods E-Business/E-Commerce business models Data Warehousing Data Mining
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Background
Competition Global Opportunities Organization Customer Demands Technological Change Employee Turn-over
The Problem
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Regulatory Change
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Background
KM is not a fad ! Concepts that are emerging via KM are needed by organizations to meet today's internal and external pressures The ultimate goal for an organization is to communicate information and manage knowledge with the same efficiency and effective as an individual
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Background
Employees Gov't Regulators Industry Associations
Management of Organizational Knowledge
Competitors Partners Suppliers
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Customers Channels
The Objective
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Background
KM lacks clear definition There are at least two reasons for this:
Debate over knowledge versus information Differences between the two major perspectives on KM
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Background
Progression from Data to Wisdom Data = measures without context Information = data or derived values within the context of other dimensions such as time and dollars Knowledge = information + people Wisdom = knowledge + benevolence?
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Background
Knowledge versus Information Information can be encoded and therefore stored, processed and communicated Knowledge is a combination of information and processes that work together to promote rational behaviour and achieve desired goals [Newell '82]
Knowledge is uniquely linked to action An intangible asset "the capacity to act" desired by all organizations [Sveiby '92]
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Background
Knowledge versus Information This definition subscribes to the autopoietic epistemology of Maturana and Varela
Autopoietic systems are open to information but closed to knowledge Only information can pass between agents Knowledge is created inside each agent based on its unique set of experiences
Knowledge is often lost when converted into information that can be handled by IT
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Background
Perspectives on Knowledge Management
Technology Centred Info. Technologists Info. and comp. sciences, database, telecomm., analysis KM = objects Information (explicit knowledge) - easily encoded
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People Centred Org. Theorists Org. behavior, group dynamics, HCI, psychology KM = process Tacit knowledge difficult to encode
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Integrating the KM Perspectives
The division between these perspectives is driven by differences in educational background, personal and profession motives The division needs to be eliminated because there is an important relationship: KM is a people-centred
philosophy that necessarily involves and promotes the use of information technologies.
Information People
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I.T.
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Integrating the KM Perspectives
"Knowledge is all about linking people with data." Ken Orr "Too many managers still believe that once the right technology is in place appropriate information sharing will follow." Thomas Davenport
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Integrating the KM Perspectives
The challenge: "To construct hybrid KM environments in which we use both humans and machines in complimentary ways" [Davenport '00] The IT proponents must understand that the people-centred approach is critical because information does not equal knowledge The people-centred proponents must accept that IT has and will play a critical role in KM
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Knowledge Management Cycle
Environmental data
Observation and Analysis
Large Corporation Small Business Individual
Problems Opportunities
"Business 22, Intelligence"
Apr 2009
Information S: policies, filing cabinets, S: INFORMATION various int./ext. DBs S: agreement, files, memory, notes, files P:P: simple database (DB) operational PC a brain, a systems, Knowledge Theory Storage P: brains, small systems Consolidation Generation integrated corporate sys. C: internalized Processing C: telephone, fax, email, C: LANs, intranet, voiceHappy! Communication meetings mail, video -- Synergy? Chaos ? Approach Results Methods
Testing and Application
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Knowledge Management Cycle
Environmental data Observation and Analysis Information S: memory, notes, files P: a brain, a PC C: internalized Happy?
Individual
Problems Opportunities
Consolidation
Theory Generation
Strategy Approach
Results Testing and Application
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Knowledge Management Cycle
Environmental data Observation and Analysis Information S: agreement, files, simple database (DB) P: brains, small systems C: telephone, fax, email, meetings - Synergy? Testing and Application
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Small Business
Problems Opportunities
Consolidation
Theory Generation
Strategy Approach
Results
Knowledge Management Cycle
Environmental data Observation and Analysis
Large Corporation
Problems Opportunities
Information S: policies, filing cabinets, various int./ext. DBs P: operational systems, Theory Consolidation integrated corporate sys. Generation C: LANs, intranet, voicemail, video - Chaos ? Strategy Results Approach Testing and Application
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Important Areas of KM Research
Observation and Analysis: Improving retrieval and filtering of information P: develop research abilities, library science skills, IT: adaptive user interfaces, content management, KM formalisms (Ontologies, KQML) Capturing salient and accurate environmental data P: cultural shift from rapid collection to accurate collection, IT: methods of "at source" electronic entry (bar coding, handheld, voice recognition)
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Apr 22, 2009
Important Areas of KM Research
Theory Generation: Fostering knowledge creation through small groups P: facilitate movement of people/ideas between groups, IT: collaborative software, DW and data mining technologies
Reducing bureaucracy and stimulating creativity P: balance legal/prof. requirements with information sharing, analysis, creativity, IT: XML, messaging, document management
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Apr 22, 2009
Important Areas of KM Research
Testing and Application: Promoting full-process involvement P: feedback methods between designers/ strategists and workers: job-shadowing, linking rewards with actual success, IT: exec. dashboard Measuring business processes and knowledge assets P: tracking intangible assets (employee turnover, days of education), valuing business processes that create or transfer knowledge, IT: methods of automated metrics gathering
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Apr 22, 2009
Important Areas of KM Research
Knowledge Consolidation: Methods of collective reflection and trust building P: perhaps most needed, regular points reflection, sharing and consolidation, "trust is the bandwidth of communications" Retaining k...