types of decisions programmed decisions situations that occur often enough to enable decision rules...
TRANSCRIPT
Types of Decisions
Programmed decisions situations that occur often enough to enable
decision rules to be developed.
Nonprogrammed decisions are made in response to situations that are
unique, are poorly defined and largely unstructured.
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Decision Making Conditions Certainty
all the information the decision maker needs is fully available.
Risk decision has clear-cut goals. good information is available. future outcomes associated with each
alternative are subject to chance.
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Decision Making Conditions (contd.) Uncertainty
managers know which goals they wish to achieve.
information about alternatives and future events is incomplete.
managers may have to come up with creative approaches to alternatives.
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Decision Making Conditions (contd.) Ambiguity
by far the most difficult decision situation. goals to be achieved or the problem to be
solved is unclear. alternatives are difficult to define. information about outcomes is unavailable.
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Ex. 6.1 Conditions That Affect the Possibility of Decision Failure
OrganizationalProblem
ProblemSolution
Low HighPossibility of Failure
Certainty Risk Uncertainty Ambiguity
ProgrammedDecisions
NonprogrammedDecisions
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Three Decision Making Models
Classical ModelClassical Model
Administrative ModelAdministrative Model
Political ModelPolitical Model
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Decisions and Decision Making A decision is a choice made from available
alternatives.
Decision making is the process of identifying problems and opportunities and then resolving them.
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Ex. 6.2 Characteristics of Classical, Administrative, and Political Decision-Making Models
Classical Model Administrative Model Political Model
Clear-cut problem and goals.
Condition of certainty.
Full information about alternatives and their outcomes.
Rational choice by individual for maximizing outcomes.
Vague problem and goals.
Condition of uncertainty.
Limited information about alternatives and their outcomes.
Satisfying choice for resolving problem using intuition.
Pluralistic; conflicting goals.
Condition of uncertainty/ambiguity.
Inconsistent viewpoints; ambiguous information.
Bargaining and discussion among coalition members.
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Ex. 6.3 Six Steps in the Managerial Decision-Making Process
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Diagnosis Questions(Kepner & Tregoe)
What is the state of disequilibrium affecting us? When did it occur? Where did it occur? How did it occur? To whom did it occur? What is the urgency of the problem? What is the interconnectedness of events? What result came from what activity?
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Ex. 6.5 Personal Decision Framework
Situation:· Programmed/non-programmed· Classical, administrative,
political· Decision steps
Decision Choice:·Best Solution to Problem
Personal Decision Style:·Directive·Analytical·Conceptual·Behavioural
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Participation in Decision MakingDiagnostic Questions
Decision significance Importance of commitment Leader expertise Likelihood of commitment Group support for goals Group expertise Team competence
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Information Technology
The hardware, software, telecommunications, database management, and other technologies used to store data and make them available in the form of information for organizational decision making.
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Ex. 6.8 Characteristics of High-Quality Information
TimeTimelinessCurrency
FrequencyTime Period
Content Accuracy Relevance
Completeness Conciseness
ScopePerformance
Form ClarityDetailOrder
PresentationMedia
Source: Adapted from James A. O’Brien, Introduction to Information Systems, 8th ed. (Burr Ridge, Ill, Irwin, 1997),284-285.
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Ex. 6.10 Basic Elements of Management Information Systems
Operations Information Systems
Management Information Systems
Reporting Systems
Decision Support Systems
Executive Information Systems
Groupware
Systems
Corporate and External Databases
SOURCE: Adapted from Ralph M. Stair and George W. Reynolds, Principles of Information Systems: A Managerial Approach , 4th ed. (Cambridge, Mass.: Course Technology, 1999), 391.
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Management and Technology Implications
Improved employee effectiveness.
Increased efficiency.
Empowered employees.
Information overload.
Enhanced collaboration.
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Decision Process
Decision Complexity
Characteristics and Capabilities of DSS
Sensitivity analysis is the study of the impact that changes in one (or more) parts of a model have on other parts.
What-if analysis is the study of the impact of a change in the assumptions (input data) on the proposed solution.
Goal-seeking analysis is the study that attempts to find the value of the inputs necessary to achieve a desired level of output.
DSS: Current Definitions
A DSS is an interactive system that helps people make decisions, use judgment, and work in areas where no one knows exactly how the task should be done in all cases. DSS’s support decision making in semi-structured and unstructured domains, and provide information, models, or tools for manipulating data (Alter, 1995).
DSS: Current Definitions - 2
A computer program that provides information in a given domain of application by means of analytical decision models and access to databases, in order to support a decision maker in making decisions effectively in complex and ill-structured (non-programmable) tasks (Klein and Methlie, 1995).
The Role of MIS
Management Information Systems: impact on structured tasks where standard operating
procedures, decision rules, and information flows can be readily defined.
Main payoff in improving efficiency by reducing costs, turnaround time, and so on by replacing clerical personnel.
Relevance for manager’s decision making has been mainly indirect, (e.g. providing reports and access to data).
DSS: Working Definition
A DSS is an interactive, flexible, and adaptable computer-based information system that utilizes decision rules, models, and model base coupled with a comprehensive database and the decision maker’s own insights, leading to specific, implementabale decisions in solving problems that would not be amenable to management science optimization models per se. Thus, a DSS supports complex decision making and increases its effectiveness.
