Making Decisions

Making Decisions

•Focus:

•Analytic v. Heuristic

•Decisions in the Problem Solving Phases

•Multiple-Criteria Methods

•Semi-structured decisions

Making Decisions

•Technology has always been used to augment the human decision-making process

•Now, however, it is being used to replace the human decision-making process

•The more we automate, the less we make the decisions that affect us

•Yet we seem willing, eager, to give up that responsibility without considering consequences, or (then) resisting when they manifest

Making Decisions

•Intelligence:

• Using the information you have to make good decisions

• Bad decisions can have ramifications, haunt you for years to come

•Business Intelligence

• Using the information you have to make good business decisions

• Bad decisions will negatively impact your company in significant ways for a long time

Making Decisions

•Decision Support Systems

•Models (many types)

• Descriptive

• Static / Dynamic

• Mental

•Decision trees / tables

•Simulations

•Flow charts / Diagrams

Making Decisions

•Decision Support Systems

• Organize the information used in the decision making process

• Support, not replace

• Can affect or change the users’ decision making process

• Best for supporting complex, unique decisions

• Highly individualized

• Focus is on the process, not output

Making Decisions

•Making fast-paced decisions

• More decisions are being made in less time

• Missed opportunities

• 75% of workers, 80% of managers

• Decisions not made fast enough

• Don’t consider all information

• Can’t consider all information in time

• Too many sources

•Decision Making Under Risk

•Certainty

•Uncertainty

•Risk

Making Decisions

•Decision Making Styles

•Analytic

•Heuristic

•Implications for DSS development

Making Decisions

•Problem-Solving Phases

•Intelligence

•Design

•Choice

Making Decisions

•Why and where do bottlenecks happen?

•Dimensions of Semi-Structured Decisions

•Degree of decision-making skill required

•The degree of problem complexity

•Number of criteria considered

Making Decisions

•Semi-Structured Decisions in the Problem-Solving Phases

•Intelligence phase decision support systems

•Identify the problem

•Define the problem

•Assign a priority to the problem

Making Decisions

•Semi-Structured Decisions in the Problem-Solving Phases

•Design phase decision support systems

•Identify alternatives

•Quantify alternatives

•Establish performance criteria

•May help decision maker identify appropriate alternatives

Making Decisions

•Semi-Structured Decisions in the Problem-Solving Phases

•Choice phase decision support systems

•Choice always left up to decision-maker

•Present methods of selection

•Help organize and display the information

Making Decisions

•Multiple-Criteria Decision Making

•The Trade-Off Process

•Two columns

•Pros

•Cons

•Updated approach using positives only

Making Decisions

Making DecisionsThe Trade-Off Approach

A B C D

Eat at McDonald’s Eat at health food store

Tastes Better 1 Healthier 1

Can get fries 1 Wider selection 1

Have happy meals 1 Common food alts 1

Many locations 1 Discover new tastes 1

Nifty mascot 1 Feel Better 1

Cheaper 1

6 5

•Multiple-Criteria Decision Making

•Weighting Methods

•Each attribute is assigned a weight (value)

•Each alternative is assigned a grade for each attribute

•Choose alternative with highest total score

Making Decisions

Decision MakingWeighting Methods

Weight Attributes Car 1 Car 2 Car 3

0.2 Manual transmission 2 2 1

0.15 Power seats 4 4 4

0.1 Engine power 5 5 10

0.15 Convertible 10 5 6

0.2 Media player inputs 10 10 10

0.05 Gas mileage 8 10 4

0.1 Color 8 6 3

0.05 Trunk space 6 7 5

Total 6.5 5.7 5.45

•Multiple-Criteria Decision Making

•Sequential Elimination by Lexicography

•Attributes are ranked according to importance•Each alternative is assigned a grade for each attribute•Only choose alternatives with highest score

•Repeat until one choice is left

Making Decisions

Making DecisionsSequential Elimination by Lexicography

Attributes Car 1 Car 2 Car 3

1 Manual transmission 10 10 10

2 Power seats 2 2 1

3 Engine power 5 5 10

4 Convertible 4 4 4

5 Media player inputs 8 10 4

6 Gas mileage 10 5 6

7 Color 8 6 3

8 Trunk space 6 7 5

Attributes Car 1 Car 2 Car 3

1 Manual transmission 10 10 10

2 Power seats 2 2 1

3 Engine power 5 5 10

4 Convertible 4 4 4

5 Media player inputs 8 10 4

6 Gas mileage 10 5 6

7 Color 8 6 3

8 Trunk space 6 7 5

Making DecisionsSequential Elimination by Lexicography

Attributes Car 1 Car 2 Car 3

1 Manual transmission 10 10 10

2 Power seats 2 2 1

3 Engine power 5 5 10

4 Convertible 4 4 4

5 Media player inputs 8 10 4

6 Gas mileage 10 5 6

7 Color 8 6 3

8 Trunk space 6 7 5

Making DecisionsSequential Elimination by Lexicography

•Multiple-Criteria Decision Making

•Sequential Elimination by Conjunctive Constraints

•Set up constraints

•Each alternative must satisfy constraints

•If not, that alternative is eliminated

Making Decisions

Making DecisionsSequential Elimination by Conjunctive Constraints

Attributes Constraints Car 1 Car 2 Car 3

Manual transmission 5spd/6spd 5 spd T 4 spd F 6 spd T

Power seats Yes Yes T Yes T Yes T

Engine power >250hp 400 T 220 F 350 T

Convertible Yes No F Yes T Yes T

Fuel tank >15 gal 15 T 12 F 18 T

Gas mileage >15mpg 12 F 20 T 16 T

Color Red/blue/black Black T Red T Green F

Trunk space >12 cu. ft. 14 T 8 F 12 T

F F F