Data Warehousing, Decision Support Systems

Front 1

The three components of Business Pressures - Responses - Support model:

Back 1

1. business pressures that result from today's business climate
2. responses (actions taken) by companies to counter the pressures, or to take advantage of the opportunities available in the environment)
3. Computerized support that facilitates the monitoring of the environment and enhances the response actions taken by organizations.

Front 2

Four major categories of Business Environment factors:

Back 2

Markets
Consumer Demands
Technology
Societal

Front 3

The _________________ of most of these factors increases with time, leading to more pressures, more competition, and so on.

Back 3

intensity

Front 4

Organizational Responses:

Back 4

Be Reactive, Anticipative, Adaptive, and Proactive

Front 5

Business Environmental Factors respond to Pressures & Opportunities, resulting in Organizational Responses that lead to Decisions and Support

Back 5

Note....

Front 6

Major Objective of computerized decision support

Back 6

facilitate closing the gap between the current performance of an organization and its desired performance, as expressed in its mission, objectives and goals and the strategy to achieve them.

Front 7

Management

Back 7

a process by which organizational goals are achieved by using resources.

Front 8

Resources =

Back 8

Input

Front 9

Output =

Back 9

Attainment of goals

Front 10

The level of productivity or the success of management depends on the performance of managerial functions, such as:

Back 10

planning organizing, directing, and controlling

Front 11

To perform their functions, managers are engaged in a :

Back 11

Continuous process of making decisions.

Front 12

Managers perform 10 major roles that can be classified into three major categories:

Back 12

Interpersonal
Informational
Decisional

Front 13

Managers use computers directly to:

Back 13

Support and improve decision making which is a key task that is part of most of these roles.`

Front 14

Managers at high managerial levels are:

Back 14

primary decision makers.

Front 15

Mintzberg's 10 Managerial Roles

Back 15

Interpersonal:
Figurehead
Leader
Liaison
Informational:
Monitor
Disseminator
Spokesperson
Decisional:
Entrepreneur
Disturbance Handler
Resource Allocator
Negotiator

Front 16

Figurehead

Back 16

symbolic head obliged to perform number of routine duties of a legal or social nature.

Front 17

Leader

Back 17

responsible for the motivation and activation of subordinates; responsible for staffing, training, and associated duties.

Front 18

Liaison

Back 18

Maintains self-developed network of outside contacts and informers who provide favors and information

Front 19

Monitor

Back 19

Seeks and receives a wide variety of special information (much of it current) to develop a thorough understanding of the organization and environment; emerges as the nerve center of the organization's internal and external information.

Front 20

Disseminator

Back 20

Transmits information received from outsiders or from subordinates to members of the organization;' some of this information is factual, and some involves interpretation and integration

Front 21

Spokesperson

Back 21

Transmits information to outsiders about the organization's plans, policies, actions, results and so forth; serves as an expert on the organization's industry.

Front 22

Entrepreneur

Back 22

Searches the organization and its environment for opportunities and initiates improvement projects to bring about change; Supervises design of certain projects

Front 23

Disturbance handler

Back 23

responsible for corrective action when the organization faces important, unexpected dusturbances

Front 24

Resource allocator

Back 24

responsible for the allocation of organizational resources of all kinds in effect, is responsible for the making or approval of all significant organizational decisions.

Front 25

Negotiator

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responsible for representing the organization at major negotiations.

Front 26

Four step process managers use to make decisions:

Back 26

1. Define the problem - difficulty or opportunity
2. Construct a model that describes the real-world problem
3. Identify possible solutions to the modeled problem and evaluate the solutions
4. Compare, choose, and recommend a potential solution to the problem

Front 27

Environmental factors that may make the evaluation process difficult:

Back 27

* more technological alternatives to choose from
* regulations, terrorism, competition and changing consumer demands - more difficult to predict future
* need for rapid decisions, unpredictable changes and the costs of making mistakes
* Environments are growing more complex

Front 28

Reasons for using Computerized Decision Support Systems:

Back 28

* Speedy computations - enabled by computers
* Improved communication and collaboration input from people in different geographical areas
* Increased productivity of group members
* Improved data management
* Managing giant data warehouses
* Quality support
* Agility support
* Overcoming cognitive limits in processing and storing information
* Using the Web
* Anywhere, anytime support

Front 29

Cognitive Limits

Back 29

indicates that an individual['s problem-solving capability is limited when a wide range of diverse information and knowledge is required.

Front 30

How have the capabilities of computing evolved over time:

Back 30

they have changed in size, capabilities, memory size, abilities, softwares

Front 31

List some capabilities of computing that can facilitate managerial decision making.

Back 31

Improved collaboration, provide great storage capability, capacity, ability to access information quickly

Front 32

How can a computer help overcome the cognitive limits of humans?

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computers can quickly access and process vast amounts of stored information

Front 33

Why is the Web considered so important for decision support?

