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Business Intelligence and Analytics: Systems for Decision

Support

(10th Edition)

Chapter 2: Foundations and Technologies

for Decision Making

Business Intelligence and Analytics: Systems for Decision

Support

(10th Edition)

Learning Objectives  Understand the conceptual

foundations of decision making  Understand Simon’s four phases of

decision making: intelligence, design, choice, and implementation

 Understand the essential definition of decision support systems (DSS)

 Understand different types of DSS classifications

(Continued…)

Learning Objectives  Learn the capabilities and limitations

of DSS in supporting managerial decisions

 Learn how DSS support for decision making can be provided in practice

 Understand DSS components and how they integrate

Opening Vignette

Decision Modeling at HP Using Spreadsheets

 Background  Problem description  Proposed solution  Results  Answer & discuss the case

questions...

Questions for the Opening Vignette

1. What are some of the key questions to be asked in supporting decision making through DSS?

2. What guidelines can be learned from this vignette about developing DSS?

3. What lessons should be kept in mind for successful model implementation?

Characteristics of Decision Making

 Groupthink  Evaluating what-if scenarios  Experimentation with a real system!  Changes in the decision-making

environment may occur continuously

 Time pressure on the decision maker

 Analyzing a problem takes time/money

 Insufficient or too much information

Characteristics of Decision Making Decision Support Systems (DSS)

Dissecting DSS into its main concepts 

Building successful DSS requires a thorough understanding of these concepts

Decision Making  A process of choosing among two or

more alternative courses of action for the purpose of attaining a goal(s)

 Managerial decision making is synonymous with the entire management process - Simon (1977)

 Example: Planning  What should be done? When? Where?

Why? How? By whom?

Decision-Making Disciplines  Behavioral: anthropology, law,

philosophy, political science, psychology, social psychology, and sociology

 Scientific: computer science, decision analysis, economics, engineering, the hard sciences (e.g., biology, chemistry, physics), management science/operations research, mathematics, and statistics

 Each discipline has its own set of assumptions and each contributes a unique, valid view of how people make decisions

Decision-Making Disciplines  Better decisions

 Tradeoff: accuracy versus speed  Fast decision may be detrimental  Many areas suffer from fast

decisions  Effectiveness versus Efficiency  Effectiveness  “goodness”

“accuracy”  Efficiency  “speed” “less

resources”  A fine balance is what is needed!

Decision Style  The manner by which decision

makers think and react to problems  perceive a problem  cognitive response  values and beliefs

 When making decisions, people…  follow different steps/sequence  give different emphasis, time allotment,

and priority to each step

Decision Style  Personality temperament tests are

often used to determine decision styles

 There are many such tests  Meyers/Briggs,  True Colors (Birkman),  Keirsey Temperament Theory, …

 Various tests measure somewhat different aspects of personality  They cannot be equated!

Decision Style  Decision-making styles

 Heuristic versus Analytic  Autocratic versus Democratic  Consultative (with individuals or groups)

 A successful computerized system should fit the decision style and the decision situation  Should be flexible and adaptable to

different users (individuals vs. groups)

Decision Makers  Small organizations

 Individuals  Conflicting objectives

 Medium-to-large organizations  Groups  Different styles, backgrounds,

expectations  Conflicting objectives  Consensus is often difficult to reach  Help: Computer support, GSS, …

Phases of Decision-Making Process

 Humans consciously or subconsciously follow a systematic decision-making process - Simon (1977) 1) Intelligence 2) Design 3) Choice 4) Implementation 5) (?) Monitoring (a part of intelligence?)

Simon’s Decision-Making Process

Decision Making: Intelligence Phase

 Scan the environment, either intermittently or continuously

 Identify problem situations or opportunities

 Monitor the results of the implementation

 Problem is the difference between what people desire (or expect) and what is actually occurring  Symptom versus Problem

 Timely identification of opportunities is as important as identification of problems

Decision Making: Intelligence Phase

 Potential issues in data/information collection and estimation  Lack of data  Cost of data collection  Inaccurate and/or imprecise data  Data estimation is often subjective  Data may be insecure  Key data may be qualitative  Data change over time (time-

dependence)

Application Case 2.1

Making Elevators Go Faster!

 Background  Problem description  Proposed solution  Results

Decision Making: Intelligence Phase

 Problem Classification  Classification of problems according to the

degree of structuredness  Problem Decomposition

 Often solving the simpler subproblems may help in solving a complex problem.

 Information/data can improve the structuredness of a problem situation

 Problem Ownership  Outcome of intelligence phase 

A Formal Problem Statement

Web and the Decisio n- Making Process