Download Chapter11 - College of Business, UNR

CHAPTER ELEVEN
MANAGING KNOWLEGE
Objectives
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We have been through some of this
already
Role of knowledge management
Types of knowledge management
systems
Providing value through knowledge
management
Business benefits
Dimensions of Knowledge
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Data is transformed into
information, which is transformed
into knowledge
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Undocumented knowledge is called
tacit knowledge
Document codified knowledge is explicit
knowledge
Collective knowledge is transformed
into wisdom
Dimensions of Knowledge
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Knowledge is an asset that requires
resources to manage
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Knowledge involves
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Value increases as more people (inside
and outside the organization) share it
How-to, craft, skill, knowing why,
understanding procedures
Process of change and knowledge
management is called
organizational learning
Steps Toward Knowledge
Management
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Acquire
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From data warehouse (data mining and
AI)
From external data stores (Government
databases)
It’s BI again
Store
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In content management systems and
knowledge database (SharePoint)
Expert systems to mimic the
knowledge of subject experts
Steps Toward Knowledge
Management
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Disseminate
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Apply
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Through portals and search engines
Through e-mail and social tools
Through DSS (BI) systems and
enterprise applications
Provides actionable decision-making
tools
And finally collaborate
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Communities of practice
Types of
Knowledge Management Systems
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Enterprise KMS
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Knowledge work systems
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Systems to collect, store, organize, and
distribute structured and unstructured
information
Specialized systems to discover and
create new knowledge
Intelligent techniques
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This is the domain of artificial
intelligence
Types of Enterprise Knowledge
Management Systems
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Content management systems
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Drupal
Joomla
WordPress
Tasks
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Capture information
Tag it for retrieval
Change management
Learning Management Systems
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Tools for employee learning and
training
Online courses (MOOCS)
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Lynda.com
We have to throw in Ted talks
Types of Knowledge Work Systems
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Computer-aided design (CAD)
Additive manufacturing (3-D
printing)
Virtual reality systems
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Augmented reality
Virtual Reality Modeling Language
(VRML)
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AND NOW ON TO THE WORLD OF
ARTIFICIAL INTELLIGENCE
Artificial intelligence simulates
human intelligence such as the
ability to reason and learn.
Expert Systems (Introduction)
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Systems that capture knowledge of
skilled employees that can be used
by others in an organization
Limitation
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Works well when decision variables are
limited
Works poorly when there are too many
decision options
Operation of an Expert System
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A knowledge base (database) stores
knowledge often represented as a set of
rules
 There may be hundreds or thousands of
rules
Types
 Forward chaining
 Start with user data and apply rules
 Backward chaining
 Start with null hypothesis
 Then apply rules and ask questions
until we get an answer
Applications
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Freight routing
Pharmacological interaction
Case-based Reasoning
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Based on historical cases
(examples)
Use historical cases to determine if
this case is applicable
Used in medical logical
Fuzzy Logic
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Rule based system that can
represent imprecision or ambiguity
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(near, far, close, warm, cold)
Autofocus in a camera
Positioning of an automatic welding
robot
Neural Networks
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How these work internally is beyond
the scope of this course
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Basically we create software that tires
to
Learn
 Mimic the human brain
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Characteristics
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Sift through large amounts of data
Find patterns in that data
Software learns and makes corrections
over time
Genetic Algorithms
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We keep looking at many solutions
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Discarding suboptimal solutions
Keeping optimal ones until the best
solution is found
Intelligent Agents
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They carry out work without human
intervention
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Deleting junk mail
Detecting spam
Excel figures out graph types based on
data heuristics
Siri
Adapts to user preferences