Back 33

Provides access to world-wide data and knowledge; effectively collaborate with remote partners; and managers can find necessary information quickly and affordably

Front 34

Gorry and Scott-Morton Classical Framework

Back 34

3-by-3 matrix showing the two dimensions are the degree of structuredness and the types of control
Type of Decision: Structured, Semistructured,
Unstructured
Type of Control: Operational, Managerial, Strategic

Front 35

___________________ processes are routine and typically repetitive problems for which standard solution methods exist.

Back 35

Structured
All phases of decision making are structured; repeatedly encountered; makes it possible to abstract, analyze and classify into specific categories. ie., make or buy decision

Front 36

____________________ processes are fuzzy, complex problems for which there are no cut-and-dried solution methods.

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Unstructured
requires none of the aspects of the four phases
can be only partially supported by standard computerized quantitative methods
Intuition and Judgement play large role in decision process.

Front 37

_________________ processes fall between structured and unstructured problems having some structured elements and some unstructured elements; i.e., trading bonds, marketing budgets , performing capital acquisition analysis

Back 37

Semistructured
A mixture requiring some of the phases
solving these problems may involve a combination of standard solution procedures and human judgement.

Front 38

Strategic Planning

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Involves defining long-range goals and policies for resource allocation

Front 39

Management Control

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the acquisition and efficient use of resources in the accomplishment of organizational goals

Front 40

Operation Control

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the efficient and effective execution of specific tasks.

Front 41

Management Science

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approach that says that in solving problems managers should follow the four-step systematic process

Front 42

Steps in MS (Management Science) Process

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1. Define the problem
2. Classify the problem into a standard category.
3. Construct a model that describes the real-world problem.
4. Identify possible solutions and evaluate
5. Compare, choose, and recommend a potential solution to the problem

Front 43

Automated Decision Making

Back 43

Relatively new approach to supporting decision making;
Rule based system that provides a solution, usually in one functional area. Example: how to price products/services
Originally called: Revenue Management (Optimization) - dynamically price tickets according to demand

Front 44

Automated Decision Making Framework

Back 44

Technology, DSS theories, Artificial intelligence & Business processes are used to define: Business decision rules.
ADS attempts to automate highly repetitive decisions based on business rules.

Front 45

2 examples of each:
Operational Control
Managerial control
Strategic planning

Back 45

Operational Control - Hire Press Ganey for Satisfaction
survey
Hire new Advertising Company
Managerial Control - acquire upgraded computer
hardware
Purchase adjacent property for
expansion
Strategic Planning - company will be paperless by 2015;
company will be global by 2015

Front 46

What are the nine cells of the decision framework? Explain what each is for.

Back 46

Each of the nine cells represents a combination of one degree of decision structure with one type of management control.
Operational Control - Structured Decision: Accounts receivable, Accounts payable, order entry
Operational Control - Semistructured Decision: Production scheduling, Inventory control
Operational Control - Unstructured Decisions: Buying software, approving loans, operating a help desk. selecting a magazine cover
Managerial Control - Structured Decision: Budget analysis, Short-term for casting, personnel reports, Make-or-buy
Managerial Control - Semistructured Decision: Credit evaluation, budget preparation, plant layout, project scheduling, Reward system design, Inventory categorization
Managerial Control - Unstructured: Negotiating, recruiting an executive, buying hardware, lobbying
Strategic Planning - Structured: Financial management, investment portfolio, Warehouse location, Distribution systems.
Strategic Planning - Semistructured, Building a new plant, mergers and acquisitions, new product panning, compensation planning, QA, HR policies
Strategic Structure - Unstructured: R & D planning; New tech development, Social responsibility planning.

Front 47

Degree of Structuredness`

Back 47

idea that decision-making processes fall along a continuum that ranges from highly structured (sometimes called programmed) to highly unstructured (non-programmed) decisions

Front 48

Phases of Decision Making Process: (four)

Back 48

Intelligence
Design
Choice
Implementation

Front 49

Intelligence

Back 49

phase that involves searching for conditions that call for decisions

Front 50

Design

Back 50

phase that involves inventing, developing, and analyzing possible alternative courses of action (solutions)

Front 51

Choice

Back 51

phase that involves selecting a course of action from among those available.

Front 52

Implementation

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phase that involves adapting the selected course of action to the decision situation (i.e., problem solving or opportunity exploiting)

Front 53

How can computers provide support to semistructured and unstructured decisions?

Back 53

data and information generated from corporate or external data sources can improve the quality of the information on which the decision is based by providing a range of solutions, along with their potential impacts. This helps managers to better understand the nature of problems and make better decisions.

Front 54

Decision Support Systems (DSS)

Back 54

systems that couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computer-based support system for management decision makers who deal with semistructured problems.

Front 55

MIS and DSS are content free expressions =

Back 55

means different things to different people.

Front 56

Architecture of DSS

Back 56

1. Data - data related to a specific situation are manipulated by using models.
2. Models - can be standard or customized.
3. Users - vital fourth component
4. User interface - interfacing with the system
5. Knowledge/Intelligence Component (optional component)

Front 57

Two Major Types of DSS

Back 57

model-oriented DSS - quantitative models are used to generate a recommended solution to a problem

data-oriented DSS - support ad hoc reporting and queries

Front 58

Provide two definitions of DSS.

