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PPT Slides by Dr. Craig Tyran and Kraig Pencil
Game Plan
• Decisions and IS support
• Decision making process
• Decision support systems (DSS)
• Expert Systems
PPT Slides by Dr. Craig Tyran and Kraig Pencil
A. Decisions and IS Support1. Business people encounter many types of decisions Follow a decision making process Variety of information systems to support decision making
From Haag, et al, MIS for the Information Age, 3rd Edition, 2002.
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process1. Simon’s decision
making model– Simple, yet enduring
– Decision process modeled as a “flow” of events
– Can proceed in linear or iterative fashion
2. Information systems can support each phase of process
This gentleman won a Nobel Prize!
PPT Slides by Dr. Craig Tyran and Kraig Pencil
Business Scenario
• Scenario: Orcas Kayaks Inc. is a company that makes sea kayaks. A new Operations Manager has been hired to promote smooth and efficient manufacturing operations.– Note: The previous Ops Mgr got fired …
• Frequent problems with factory equipment
• Much factory downtime
• Poor decision making
• Desired:– Better decision making process
– Support for mgmt decision making
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process (cont.)3a. Intelligence phase
– Gather data that may be used for “intelligence” purposes
– Does there seem to be a problem(s) or opportunity(s)?
– Define the problem or opportunity
– “Operations Mgr” scenario:• Gather data• Review of production log reveals
significant equipment downtime• Problem: Poor maintenance? (Or
could it be something else?)
• Can IS help? Which type(s) of IS could be useful for this phase?
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process (cont.)3b. Design phase
– Identify key variables– Create model to aid decision making– Validate model– Establish criteria to be used to make a
choice– Identify alternative solutions
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process (cont.)
3b. Design phase
“Operations Mgt” scenario:• Variable: e.g.,
– current maintenance schedule, – age of equipment, – cost of maintenance, – cost of lost productivity ...
• Model(s): e.g., – statistical regression, – cost-benefit forecast model
• Establish criteria: e.g., $ total 5-year cost• Alternatives: e.g.,
– repair as needed– purchase new equipment– change maintenance schedule
• Can IS help? How?
PPT Slides by Dr. Craig Tyran and Kraig Pencil
Example: Statistical Model – Factory Equipment Maintenance Cost vs. Age
Should we be concerned about model?
The model sounds good
Age
Cos
ts
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process (cont.)
3c. Choice phase– Evaluate potential solutions using
model(s) developed earlier• e.g., “What if” analysis, Sensitivity
analysis– Use criteria to choose the preferred
solution
– “Operations Mgr” scenario:• Tasks: See above• Make it easy to explore different
scenarios of interest• Convey useful information
• Can IS help? How?
PPT Slides by Dr. Craig Tyran and Kraig Pencil
B. Decision Making Process (cont.)
3d. Implementation phase– Implement the decision– Monitor– Make adjustments
– “Operations Mgr” scenario:• Tasks: See above
• How could an IS provide support for the above?
PPT Slides by Dr. Craig Tyran and Kraig Pencil
C. Decision Support Systems1. Used for decisions that are
• Complex, “Messy”
• Non routine, Non structured
2. Include models (financial, prediction, etc.)• e.g., Allow decision maker to manipulate inputs,
Support “what if” analysis
3. Particularly helpful for ______ and/or _______ phases of decision process
• Example: “Cow culling” DSS to support cattle management: http://ag.arizona.edu/AREC/cull/culling.html
choicedesign
PPT Slides by Dr. Craig Tyran and Kraig Pencil
DSS for Cattle Management
DSS results in this case are displayed using a graphical output
Flexible: can evaluate multiple cases or scenarios.
Does the DSS “make” the decision???
No, the user may need some expertise to interpret the results or to consider other factors.
PPT Slides by Dr. Craig Tyran and Kraig Pencil
C. Decision Support Systems (cont.)
4. Three primary components of DSS include (see figure)• User interface
• Model management
• Data management
PPT Slides by Dr. Craig Tyran and Kraig Pencil
C. Decision Support Systems (cont.)5. Excel-based DSS Example: (next slide)
Break-even analysis for a manufacturing business• Decision: What sales price will lead to “breakeven” after 1,000
units sold?• DSS components and features
• Interface– Graphical output– Advanced Excel feature: User input
form
• Model management– Break-even model
• Data management– Assumption data table (very simple)– Easy access to the workbook through
the WWW
PPT Slides by Dr. Craig Tyran and Kraig Pencil
D. Introduction to Expert Systems (ES)
1. Expert systems– Replicate the thought processes of human
“experts”• Follow a structured set of rules
– “Knowledge-based” systems– Whale watcher demo:
http://www.aiinc.ca/demos/whale.shtml– Other ES examples (from exsys.com)
http://www.exsys.com/demomain.html– The Cs: Create and ConveyImage: www.tubecad.com/2006/10/05/Genius.png
PPT Slides by Dr. Craig Tyran and Kraig Pencil
D. Introduction to Expert Systems (ES)
Figure: http://www.generation5.org/content/2004/bdt-implementation.asp
Expert Systems tend to use branching
logic, like this one.
bare
PPT Slides by Dr. Craig Tyran and Kraig Pencil
D. Introduction to Expert Systems (ES)
• Knowledge Base – as Expert System– Use indexes and search technology (key word
searches) to catalog and retrieve relevant information recorded by “experts”.
PPT Slides by Dr. Craig Tyran and Kraig Pencil
D. Introduction to Expert Systems (cont.)
2. How is an ES different from a DSS?– DSS
• Allows decision maker a platform for exploring and evaluating the options
– ES • Delivers advice based on answers to a set of questions
– Where does the “knowledge” reside for DSS? For ES?
3. Business examples of ES?– ? ? ?
4. Would it be easier to develop a set of “expert rules” for an ES for …a) a narrow, well-defined application?b) a wide-ranging, poorly-defined application?
– What are the implications for ES applications?