bcis 401 information systems for management knowledge management dr. j. affisco fall 2001
Post on 20-Dec-2015
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TRANSCRIPT
Why Knowledge Management?
• Knowledge is the property of the individual
• Successful practices rarely transferable
• Knowledge is embedded and hard to extract– Large amounts of time spent “reinventing the
wheel”
Why Knowledge Management?• Fortune 500 companies wasted $12 billion in
1999 as employees duplicated one another’s work
• 90% of 800 North American and European Companies were working on some aspect of knowledge management
• Ford estimated that in 1997-99 knowledge management initiatives resulted in cost savings or additional revenues of $914 million
Why Knowledge Management?• Chevron estimates it has saved more than $650
million since 1991 by sharing best practices among mangers in charge of energy use at its oil refineries
• Texas Instruments reports savings of more than $1 billion by disseminating best practices throughout its 13 semiconductor plants
• By late 1999 1/3 of top 1,000 largest U.S. companies had begun knowledge mgt. initiatives; by 2003 more than half will have done so.
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Types of Knowledge
• Explicit Knowledge– Easily collected and organized– Transferred through digital means
• Tacit Knowledge– Personal context-specific– Process knowledge– Hard to formalize and communicate
Knowledge Management Strategies
• Sets forth criteria for choosing– What knowledge a firm plans to pursue
– How firm will capture and share it
• Generally determined through strategic audit– What sorts of knowledge are critical to support
business positioning
– Who needs to have what information?
– When do they need to know it?
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Generating
• Identifying the desired content
• Getting people to contribute ideas– On-line discussions– Submitting deliverables that have emerged
from other work
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Generating
• Buy or Rent
• Research and Development
• Shared Problem Solving
• Adaptation
• Communities of Practice
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Organizing
• Organizing collected data so it can be represented and retrieved electronically
• Knowledge sharing systems or tools– Knowledge bases– Navigational devices– User interfaces– Taxonomies
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Organizing - Knowledge Bases
• Unfiltered– Archive documents directly– Many-to-many communication without
intervention by others
• Filtered– Content screened, distilled, and approved for use
by recognized experts– Material continually refreshed to maintain its
currency
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Developing
• Selection and further refinement of material to increase its value for users
• Subject matter experts review work done by others such as editors
• Results include– Final content/form of expert material– Knowledge objects
Distributing• How people get access to material• User friendliness• Encouraging use and reuse of knowledge• Types of systems
– Push - Sends large masses of information out to users– Pull - Users call on the knowledge base to draw
material out– Targeted Push - Proactively deliver material that is
context sensitive
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Types of Decision Support
• Decision Support Systems
• Expert Systems/Knowledge Based DSS
• Group Decision Support Systems
• Executive Support Systems
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Intelligence
• Searching the environment for conditions
calling for decisions
• Raw data are obtained, processed, &
examined for clues that may identify
problems.
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Design
• Inventing, developing, & analyzing possible
courses of action.
• This involves processes to– Understand the problem– Generate solutions– Test solutions for feasibility
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Choice
• Selecting a particular course of action from
those available
• A choice is made and implemented
Levels of Org Decision MakingInformation Characteristics
Task Variable Strat. Plan. Mgt. Control Operational Control
Accuracy Low High
Level of Detail Aggregate Detailed
Time Horizon Future Present
Frequency of Use Infrequent Frequent
Source External Internal
Scope of Info. Wide Narrow
Type of Info Qualitative Quantitative
Age of Info. Older Current
A MIS/DSS Framework
Type ofDecisionTask
OperationalControl
ManagerialControl
StrategicPlanning
SystemsSupport
StructuredInventoryReordering
Pdn.PlanningUsing LP
PlantLocation
TPS, EDP,MS Model MIS
Semi-Structured
BondTrading
SettingMktg.Budgets
CapitalAcquisitionAnalysis
DecisionSupportSystems
Un-Structured
Selecting acover formagazine.
HiringManagers
R&DPortfolioDevelop.
KBDSSESEIS
Specific DSS
DSS Generator
DSS Tools
Manager (user)
DSS Builder
Toolsmith
Intermediary
Technical Supporter
Relating DSS Levels and Roles
DSS Development ProcessDSS Development Process
Builder and User agree on small significant sub- problem.
Design and develop an initial system to support decision making required by sub-problem.
Use the system for a short period of time.
Evaluate the system. Modify the system. Incrementally expand the system.
Systems Development Process
• Analysis - What application is to be supported?
• Design - What is the best way to support application?
• Construction - Build the designed system.
• Implementation - Apply the system.
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Definition
Expert Systems are special-purpose computer
programs which use knowledge and reasoning
to perform complex tasks in a specific problem
domain at a level of performance usually
associated with an expert in the domain.
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Purpose
• Originally designed to replace domain
experts.
• Today viewed as Knowledge-based Decision Support Systems– System supports Managerial Decision Making
with the capability to process knowledge in addition to quantitative data.
Expert Systems Architecture
Inference Engine
- Forw ard Chaining- Backw ard Chaining
Know ledge Base- Facts- Rules
- Fram es
UserInterface
User
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Knowledge Base
• Repository of domain-specific knowledge • Knowledge needs to be represented and
employed in a form that can be used for reasoning.
• Knowledge structures– Facts– Rules– Frames
Rules
• Knowledge structure of the form “if-then”
• The “if statement” represents a premise.