Back 58

1. systems that couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions.
2. Interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems.

Front 59

Describe DSS as an umbrella term.

Back 59

Used in this way, DSS describes any computerized system that supports decision making in an organization. An organization may have (for example) a knowledge management system to guide all its personnel in their problem solving, it may have separate support systems for marketing, finance, and accounting, a supply chain management (SCM) system for production, and several expert systems for product repair diagnostics and help desks. The term DSS encompasses them all.

Front 60

How is the term DSS used in the academic world?

Back 60

The term DSS is used primarily in the academic world today. It is commonly used to describe the area of research related to computer support for decision making, is the name of a leading journal in the field, and is a standard course title. The industry tends to use the term business intelligence. However, the two are not always seen as identical.

Front 61

Business Intelligence (BI)

Back 61

an umbrella term that combines architectures, tools, databases, analytical tools, applications and methodologies. (content-free expression - means different things to different people)

Front 62

Major Objective of BI

Back 62

enable interactive access (sometimes in real time) to data, to enable manipulation of data, and to give business managers and analysts the ability to conduct appropriate analysis.

Front 63

Process of BI

Back 63

based on the transformation of data to information, then to decisions and finally to actions.

Front 64

List and describe the major components of BI. (Architecture)

Back 64

BI systems have four major components: the data warehouse (data in the DSS architecture), business analytics and business performance management, and the user interface (which corresponds to the component of the DSS architecture). You could also list the user as a component here, as with DSS.

Front 65

Business Analytics

Back 65

a collection of tools for manipulating, mining, and analyzing the data in the data warehouse; analytic environment.
1. Reports and queries.
2. Data, text and Web mining and other sophisticated mathematical and statistical tools.

Front 66

Data Mining

Back 66

a process of searching for unknown relationships or information in large databases or data warehouses, using intelligent tools such as neural computing, predictive analytics techniques, or advanced statistical methods

Front 67

Business Performance Management (BPM)
(also known as Corporate Performance Management (CPM))

Back 67

an emerging portfoloiuo of applications and methodology that contains evolving BI architecture and tools in its core. BPM extends the monitoring, measuring and comparing of sales, profit, cost, profitability, and other performance indicators by introducing the concept of management and feedback.
Provides a top-down enforcement of corporate-wide strategy.

Front 68

User Interface

Back 68

Dashboards and other information Broadcasting Tools
Dashboards - provide a comprehensive visual view of corporate performance measures, trends and exceptions Integrate information from multiple business areas and presents an at-a-glance view of the health of the organization.
Other tools are corporate portals, digital cockpits

Front 69

Styles of BI (five)

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report delivery and reporting
enterprise reporting (using dashboards and scorecards)
cube analysis (slice & dice analysis)
ad-hoc queries
statistics and data mining

Front 70

Benefits of BI

Back 70

the major benefit of BI to a company is the ability to provide accurate information when needed - including a real-time view of the corporate performance and its parts.
* Faster, more accurate reporting
* Improved decision making
* Improved customer service
* Increased revenue

Front 71

The Major Similarities and Difference between BI and DSS

Back 71

BI implies the use of a data warehouse, DSS may or may not have such a feature.
• BI uses a data warehouse, whereas DSS can use any data source (including a data warehouse).
(BI is more appropriate for large organizations because data warehouses are expensive to build and maintain but DSS can be appropriate to any type of organization)
• Most DSS are built to support decision making directly, whereas most BI systems are built to provide information that it is believed will lead to improved decision making. (Most DSS are constructed to directly support specific decision making. BI systems, are geared to provide accurate and timely information and they support decision support indirectly)
• BI has a strategy/executive orientation whereas DSS are usually oriented toward analysts
• BI systems tend to be developed with commercially available tools, whereas DSS tend to use more custom programming to deal with problems that may be unstructured.
• DSS methodologies and tools were developed mostly in Academia. BI methodologies and tools were developed mostly by software companies.
• Many of the tools that BI uses are also considered DSS tools. (e.g., data mining and predictive analysis are core tools in both areas)

Front 72

List and describe the major tangible and intangible benefits of BI.

Back 72

According to one survey, the major benefits of BI are faster and more accurate reporting, improved decision making, improved customer service and increased revenue. The first three are intangible; that is, they have no directly associated financial value. The last is tangible.

Front 73

Define Management Support Systems (MSS)

Back 73

refers to a broad concept of using technology to support managerial tasks in general and decision making in particular.

Front 74

Work System

Back 74

a system in which human participants and/or machines perform a business process, using information, technology, and other resources, to produce products and/or services for internal or external customers.

Front 75

What is Alter’s definition of decision support?

Back 75

The use of any plausible computerized or non-computerized means for improving decision making in a particular repetitive or non-repetitive business situation, in a particular organization.

Front 76

List the nine elements of a work system.

