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CHAPTER 2: DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT

Decision Support Systems and Intelligent Systems, 7th

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Decision Making: Introduction and Definitions

Characteristics of decision making: Groupthink Decision makers are interested in evaluating

what-if scenarios Experimentation with the real system may

result in failure Experimentation with the real system is

possible only for one set of conditions at a time and can be disastrous

Changes in the decision making environment may occur continuously, leading to invalidating assumptions about the situation

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Decision Making: Introduction and Definitions (cont.)

Changes in the decision making environment may affect decision quality by imposing time pressure on the decision maker

Collecting information and analyzing a problem takes time and can be expensive. It is difficult to determine when to stop and make a decision

There may not be sufficient information to make an intelligent decision

Information overload

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Decision Making: Introduction and Definitions (cont.)

Working Definition of Decision makingThe process of choosing among two or more alternatives courses of action for the purpose of attaining a goal or goals.

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Decision Making: Introduction and Definitions (cont.)

Decision Making and Problem Solving Phases of the decision process

1. Intelligence 2. Design 3. Choice

Problem solvingA process in which one starts from an initial state and proceeds to search through a problem space to identify a desired goal. It includes the 4th phase of the decision process

4. Implementation 5. Monitoring ? Is it the fifth phase?

Systems

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A system is a collection of objects such as people, resources, concepts, and procedures intended to perform an identifiable function or to serve a goal

System Levels (Hierarchy): All systems are subsystems interconnected through interfaces

Systems (con.)2-7

Structure Inputs: are elements that enter the system Processes: are all the necessary to convert or transform

inputs into outputs. Outputs: are the finished products or the consequences of

being in the system. Feedback : is a flow of information from the output

component to the decision-maker concerning the system’s output or performance. Based on the outputs, the decision-maker, may decide to modify the inputs, the processes, or both. the decision-maker compares the output to the expected output and adjusts the input and possibly the processes to move close to the output targets.

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Systems (con.)

The environment: Is composed of several elements that lie outside in in the sense that they are not inputs, output, or processes. However they affect the system’s performance and consequently the attainment of its goals. Environmental elements can

be social, political, legal, physical, or economic . Boundary: A system is separated from its

environment by boundary.Input Processes Outputboundary

Environment

Systems (con.)2-9

System Types2-10

Closed system Independent Takes no inputs Delivers no outputs to the environment Black Box: is one which inputs and outputs are well

defined, but the process itself is not specified.Such as transaction processing system (TPS).

Open system Very dependent on it environment. Accepts inputs from the environment. Delivers outputs to environment

An Information System

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Collects, processes, stores, analyzes, and disseminates information for a specific purpose

Is often at the heart of many organizations Accepts inputs and processes data to provide

information to decision makers and helps decision makers communicate their results

System performance measures Effectiveness : The degree of goal

attainment (e.g. total sales) . Doing the right things

Efficiency : The ratio of output to input. Appropriate use of resources. Doing the things right

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Models

Model: is a simplified representation or abstraction of reality Four groups of models:1. Iconic model

A scaled physical replica2. Analog model

An abstract, symbolic model of a system that behaves like the system but looks different

3. Mental modelThe mechanisms or images through which a human mind performs sense-making in decision making

4. Mathematical (quantitative) modelA system of symbols and expressions that represent a real situation

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Models (cont.)

The Benefits of Models Model manipulation is much easier than

manipulating a real system Models enable the compression of time The cost of modeling analysis is much lower The cost of making mistakes during a trial-

and-error experiment is much lower when models are used than with real systems

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Models (cont.)

With modeling, a manager can estimate the risks resulting from specific actions within the uncertainty of the business environment

Mathematical models enable the analysis of a very large number of possible solutions

Models enhance and reinforce learning and training

Models and solution methods are readily available on the Web

Many Java applets are available to readily solve models

Intelligence PhaseIntelligence Phase

Design PhaseDesign Phase

Choice PhasesChoice Phases

REALITY

Implementationof Solution

Implementationof Solution

SUCCESS

FAILURE

Verification, Testing of Proposed Solution

Verification of the Model

Examination

Phases of the Decision-Making Process

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Phases of the Decision-Making Process (con.)

Intelligence phaseThe initial phase of problem definition in decision making

Design phaseThe second decision-making phase, which involves constructing model of decision making problem, finding possible alternatives in decision making and assessing their contributions

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Phases of the Decision-Making Process (cont.)

