Decision Making & Decision Support

Decision Making & Decision Support

MIS 320

Kraig Pencil

Summer 2013

PPT Slides by Dr. Craig Tyran and Kraig Pencil

Game Plan

• Decisions and IS support

• Decision making process

• Decision support systems (DSS)

• Expert Systems


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.


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!


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


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?


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


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?


Example: Statistical Model – Factory Equipment Maintenance Cost vs. Age

Should we be concerned about model?

The model sounds good

Age

Cos

ts



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?



3d. Implementation phase– Implement the decision– Monitor– Make adjustments

– “Operations Mgr” scenario:• Tasks: See above

• How could an IS provide support for the above?


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


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.


C. Decision Support Systems (cont.)

4. Three primary components of DSS include (see figure)• User interface

• Model management

• Data management


D. DSS Components


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


Break-Even Analysis Model


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



Figure: http://www.generation5.org/content/2004/bdt-implementation.asp

Expert Systems tend to use branching

logic, like this one.

bare



• Knowledge Base – as Expert System– Use indexes and search technology (key word

searches) to catalog and retrieve relevant information recorded by “experts”.


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?

Decision Making & Decision Support

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