Back 76

business process, participants, information, technology, products/services, customers, infrastructure, environment, strategy

Front 77

In what ways can the Web facilitate the use of these tools?

Back 77

The Web facilitates the use of these tools by providing access. This includes (a) a common, familiar way to access a variety of software located anywhere and (b) a standard way for DSS to obtain data from a variety of sources.

Front 78

What is a hybrid system? What are its benefits?

Back 78

A hybrid system combines several tools and techniques to solve a problem. Its benefits are that it takes advantage of the strengths of all the tools used, rather than forcing the system to use a single tool, which may be strong in some areas but weak in others.

Front 79

Discuss the importance of ADS.

Back 79

ADS "eliminates the need for a human decision maker in a programmed decision situation. Business rules and programmed instructions are triggered by events and contingent choices are made. The greatly expanded and evolving computing infrastructure makes it increasingly cost effective to apply decision automation in situations where that had been prohibitively costly." Ask Dan! About DSS - http://dssresources.com/faq/index.php?action=artikel&id=6

Front 80

Discuss how a wireless system can support decision making.

Back 80

Managers/Executives can have access to the tools in any area of the business, they do not have to be at their desks. They can pull data during any meeting, discussion, or any opportunity that presents and are not tethered to their desk. Helps defray the need for re-visiting the process at a later time.

Front 81

Tool

Back 81

a reusable analytical solution designed to be handed off to nontechnical end users to assist them in solving a repeated business problem.

Front 82

Working Definition of Decision Making

Back 82

a process of choosing among two or more alternative courses of action for the purpose of attaining one or more goals.

Front 83

Behavioral Disciplines of Decision Making

Back 83

anthropology, law, philosophy, political science, psychology, social psychology, sociology

Front 84

Scientific Disciplines of Decision Making

Back 84

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

Front 85

Effectiveness

Back 85

"goodness" of the decision produced rather than on the computational efficiency of obtaining it.

Front 86

Decision Style

Back 86

the manner by which decision makers think and react to problems. Includes the way they perceive a problem, their cognitive responses, and how values and beliefs vary from individual to individual, and from situation to situation.

Front 87

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

Back 87

• What are the root issues underlying the decision situation? Do we understand the problem sufficiently to support it?
• How structured is the decision? Is it unstructured, semi-structured, or structured?
• Does the decision involve judgment? To what extent?
• What data is needed to solve the problem?
• Can an existing tool be leveraged or reused?
• Is a tool needed?
• What is the implementation plan?

Front 88

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

Back 88

• Before building a model, decision makers should develop a good understanding of the problem that needs to be addressed.
• Coming up with nonmodeling solutions is important because if the problem is due to conflicting priorities, or the misalignment of incentives or unclear lines of authority or plans, then no DSS can help support the decision.
• A model many not be necessary to address the problem.
• Before developing a new tool, decision makers should explore reuse of existing tools.
• The goal of model building is to gain better insight into the problem, not just to generate more numbers.

Front 89

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

Back 89

• Implementation plans should be developed along with the model. Successful implementation results in solving the real problem.
• Including the end users in the development process enhances the decision makers’ analytical knowledge and capabilities. And by working together, their knowledge and skills complement each other in the final solution and the success of the implementation.

Front 90

What are the various aspects of decision making?

Back 90

Aspects of decision making that are important to understand if we are to develop effective computer support include the following:
* characteristics of decision making, such as groupthink, experimentation, and information overload.
* decision styles of the decision makers
* objectives of the decision makers
* supporting disciplines, styles and how they relate to the personal characteristics of the decision maker, and the nature of group involvement in the decision (if any).
* rationality of the decision maker. A decision maker should not simply apply IT tools blindly. Rather, the decision maker gets support through a rational approach that simplifies reality and provides a relatively quick and inexpensive means of considering various alternative courses of action to arrive at the best or a good solution to the problem.

Front 91

Why is decision making so complex in today’s business environment?

Back 91

Today’s business environment is extremely dynamic. While the decision is being made, changes may be occurring in the decision-making environment. Those changes may invalidate the assumptions upon which the decision is based.
There is time pressure from these same changes in the decision-making environment may affect decision quality by imposing time pressure on the decision maker. The fast-changing business environment often requires faster decisions, which may actually be detrimental to decision quality. The cost and expense of collecting information and analyzing a problem, with the difficulty of determining when to stop and make a decision; possible lack of sufficient information to make an intelligent decision; and conversely the possible availability of too much information (information overload).

Front 92

3. Identify similarities and differences between individual versus group decision making.

Back 92

• Individual decision makers need access to data and to experts who can provide advice, while groups additionally need collaboration tools.
• There are often conflicting objectives in a group decision-making setting, but not in an individual setting.
• Groups can be of variable size and may include people from different departments or from different organizations. Collaborating individuals may therefore have different cognitive styles, personality types, and decision styles. Some clash, whereas others are mutually enhancing.
• Consensus can be a difficult political problem in group decision making which is not a problem in individual decision making.
For these and similar reasons, group decision making can be more complicated than individual decision making

Front 93

Compare decision making versus problem solving. Determine whether or not it makes sense to distinguish the two from one another.

