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Decision Making 3Factors in decision-making

• - decision theory has evolved from an abstract mathematical discipline for optimal decisions to a framework for thinking that enables different perspectives of a problem to be brought together with the result that new intuitions and higher-level perspectives are generated.

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Factors to Consider

• Rationality• Certainty and uncertainty• Risk• Psychology – hidden traps• Computer Support For Decision Making.

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Models of Human Decision Making

• Models by definition involve a simplification of reality.

• Simon’s three phase model (sometimes this includes implementation and is called Simon’s four phase model) assumes rational decision-making.

• There are other models:– Humans make “non-rational” decisions all of the

time.

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How do we choose?

• In Simon’s model we look at the alternatives, predict and measure outcomes and pick the alternatives which best matches our goal or goals.

• How realistic is this?

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Rationality Assumptions

• The decision maker is rational.– Humans are economic beings whose objective is

to maximise the attainment of goals.– In a given situation all viable alternative courses of

action and their likely consequences are known.– Decision makers have an order of preference that

enables them to rank the desirability of all consequences of the actions.

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Are these assumptions valid?

• Consider the decision whether to go with O2,Vodafone, Meteor or 3 for your new mobile phone contract:– Do you know all viable courses of action and their

likely consequences.– What are your goals?– Can you compare goals?– Do the rationality assumptions apply?

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A Different sort of Decision

• Consider the decision to return to college to get a higher degree.– Do the rationality assumptions apply?

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Rationality Assumptions

• Are they useful?– These are a simplification of the way we make

decisions which may or may not be useful depending on how close the assumptions are to reality for a given situation.

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Rationality?

• “If a decision-maker is prepared to accept a set of rules that most people regard as sensible then to be rational he or she should prefer the indicated course of action to its alternatives.....”

BUT• - this might conflict with their intuitive feelings

and it is good to explore this as this might lead to further insight and understanding

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• Decision analysis requires a decision-maker to be clear about his/her judgements

• Helps learning• Helps communication• Can produce insight and foster creativity

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Bounded Rationality

• A human has limits to degree of rationality he/she can bring to a problem.

• The decision-maker cannot have complete knowledge of all the alternatives to the consequences of choice.

• Managers often simplify the problem in order to make a decision.

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Good Enough Solutions

• Can search for the optimal solution.

• Satisficing: Look for a good enough solution rather than the best solution.

• Sometimes the extra costs associated with looking for the best solution are not justified.

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Choosing between Alternatives

• Sometimes we make decisions where we know what the outcome of actions will be. We choose which outcomes we want.

• More often the outcomes are uncertain.

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Certainty versus uncertainty• Classify the different

alternatives:– Certainty– Risk– Uncertainty.

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Certainty

• Assume that complete knowledge is available.• Deterministic Environment.– Example: Fixed mortgage rate.

• Usually structured problems with short time horizons.

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Risk

• Decision situations which involve chance.• Consider several possible outcomes for each

alternative, each with a probability.• Probabilities are known or can be estimated.• Each alternative has a degree of risk.

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Risk Analysis

• Calculate the expected value of each alternative.

• Select the alternative with the best expected value.

– EV = Σ (Probability of Outcome) * (Value of Outcome

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Exercise

• If I offer you 5 to 1 odds on a six coming up with one roll of a die would you take the bet?

• What is the Expected Value?

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Uncertainty

• Several outcomes are possible for each course of action.

• It is not possible to estimate the probability of occurrence of the outcome.

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Can our thinking be flawed?

• The Hidden traps in decision making.• Awareness of our thinking helps avoid these

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Computer Support For Decision Making

• Depends on the type of decision– What are the different classifications we have

discussed?

• Depends on the decision making phase– What are the different phases of decision making?

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Structured versus Unstructured decision

• Reminder of definitions• Which do you think is more likely to be

supported by computer systems.

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Structured Decisions • Decisions are repetitive in nature• Computer support has been available since the

1960s.• Can abstract and analyze the decision, and classify

them into well understood categories.• Mathematical techniques may exist for solving the

problem and/or finding an optimal solution.• Management Science (MS) / Operations Research

(OR)• The system can help select the solution.

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Routine Decisions

• Routine decisions should be treated as such.

• They should be analyzed and “programmed”.

• Should be supported by technology.• Can have large benefits.• Do not reinvent the wheel each time.

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Example of Structured Decision

• Linear Programming:• Examples:– Route Planning, Cloth cutting, material allocation.

• If the computer system can make the decision then it is management science,

• The term DSS is used for those situations where human input is necessary.

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Unstructured Decisions

• Computer support is more focused on information presentation, summary and analysis.

• Expert Systems can capture expert knowledge using heuristics and use these to make decisions.

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Support for Intelligence Phase

• Intelligence Phase–Ability to scan internal and external information–Looking for opportunities and threats–Routine and ad-hoc reporting–Regular meetings at strategic level–Technologies include:• Web-based information systems –RSS feeds• Executive Information Systems/Business Analytics• Expert Systems for interpretation and diagnostics• Data mining• On Line Analytical Processing

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Support for the Design and Choice Phase

• Design/Choice Phase–Generating alternatives and selection–Use of modelling–Technology includes:• Decision Support Systems/Business

intelligence• Expert Sytems to assist choice• Simulation software• Group Decision Support Systems,

Knowledge management systems

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Support for Implementation

• Implementation–Emphasis on communication, explanation

and justification–Visability of the decision and rejected

alternatives–Technologies include:• DSS; analysis carried out can be published• Forecasting and simulation

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Support for Decision making

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INTELLIGENCE

DESIGN

CHOICE

IMPLEMENT

MIS

Data Mining

OLAP

EIS

GDSS

Management Science

Modelling

GDSS

DSS

ES

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