Choice phaseThe third phase in decision making, in which an alternative is selected

Implementation phaseThe fourth decision-making phase, involving actually putting a recommended solution to work

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Decision Making: The Intelligence Phase

1- Problem (or opportunity) identification: some issues that may arise during data collection

Data are not available Obtaining data may be expensive Data may not be accurate or precise enough Data may be insecure Information overload Outcomes (or results) may occur over an extended

period

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Decision Making: The Intelligence Phase (cont.)

2- Problem classificationThe conceptualization of a problem in an attempt to place it in a definable category, possibly leading to a standard solution approach

3- Problem decomposition Dividing complex problems into simpler subproblems may help in solving the complex problem

4- Problem ownership The jurisdiction (authority) to solve a problem

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Decision Making: The Design Phase

The design phase involves finding or developing and analyzing possible courses of action

These include: Understanding the problem Testing solutions for feasibility A model of the decision-making problem

is constructed, tested, and validated

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Decision Making: The Design Phase (cont.)

Modeling involves conceptualizing a problem and abstracting it to quantitative and/or qualitative form

A proper balance between the level of model simplification and the representation of reality must be obtained because the cost-benefit trade-off.

The process of modeling is a combination of art and science.

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Decision Making: The Design Phase (cont.)

Models have:1. Decision variables

A variable in a model that can be changed and manipulated by the decision maker. Decision variables correspond to the decisions to be made, such as quantity to produce, amounts of resources to allocate, and so on

2. Principle of choiceThe criterion for making a choice among alternatives

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Decision Making: The Design Phase (cont.)

Models can be:1. Normative models

Models in which the chosen alternative is demonstrably the best of all possible alternatives Optimization

The process of examining all the alternatives and proving that the one selected is the best

Suboptimization An optimization-based procedure that does not consider all the alternatives for or impacts on an organization

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Decision Making: The Design Phase (cont.)

2. Descriptive modelA model that describes things as they are. It is mathematically based. Simulation

An imitation of reality Narrative

It is a story that helps a decision maker uncover the important aspects of the situation and leads to better understanding and framing

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Decision Making: The Design Phase (cont.)

Good enough or satisficing Satisficing

A process by which one seeks a solution that will satisfy a set of constraints. In contrast to optimization, which seeks the best possible solution, satisficing simply seeks a solution that will work well enough

Reasons for satisficing: Time pressures Lack the ability to achieve optimization Recognition that the marginal benefit of a better

solution is not worth the marginal cost to obtain it

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Decision Making: The Design Phase (cont.)

Developing (generating) alternatives: In some situation, the alternatives may be

generated automatically by the model In most situations it is necessary to generate

alternatives manually (a lengthy, costly process); issues such as when to stop generating alternatives are very important

The search for alternatives usually occurs after the criteria for evaluating the alternatives are determined

The outcome of every proposed alternative must be established

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Decision Making: The Design Phase (cont.)

Measuring outcomes The value of an alternative is evaluated in

terms of goal attainment Risk

One important task of a decision maker is to attribute a level of risk to the outcome associated with each potential alternative being considered

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Decision Making: The Design Phase (cont.)

ScenarioA statement of assumptions about the

operating environment of a particular system at a given time; a narrative description of the decision-situation setting

Scenarios are especially helpful in simulations and what-if analyses

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Decision Making: The Design Phase (cont.)

Scenarios play an important role because they: Help identify opportunities and problem areas Provide flexibility in planning Identify the leading edges of changes that

management should monitor Help validate major modeling assumptions Allow the decision maker to explore the

behavior of a system through a model Help to check the sensitivity of proposed

solutions to changes in the environment

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Decision Making: The Design Phase (cont.)

Possible scenarios The worst possible scenarioThe best possible scenarioThe most likely scenarioThe average scenario

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Decision Making: The Design Phase (cont.)

Errors in decision making The model is a critical component in the

decision-making process A decision maker may make a number of

errors in its development and use Validating the model before it is used is

critical Gathering the right amount of

information, with the right level of precision and accuracy is also critical

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Decision Making: The Choice Phase

Solving a decision-making model involves searching for an appropriate course of action Analytical techniques (solving a formula) Algorithms (step-by-step procedures) Heuristics (rules of thumb) Blind searches

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Decision Making: The Implementation Phase

Generic implementation issues include: Resistance to change Degree of support of top management User training

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How decisions are supported