Back 93

They are quite similar activities. Some people consider decision making as the first three steps in problem solving. Others use the terms interchangeably. Those who distinguish between them consider decision making to be the process of making a recommendation, whereas problem solving includes the implementation of the recommendation (and perhaps monitoring its effects to determine whether or not the problem has been solved).

As experts on the subject disagree on whether or not it makes sense to distinguish between the two concepts, there is no single correct answer to the second part of this question.

Front 94

Define decision style and describe why it is important to consider in the decision-making process.

Back 94

Decision style is the manner in which a decision maker thinks and reacts to problems. It is important to consider it because different decision styles require different types of support.

Front 95

Model

Back 95

A simplified representation or abstraction of reality.(complexity is actually irrelevant in solving a specific problem.)

Front 96

Iconic Model (Scale Model)

Back 96

the least abstract type of model - is a physical replica of a system, usually on a different scale from the original. May be 3D.

Front 97

Analog Models

Back 97

behaves like the real system but does not look like it. It is more abstract than an iconic model and is a symbolic representation of reality. Usually 2D charts or diagrams.
Examples: Organization charts that depict structure, authority, and responsibility relationships; Maps on which different colors represent objects; stock market charts that represent the price movements of stocks; blueprints of a machine or a house;; animations, videos and movies.

Front 98

Mental Models

Back 98

descriptive representations of decision-making situations that people form in their heads and think about. Typically used when there are mostly qualitative factors in the decision-making problem.
Help frame the decision-making situation, a topic of cognition theory.

Front 99

Mathematical (Quantitative) Models

Back 99

mathematical descriptions of more abstract models. Most DSS analyses are performed numerically with mathematical or other quantitative models.

Front 100

Benefits of Models

Back 100

* easier to manipulate than a real system. Experimentation is easier and doesn't interrupt daily operations.
* enable the compression of time - years can be simulated in minutes or seconds of computer time.
* cost of modeling analysis is much lower than the cost of a similar experiment on a real system.
* cost of making mistakes during a trial-and-error experiment is much lower when models are used
* a manager can estimate the risks resulting from specific actions.
* 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 via the web
* Many Java applets are available to readily solve models.

Front 101

Describe the different categories of models.

Back 101

Categories of models that can be useful in business include iconic (scale, physical) models, analog models, mental models, and mathematical (quantitative) models. Other types of models, such as fashion models or data models as used in system analysis and design, are not relevant to this context but share the underlying concept of representing some aspect of a real system, having advantages over it for a specific purpose and lacking features that would permit them to replace it.

Front 102

The relevance of decision-making methods to DSS/BI -The key reason is in the word “support” in the term DSS.

Back 102

We are discussing systems that support people who make decisions, not systems that make decisions on their own. People who make business decisions are often high enough in the organization to have choices as to how they make their decisions, so it is important to support decision-making methods and styles that they are willing to use.

Front 103

How can mental models be utilized in decision making involving many qualitative factors?

Back 103

Mental models, which are typically used when a decision involves mostly qualitative factors, can help frame the decision-making situation and can work through scenarios to consider the risks and benefits of alternative decisions

Front 104

How can modern IT tools help synthesize qualitative and quantitative factors in decision making?

Back 104

Modern information technology tools can present qualitative factors along with its analysis of quantitative factors, so decision makers can consider both together and use the qualitative information to guide them to the most useful quantitative analyses.

Front 105

List and briefly describe Simon’s four phases of decision making.

Back 105

Simon’s four phases of decision making are intelligence, design, choice, and implementation.

Intelligence consists of gathering information by examining reality, then identifying and defining the problem. In this phase problem ownership should also be established.

Design consists of determining alternatives and evaluating them. If the evaluation will require construction of a model, that is done in this phase as well.

The choice phase consists of selecting a tentative solution and testing its validity.

Implementation of the decision consists of putting the selected solution into effect.

Front 106

Why is a fifth phase, evaluation, not necessary?

Back 106

The authors of this book view monitoring as a manifestation of the intelligence phase, applied to the implementation of a decision. Like any other intelligence phase, it may lead to a future decision.

Front 107

Problem

Back 107

a negative discrepancy between what is and what a decision maker feels should be.

Front 108

What can cause a problem to exist in decision making?

Back 108

A problem can result from a change in the decision maker’s expectations or from a change in the situation. Expectations can be raised, creating such a discrepancy, by (for example) seeing how competitors have improved their operations. The situation can change in many ways: higher costs, lower market share, etc.