• The “then statement” represents a conclusion.
• As rules are processed, if the premise is true then the conclusion indicates some action to be taken.
• A rule is proved when the premise of the rule matches known facts.
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Frames
• A way of packaging knowledge about one
object.
• Are composed of slots in which data or characteristics associated with specific objects are stored.
• Frames are organized in a hierarchy which allows for sharing of knowledge through the property of heredity.
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Rules vs Frames
• Frames are especially efficient for
packaging knowledge and handling the
storage and retrieval of that knowledge.
• Rules work best at making deductions.
Inference Engine
• Its task is to process the domain knowledge contained in the knowledge base to arrive at a solution to the problem.
• Inference engine combines facts and rules through an inference process to arrive at conclusions.
• Inference techniques– Forward chaining– Backward chaining
Forward Chaining• Begins with known facts and the rule set and attempts
to deduce new facts which may eventually lead to the deduction of the goal.
• Inference engine cycles through the rules until one is found whose premises matches a fact. This rule is then proved or fired, and the conclusion is added to the fact base.
• Process continues until the implication of the conclusions reached are sufficient to provide a solution.
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Backward Chaining
• Inference processes work backwards from the goal.
• Inference takes the goal as a hypothesis and then seeks to prove a series of subgoals working backward from the goal.
• This is done recursively until all subgoals that are required for the goal’s existence are proven.
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GROUP DECISION-SUPPORT SYSTEM
(GDSS)
INTERACTIVE COMPUTER-BASED
SYSTEM FACILITATES SOLUTION OF
UNSTRUCTURED PROBLEMS BY
DECISION MAKERS WORKING AS
GROUP
*
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TOOLS OF GDSS
• ELECTRONIC QUESTIONNAIRES
• ELECTRONIC BRAINSTORMING
• IDEA ORGANIZERS
• QUESTIONNAIRE TOOLS
• TOOLS FOR VOTING, SETTING PRIORITIES
*
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TOOLS OF GDSS
• STAKEHOLDER IDENTIFICATION &
ANALYSIS TOOLS
• POLICY FORMATION TOOLS
• GROUP DICTIONARIES
*
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ELECTRONIC MEETING SYSTEM (EMS)
COLLABORATIVE GDSS USES
INFORMATION TECHNOLOGY TO
MAKE GROUP MEETINGS MORE
PRODUCTIVE FACILITATES
COMMUNICATION DECISION MAKING
*
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• IMPROVED PRE-PLANNING
• INCREASED PARTICIPATION• OPEN, COLLABORATIVE ATMOSPHERE
• IDEA GENERATION FREE OF CRITICISM
• EVALUATION OBJECTIVITY
• IDEA ORGANIZATION & EVALUATION
*
HOW GDSS ENHANCED DECISION MAKING
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• SETTING PRIORITIES & DECISION MAKING
• DOCUMENTATION OF MEETINGS
• ACCESS TO EXTERNAL INFORMATION
• PRESERVATION OF ORGANIZATIONAL
MEMORY
*
HOW GDSS ENHANCED DECISION MAKING
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The Problem
• Plant Location– In practice, a cross-functional team of senior
executives typically makes plant location decisions.
– In arriving at this decision the team looks at a number of conflicting variables and factors, both quantitative and qualitative.
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The Objective
• To provide training for executives in plant
location strategic decision making so as to
improve their performance when faced with
such a decision.
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The Scenario
• A general scenario describing the industry,
competitive environment, government and
legal environment, and position of various
other stakeholders is provided prior to the
group support sessions.
• The exercise proceeds in two phases
Phase I• The executive group is broken into three role
playing groups– Corporate management
– State and local government
– Environmental stakeholders
• A more specific scenario in terms of the firm’s products and processes is distributed with instructions to read it from the point of view of their role playing group.
Phase I - Individual GSS Sessions
• Electronic brainstorming is used to help the participants develop ideas about the plant location problem from their respective role’s point of view.
• Idea organizer is used to help crystallize the ideas already generated into a set of critical issues for each of the three constituencies.
• Vote then is used by to prioritize the critical issues previously developed.
Phase I - Individual GSS Sessions
• The group is given information on three potential location sites and are then asked to evaluate the sites based on the critical issues they developed.
• The alternative evaluation tool is used to help rank order the competing location sites. However, the ranking is not revealed to the participants at this point.
• A transcript of the sessions is used to help debrief the groups on the decision making process as well as the decision content.
Phase II - Metagroup GSS Session
• The sets of critical issues identified, in the earlier sessions, by the groups representing the three constituencies are discussed.
• The stakeholder identification tool helps the group to analyze the impact of policies relating to the critical issues on the stakeholders.
• The policy formulation tool is used to facilitate the arrival at a consensus on which issues remain critical to the group.
Phase II - Metagroup GSS Session
• Vote may be used once again to arrive at a final prioritization.
• Having achieved this understanding of their position on the critical plant location factors, the metagroup is now given the information on the same three sites as during the individual group sessions.
• Using the appropriate tools, the metagroup is asked, for a second time, to rank order the alternatives. This time they are given the final ranking.
Phase II - Metagroup GSS Session
• In addition, at this time they are given the final ranking which resulted from each of the individual group decision sessions.
• A comparison of these rankings is used to fuel the debriefing discussion. As part of the debriefing we can compare the processes and results of the individual groups with those of the metagroup.
• A discussion of expectations versus reality is generally useful.