Class 11
Decision Making,
Decision Support Systems, &
Executive Information Systems
MIS 2000
Decision Making and Information Systems
Outline
Decision making concepts
Decision making and information systems
Decision Support Systems (DSS) – upper level management
Datamining – increasingly used data-driven DSS
Executive Support Systems (ESS)
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Decision Making*
Decision making = problem solving by making choices.
Stages in “Rational (Ideal, Scientific) Model” ** of decision making:
Problem Definition: Collect data, learn & analyze
Alternatives Solutions Creation: Figure out what courses of action
could solve the problem
Selection of best alternative: Evaluate alternatives on certain criteria
and choose the best; this the decision
Implementation: Put the decision into effect and evaluate effects
Other Models (“good enough”, “Gut Feeling”, “Garbage Can”, etc.)*
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Decisions and IS
Types of problems to solve/decisions to make:
Structured (well understood) – managing accounts receivable
Unstructured (poorly understood, unknowns) – designing new product
Semi-structured (some familiarity with problem) – budget preparation
Information systems for decision making:
TPS, MIS – previous lecture
Decision Support Systems
Executive Support Systems
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Decision Support Systems
DSS is a type of IS that supports mid-level and higher management in
semi-structured decision making.
Corporate financial planning (capital budgeting, scoring models)
Product planning, Information systems planning; other planning*
Supply chain management (production & shipping schedules)
Customer relationship management (cross-selling, market
segmentation)
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Decision Support Systems
DSS does:
Support decision making steps (Problem, Alternatives)
Improve speed and quality of decision making (better alternatives, more
methodical). Consequences on organizational efficiency and effectiveness.
MIS
vs.
- Routine or exceptional reports
- Structured problems, general control
MIS 2000
DSS
- Semi Structured problems
- Focus: Change, rapid response
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Types of DSS
Model-driven DSS
Systems that use some model for transforming data coming from
TPS/MIS and external sources (e.g., “what-if” analysis; optimization
models like Solver in Excel, etc.) – your Excel assignment
Data-driven DSS
Analyze data from TPS and external sources by using special
software -Datamining is the main kind of IT used in data-driven
DSS today (see next slides)
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MIS vs. Data-Driven DSS
MIS:
Query: “How many units of product 420 were shipped last month?”
Data retrieved from databases (TPS) to answer specific business
questions
Datamining :
Automated analysis of hidden patterns & relationships
TPS data are “cleaned” , integrated, and moved into Data
Warehouse
TPSs (data organized
in tables; SQL used for
search)
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Data
Warehouse
(data organized differently)
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Datamining
Used increasingly in marketing. Data analysis helps with identifying:
1. Associations: co-occurrence of events (e.g., does a consumer buys a
group of same products at the same time; leads for cross-selling)
2. Sequences: identify events that are linked over time (e.g., after
purchasing a new TV, within 3 months a DVD player is purchased 30% of
the time; also cross-selling)
3. Classifications: identify patterns in data (e.g., determine buyers’
behaviour – happy customer, runaway customer)
4. Clusters: group related data to understand objects of interest (e.g.,
market segmentation on types of customers)
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Executive Support Systems (ESS)
ESS is an IS that supports top management in unstructured decision making.
Helps senior executives to
1. Monitor and analyze organizational performance in order to identify
opportunities and weaknesses relevant for improvement of the organization,
and its efficiency and effectiveness
2. Develop business intelligence on competitors, future opportunities, and
trends in order to define organizational strategies - goals and the paths of
reaching the goals
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ESS
Data from external sources used extensively in ESS
ESS has a drill-down capability, which helps an executive to understand
what is behind aggregated performance figures
User interface is graphics-intensive (next slide)
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ESS Example
Performance Analysis by using the method of Balanced Scorecard for monitoring
and analyzing organizational performance (mixed quantitative & qualitative data
- financial figures, productivity measures, customer & employee satisfaction)
User interface is in the form of Executive Dashboard with scales/dials showing
intensity of performance indicators.
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