Front 109

Steps of Intelligence Phase

Back 109

Organization objectives
Search and Scanning procedures
(Simplification\Assumptions)
Data collection
Problem identification
Problem ownership
Problem classification
Problem statement
Combined = Problem Statement

Front 110

Steps of Design Phase`

Back 110

(Validation of the Model)
Formulate a model
Set criteria for choice
Search for alternatives
Predict and measure outcomes
Combined = Alternatives

Front 111

Steps of Choice Phase

Back 111

(Verification, testing of proposed solution)
Solution to the model
Sensitivity analysis
Selection of the best (good) alternative(s)
Plan for Implementation

Front 112

Final Phase

Back 112

Implementation
Can equal failure - results in returning to an earlier phase
Can equal success - real problem is solved.

Front 113

Problem Identification

Back 113

(Intelligence Phase)
Begins with the identification of organizational goals and objectives related to an issue of concern and determination of whether they are being met.

Front 114

Dissatisfaction

Back 114

The result of a difference between what people desire (or expect) and what is occurring.

Front 115

What are the most difficult steps in problem analysis?

Back 115

the collection of data and the estimation of future data

Front 116

Issues that may arise during data collection:

Back 116

* Data are not available.
* Obtaining data may be expensive
* Data may not be accurate or precise enough.
* Data estimation is often subjective
* Data may be insecure
* Important data that influence the results may be qualitative (soft)
* There may be too many data (information overload)
* Outcomes (or results) may occur over an extended period resulting in revenues, expenses, and profits being recorded at different points in time.
* It is assumed that future data will be similar to historical data. Otherwise, the nature of the change has to be predicted and included in the analysis

Front 117

Problem Classification

Back 117

the conceptualization of a problem in an attempt to place it in a definable category - possibly leading to a standard solution approach. An important approach classifies according to the degree of structuredness evident in them.

Front 118

Problem Decomposition

Back 118

dividing complex problems into sub-problems. Solving the simpler sub-problems may help in solving a complex problem.

Front 119

Problem Ownership

Back 119

A problem exists in an organization only if someone or some group takes on the responsibility of attacking it and if the organization has the ability to solve it. The assignment of the authority to solve the problem is problem ownership.

Front 120

What is the difference between a problem and its symptoms?

Back 120

Problems arise out of dissatisfaction with the way things are going. It is the result of a difference or gap between what we desire and what is or is not) happening. A symptom is how a problem manifests itself.
A business example: high prices (problem) and high unsold inventory level (symptom). Another is quality variance in a product (symptom) and poorly calibrated or worn-out manufacturing equipment (problem).

Front 121

Why is it important to classify a problem?

Back 121

Classifying a problem enables decision makers to use tools that have been developed to deal with problems in that category, perhaps even including a standard solution approach.

Front 122

Why is establishing problem ownership so important in the decision-making process?

Back 122

Problem ownership means having the authority, and taking the responsibility, of solving it. Lack of problem ownership means either that someone is not doing his or her job, or that the problem at hand has yet to be identified as belonging to anyone. In either case, it cannot be solved until someone owns it.

Front 123

Design Phase

Back 123

involves finding or developing and analyzing possible courses of action including understanding the problem and testing solutions for feasibility. A model is constructed, tested, and validated.

Front 124

Decision Variables

Back 124

describe the alternatives a manger must choose from

Front 125

Result Variable

Back 125

(e.g., profit, revenue, sales) describes the objective or goal of the decision-making problem and uncontrollable variables or parameters that describe the environment.

Front 126

Principle of Choice

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criterion that describes the acceptability of a solution approach. In a model, it is a result variable. Involves how a person establishes decision-making objective(s) and incorporates the objective(s) into the models.

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Normative Models

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models in which the chosen alternative is demonstrably the best of all possible alternatives.

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Optimization

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the decision maker should examine all the alternatives and prove that the one selected is indeed the best, which is what the person would normally want.

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Three ways to achieve optimization:

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1. Get the highest level of goal attainment from a given set of resources. e.g. which alternative will yield the max profit from an investment
2. Find the alternative with the highest ratio of goal attainment to cost (e.g., profit per dollar invested)or maximize productivity.
3. Find the alternative with the lowest cost (or smallest amount of other resources) that will meet an acceptable level of goals.

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Normative decision theory is based on the following assumptions of rational decision makers: (three)

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* Humans are economic beings whose objective is to maximize the attainment of goals that is, the decision maker is rational.
* For a decision-making situation, all viable alternative courses of action and their consequences, or at least the probability and the values of the consequences, are known.
* Decision makers have an order of preference that enables them to rank the desirability of all consequences of the analysis (best to worst).

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Suboptimization

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By simplifying, the model then does not incorporate certain complicated relationships that describe interactions with and among the other departments. The other departments can be aggregated into simple model components.
May also involve simply bounding the search for an optimum by considering fewer criteria or alternatives or by eliminating large portions of the problem from evaluation. (a good enough solution)

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Descriptive Models

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describe things as they are or as they are believed to be. Typically mathematically based models. Extremely useful in DSS for investigating the consequences of various alternative courses of action under different configuration of inputs and processes.

