Transcript MIS 301 - Technology & Management

MIS 301
Information Systems in Organizations
Dave Salisbury
[email protected] (email)
http://www.davesalisbury.com/ (web site)
Why We Invest in IS&T
Revenue
+
Strategic
Systems
+
Management
Support & Decision
Systems
IS&T
Investment
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Operational
Systems
Profit
–
Costs
Decisions in Business
Decision Characteristics
Unstructured
Semi-structured
Strategic
Management
Tactical
Management
Structured
Operational
Management
Ad Hoc
Unscheduled
Summarized
Infrequent
Forward Looking
External
Broad Scope
Prespecified
Scheduled
Detailed
Frequent
Historical
Internal
Narrow Focus
Short Time Frame
Management Reports
Periodic Scheduled
Reports
Exception Reports
Major
Management
Information
Systems Reports
Demand Reports
and Responses
Push Reports
Management Roles
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Interpersonal - figurehead, leader,
liaison
Informational - monitor, disseminator,
spokesperson
Decisional - entrepreneur, problem
solver, resource coordinator, and
negotiator
Simon & the Rational Person
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Humans can be rational actors, their
rationality is bounded by their limitations
Humans tend to satisfice, or settle on the first
acceptable option, rather optimizing
Information stored in computers can increase
human rationality if accessible when needed
The central problem is not how to organize to
produce efficiently, but how to organize to
make decisions (i.e. process information)
IT Provides Assistance to...
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Communicate and/or distribute
knowledge
Collaborate with other workers
Routinize procedures
Capture and codify knowledge
Create knowledge
Two Key Issues
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Uncertainty
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Lack of information
Ambiguity
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Lack of structure
Data, Information, Knowledge
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Data are a collection of:
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Information is organized or processed data that are:
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Facts
Measurements
Statistics
Timely
Accurate
Knowledge is information that is:
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Contextual
Relevant
Actionable
Knowledge Types
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Explicit Knowledge
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Facts, figures
Easily codified
Easily transmitted
People to Documents
Learn by studying
Codify in programs
and systems
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Tacit Knowledge
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Experiences
Not easily codified
Hard to transmit
People to People
Learn by doing
Share by networking
holders of the
knowledge
Knowledge Management
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Structuring of knowledge enables
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Knowledge management initiatives focus on
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effective and efficient problem solving
dynamic learning
strategic planning
decision making.
identifying knowledge
how it can be shared in a formal manner
leveraging its value through reuse.
Knowledge management can
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promote organizational learning
help solve problems
Knowledge Management Systems
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Communication technologies allow
users to access needed knowledge and
to communicate with each other.
Collaboration technologies provide the
means to perform group work.
Storage and retrieval technologies
(database management systems) to
store and manage knowledge.
Knowledge & IT
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Codify knowledge for transfer
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Easily reusable
People to documents
Individual-level standardization
a.k.a process in your book
Knowledge & IT
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Create networks among expert
knowledge holders
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Knowledge lies in experts, not easily
reusable
Person to person
Individual-level uniqueness and innovation
a.k.a practice in your book
Knowledge Management Systems
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IT that helps gather, organize, and share
business knowledge within an organization
Hypermedia databases that store and
disseminate business knowledge. May also
be called knowledge bases
Best practices, policies, business solutions
Entered through the enterprise knowledge
portal
Enterprise Information Portals & DSS
Internet
Extranet
Intranet
Enterprise Information Portal Gateway
Enterprise Information Portal User Interface
Search
Agents
Data
Mining
OLAP
DSS
What-If Models
Sensitivity Models
Goal-Seeking Models
Optimization Models
Knowledge
Management
Database Management Functions
Data
Mart
Operational
Database
Other
Business
Applications
Analytical
Database
Knowledge
Base
Online Analytical Processing
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Enables interactive examination/manipulation of
detailed & consolidated data from many perspectives
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Consolidation
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The aggregation of data.
From simple roll-ups to complex groupings of interrelated
data
Drill-Down
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Analyze complex relationships to discover patterns, trends,
and exception conditions in real time
Display detail data that comprise consolidated data
Slicing and Dicing
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The ability to look at the database from different viewpoints.
When performed along a time axis, helps analyze trends and
find patterns
Decision Support Systems
What If-Analysis
Sensitivity Analysis
Important
Decision
Support
Systems
Analytical Models
Goal-Seeking Analysis
Optimization Analysis
Data Mining for Decision Support
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Software analyzes vast amounts of data
Attempts to discover patterns, trends, &
correlations
May perform regression, decision tree,
neural network, cluster detection, or
market basket analysis
Management Support Systems
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Decision Support Systems (DSS) provide
support primarily to analytical, quantitative
types of decisions.
Executive (Enterprise) Support Systems (ESS)
support the informational roles of executives.
Group Decision Support Systems supports
managers and staff working in groups.
Intelligent Systems
Decision Process
Define
the
Process or Problem
Intelligence phase
Develop
Modeling
Alternative
Courses of Action
Select
The “Best”
One
phase
Choice phase
Review It
Act on it
Implementation
phase
Models as decision making aids
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A model (in decision making) is a simplified
representation of reality.
The benefits of modeling in decision making
are:
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Cost of virtual experimentation is much lower
Simulated compression of time.
Manipulating the model is much easier
The cost of mistakes are much lower
Modeling for “what-ifs”
Analysis and comparison of a large number
alternatives
Models enhance and reinforce learning
Group Decision Support Systems
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Decision making is frequently a shared
process involving groups using group
decision support systems (GDSS).
Groups
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Co-located
Dispersed
Process structuring
Problem structuring
Executive Information & Support
Systems
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Serves top management
Original intent – provide executives with immediate, information
about the firm “critical success factors”
Features of an EIS
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Information presented in forms tailored to the preferences of the
users
Most stress use of graphical user interface and graphics displays
May also include exception reporting and trend analysis
Very user friendly
Supported by graphics
Provide drill down (investigating information in increasing detail).
ESS goes beyond EIS to include:
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Analysis support
Communications
Office automation
Intelligence support
Artificial Intelligence
Artificial
Intelligence
Cognitive
Science
Applications
•Expert Systems
•Fuzzy Logic
•Genetic Algorithms
•Neural Networks
Robotics
Applications
Natural
Interface
Applications
•Visual Perceptions
•Locomotion
•Navigation
•Tactility
•Natural Language
•Speech Recognition
•Multisensory Interface
•Virtual Reality
AI Application Areas in Business
Neural Networks
Fuzzy Logic Systems
Genetic Algorithms
Virtual Reality
AI Application
Areas in
Business
Intelligent Agents
Expert Systems
Intelligent Agents
Interface
Tutors
Presentation
Agents
Search
Agents
User
Interface
Agents
Information
Management
Agents
Information
Brokers
Network
Navigation
Agents
RolePlaying
Agents
Information
Filters
Expert Systems
The Expert System
Expert
Advice
User
User
Interface
Programs
Inference
Engine
Program
Knowledge
Base
Workstation
Expert System Development
Knowledge
Engineering
Knowledge
Acquisition
Program
Workstation
Expert and/or
Knowledge Engineer
Expert System Applications
Decision Management
Diagnostic/Troubleshooting
Maintenance/Scheduling
Design/Configuration
Major
Application
Categories
of Expert Systems
Selection/Classification
Process Monitoring/Control