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Simulation

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Probably the most common descriptive modeling method. I is the imitation of reality and has been applied to many areas of decision making.
e.g., computer and video games

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Classes of Descriptive Models

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* Complex inventory decisions
* Environmental impact analysis
* Financial planning
* Information flow
* Markov analysis (predictions)
* Scenario analysis
* Simulation (alternative types)
* Technological forecasting
* Waiting-line (queuing) management

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Cognitive Map

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A non-mathematical descriptive model that sketches out the important qualitative factors and heir causal relationships in a messy decision-making situation. Helps to focus on what is relevant and what is not, and the map evolves as more is learned about the problem.

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Narrative

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A descriptive decision-making model - a story that helps a decision maker uncover the important aspects of the situation and leads to better understanding and framing. Extremely effective for group decision-making.

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Satisficing

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the decision maker sets up an aspiration, a goal, or a desired level of performance and then searches the alternatives until one is found that achieves this level.

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Usual Reasons for Satisficing

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time pressures
ability to achieve optimization

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Bounded Rationality

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Humans have a limited capacity for rational thinking; they generally construct and analyze a simplified model of a real situation by considering fewer alternatives, criteria, and/or constraints than actually exist

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Developing (Generating) Alternatives.

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The least formal aspect of problem solving!
Alternatives can be generated and evaluated using heuristics. Can be supported by electronic brainstorming.

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Measuring Outcomes

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The value of an alternative is evaluated in terms of goal attainment.

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Risk

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(measured as probability) Unpredictable events in both the economic and physical environments.

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Scenarios

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a statement of assumptions about the operating environment of a particular system at a given time. A narrative description of the decision-situation setting
A scenario describe the decision and uncontrollable variables and parameters for a specific modeling situation.

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Role of Scenarios:

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* 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, as described by the scenario.

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Possible Scenarios: (four)

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The worst possible scenario
The best possible scenario
The most likely scenario
The average scenario

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Define optimization and contrast it with suboptimization

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Optimization refers to the “best.” (There is no such thing as “more” optimal!) To achieve it, all alternatives must be considered, and the optimal one must be the best. Suboptimization is the optimization of a subsystem, without considering its impacts on other parts of the overall system. What is optimal for a part of a system (or organization) may not be for the entire system (or organization).

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Compare the normative and descriptive approaches to decision making.

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Normative decision making uses models, or methods that have perhaps previously been derived from models that tell a decision maker what they should do. These prescriptive models are often developed by utilizing optimization methods.
Descriptive decision making uses models that tell a decision maker “what-if.” These are usually simulation models.

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Define rational decision making. What does it really mean to be a rational decision maker?

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Rational decision making follows the economic assumptions of rationality. A rational decision maker exhibits certain assumed behaviors: (1) Humans are economic beings, whose objective is to maximize the attainment of goals; (2) for a decision-making situation, all viable alternative courses of action and their consequences, or at least the probability and the values of the consequences are known; and (3) decision makers have an order or preference that enables them to rank the desirability of all consequences of the analysis (best to worst).
Being a rational decision maker means making decisions according to these assumptions.

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Why do people exhibit bounded rationality when problem solving?

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Humans in general have limitations that prevent us from being completely rational. We usually simplify things. Individuals’ evaluation scales for the costs and benefits of a decision may be nonlinear and may not follow those of the organization. Also, individual characteristics may result in a restricted rationality.

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Define scenario. How is a scenario used in decision making?

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A scenario is a statement of assumptions about the operating environment of a particular system in a given time. It describes the system's configurations. By changing scenarios and measuring the goal attainment level, it is possible to compare alternatives under different sets of conditions.

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Some “errors” in decision making can be attributed to the notion of decision making from the gut. Explain what is meant by this and how such errors can happen.

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People have a tendency to measure uncertainty and risk badly. They tend to be overconfident and have an illusion of control in decision making. As a result, decisions in which some part of the future is unknown, which is true of most business decisions, are often made more optimistically than they should.
"Intuition" used in decision making.

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Explain the difference between a principle of choice and the actual choice phase of decision making.

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A principle of choice is a criterion used to describe the acceptability of a solution approach-it is a basis for deciding whether one approach or another is superior. A principle of choice is general: it applies to many possible decision-making situations.
The choice phase of decision making uses one or more principles of choice, chosen during this decision phase or prior to it, to select an alternative in a specific situation.

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Why do some people claim that the choice phase is the point in time when a decision is really made?

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Because it is. The decision, choosing one of the available alternatives, is made during this stage. It is, therefore, easy to equate the two.
However, the choice phase as the term is usually used covers more than this single point in time. It also includes the comparisons that lead up to it and the assessment of robustness and possible adverse consequences that may lead a decision maker to choose an alternative that is less desirable under ideal conditions but also less likely to lead to disaster in other circumstances

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How can sensitivity analysis help in the choice phase?

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Sensitivity analysis determines how an alternative responds to small changes in the input parameters. An alternative that appears best for the nominal set of parameters might produce far worse results for small changes in them. Another alternative, which might not be as attractive if all parameters have their nominal values, might be more robust—that is, it might not degrade as much if they depart from those values. It might therefore be a better choice in practice, since some statistical variation in these values is only to be expected.

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Why do people attempt to narrow the definition of DSS?

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a

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Give your own definition of DSS. Compare it to the definitions in question 1. (Question 2)

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b

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Explain how the system described in Application Case 3.1 is a DSS. (Use the definition from question 2.

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c

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Business Analytics (BA)

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Implies the use of models and data to improve an organization's performance or competitive posture. Focus is on the use of models.
Advanced models are rarely used in BI.

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Web Analytics

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an approach to using business analytics tools on real-time Web information to assist in decision making. (mostly related to e-commerce)

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Predictive Analytics

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describes the business analytics method of forecasting problems and opportunities rather than simply reporting them as they occur. utilizes advanced forecasting and simulation models.

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List the Key Characteristics and capabilities of DSS:

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1. Support for decision makers by bringing together human judgement and computerized information
2. Support for all managerial levels
3. Support for individuals/groups
4. Support for interdependent and/or sequential decisions
5. Support in all phases of decision making process : intelligence, design, choice, and implementation.
6. Support for a variety of decision-making processes and styles.
7. Decision maker should be reactive, able to confront changing conditions quickly and able to adapt the DSS to meet these changes.
8. User-friendliness, strong graphical capabilities, and a natural language interactive human-machine interface can greatly increase the effectiveness of DSS.
9. Improvement of effectiveness of decision making rather than its efficiency.
10. Decision maker has complete control over all steps of process in solving a problem.
11. End users are able to develop and modify simple systems by themselves.
12. Models are generally utilized to analyze decision-making situations.
13. Access is provided to a variety of data sources, formats and types
14. The DSS can be employed as a stand-alone tool used by an individual decision maker in one location or distributed throughout an organization.

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Describe how providing support to a workgroup is different from providing support to group work. Explain why it is important to differentiate these concepts.

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1

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What kinds of DSS can end users develop in spreadsheets?

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2

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Why is it so important to include a model in a DSS?

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3

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Categories of the AIS SIGDSS Classification for DSS:

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* communications driven and group DSS (GSS)
* Data driven DSS
* Document-driven DSS
* Knowledge-driven DSS, data mining, and management ES applications.
* Model-driven DSS
Note: there may be hybrids that combine two or more categories, these are called Compound DSS

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Communications-Driven and Group DSS

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Communications-driven and Group DSS include DSS that use computer, collaboration, and communication technologies to support groups in tasks that may or may not include decision making.

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Data-Driven DSS

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Data-driven DSS are primarily involved with data and processing them into information and presenting the information to a decision maker. Many DSS developed in OLAP and data mining software systems fall into this category.

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Document-Driven DSS

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rely on knowledge coding analysis, search. and retrieval for decision support. essentially include all DSS that are text based.

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Knowledge-Driven DSS, Data Mining, and Management Expert Systems Applications.

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Involve the application of knowledge technologies to address specific decision support needs. (all artificial intelligence-based DSS fall into this category.)

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Model-Driven DSS

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major emphases of DSS that are primarily developed around one or more (large-scale?complex) optimization or simulation modes typically include significant activities in model formulation. model maintenance, model management in distributed computing environments, and what-if analyses. (Most large-scale operations are in this category.)

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Compound DSS

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A compound, or hybrid,
Dss includes two or more of the major categories described earlier.

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Holsapple and Whinston's Classification

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Classified DSS into the following six frameworks:
text-oriented DSS, (same as Document driven)
Database-oriented DSS, (data-driven DSS of the AIS SIGDSS)
spreadsheet-oriented DSS, (Fx & Addins of spreadsheet program are used to create & management models)
solver-oriented DSS, (map directly into the model-driven DSS)
rule-oriented DSS (include most knowledge-driven DSS, data mining and management ES Aps)
and, compound DSS (integrates 2 fr: above and id defined same as by the SIGDSS)

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Alter's Output Classification

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(1980) classification is based on the "degree of action implication of system outputs," or the extent to which system outputs can directly support or determine the decision.
There are 7 categories:
(data oriented) performing data retrieval or analysis, deals both with data and models,
(remaining 4) model oriented, providing simulation capabilities, optimization, computations that suggest an answer

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Institutional DSS

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Donovan and Madnick 1977
Deal with decision of a recurring nature. Used repeatedly to solve identical or similar problems.

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Ad hoc DSS

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Deal with specific problems that are usually neither anticipated nor recurring. Often involve strategic planning issues and sometimes management control problems.

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Personal Support

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focus is on an individual user performing an activity in a discrete task or decision. task is fairly independent of other tasks.

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Group Support

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focus is on a group of people, all of whom are engaged in separate but highly interrelated tasks. e.g., typical finance dept.

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Organizational Support

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focus is on organizational tasks or activities involving a sequence of operations, different functional areas, possibly different locations, and massive resources. (may be considered enterprise-wide support)

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Ready-made DSS

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a generic DSS that can be used (sometimes with modifications) in several organizations. Essentially the models, interface and other support features are built in, just add an organizations data and logo.