Idealized Characteristics and Capabilities of a DSS Provide support in semi-structured and unstructured situations
by bringing together human judgment and computerized information.
Support is provided for various management levels ranging from top management to line managers.
Support is provided to individuals as well as groups. Supports several independent and/or sequential decisions.
Idealized Characteristics and Capabilities of a DSS - 2
Supports all phases of the decision-making process: Intelligence, Design, Choice
Supports a variety of decision-making processes and styles, e.g. a fit between the DSS and attributes of the decision makers.
DSS must be adaptive over time DSS must be easy to use. DSS attempts to improve the effectiveness of the decision
rather than efficiency.
Idealized Characteristics and Capabilities of a DSS - 3
Decision maker has complete control over all steps of the process. It supports, not replaces the decision maker.
DSS leads to learning, which leads to new demands, and the refinement of the system.
DSS should be easy to construct.
What-If Analysis
Model maker makes predictions and assumptions regarding the input data.
When a model is solved, the future depends on this data.
What If the cost of carrying inventory increases 15%?
What will be the market share if advertising budget increases by 5%?
Goal Seeking
Attempts to find the value of inputs necessary to achieve a desired output level.
Represents a “backwards” solutionIf an initial analysis yields profits of $2
million, what sales volume is necessary for a profit of $2.2 million?
DSS Components
Data Management DSS database Database Management System Data Directory Query facility
Model Management Model Base Model base management system Model Directory Model execution, integration, and command
Communication (dialogue) subsystem.
Types of Models: Strategic
Strategic Models -use to support top management’s strategic planning responsibilities
tend to be broad in scope with many variables expressed in a compressed form. The models tend to be of a descriptive (simulation) rather than an optimization nature.
Examples: develop corporate objectives environmental impact analysis non-routine capital budgeting
Types of Models: Tactical
Used by middle management in allocating and controlling the organization’s resources.
May be applicable only to one organizational unit or subsystem (e.g. accounting subsystem).
Some are optimization while others are descriptive in nature. Examples:
labour requirement planning sales promotion planning plant layout determination routine capital budgeting
Types of Models: Operational
Operational Models are used to support day to day working activities of the organization.
Examples: approving personal loans by a bank production scheduling inventory control maintenance planning and scheduling quality control
Model Building Blocks
In addition to strategic, tactical, and operational models, the model base could contain model building blocks and subroutines.
Examples: random number generators curveline fitting routines present-value computational routines regression analysis
All of the above can be used individually for data analysis or combined as components of larger, more complex models.
Subscription Model
Decision maker receives outputs from the DSS on regular basis
Terminal Mode
Direct use of the DSS by the decision maker Access is through individual terminals May be user specific requirements
Clerk Mode
Decision maker fills out a form requesting output from DSS
A clerk accesses the DSS Sends the output to the decision maker
Intermediary Mode
Decision maker uses the DSS with the help of a professional, knowledgeable assistant
The assistant can be either a: Staff Assistant Technical Support Staff Business Analyst
Structure and Components of DSS
Data management subsystem contain all the data that flow from several sources.
Model management subsystem contains completed models and the building blocks necessary to develop DSS applications.
User interface covers all aspects of the communications between a user and the DSS.
Users are the persons faced with the problem or decision that the DSS is designed to support.
Knowledge-based subsystems provide the required expertise for solving some aspects of the problem.
DSS Process
Executive Information (Support) Systems
Executive information system (EIS) also known as an executive support system (ESS), is a computer-based technology designed specifically for the information needs of top executives and provides for: Rapid access to timely information; Direct access to management reports; Very user friendly and supported by graphics. Exception reporting – reporting of only the results that deviate
from a set of standards. Drill down reporting – investigating information in increasing
detail. Easily connected within online information services and e-mail. Include analysis support, communications, office automation and
intelligence support.
Intelligent Systems
Expert systems (ESs) are attempts to mimic human experts. It is decision-making software that can reach a level of performance comparable to a human expert in some specialized and usually narrow problem area. The idea is simple: expertise is transferred from an expert or other source of expertise to the computer. The transfer of expertise from an expert to a computer and then to the user
involves four activities:
Knowledge acquisition (from experts or other sources)
Knowledge representation (organized as rules or frames in the computer)
Knowledge inferencing is performed in a component called the inference engine of the ES and results in the recommendation.
Knowledge transfer to the user (the expert’s knowledge has been transferred to users).
Intelligent Systems (cont’d)
The Benefits of Expert Systems
Reduce downtime
Decreased decision-making time
Enhancement of decision- making and problem-solving capabilities
Provision of training
Ability to work with incomplete or uncertain information
Reliability
Accessibility to knowledge and help desks
Operation in hazardous environments
Capture and dissemination of scarce expertise
Increased quality
Increased output and productivity
Benefit
ESs can quickly diagnose faster decisions than humans and prescribe repairs.
ESs usually can make faster decision than humans working alone.
ESs allow the integration of expert judgment into analysis (e.g., diagnosis of machine malfunction and even medical diagnosis).
The explanation facility of an ES can serve as a teaching device and knowledge base for novices.
Even with answer of ‘ don’t know ‘ an ES can produce an answer, though it may not be a definite one.
ESs do not become tired or bored, call in sick or go on strike. They consistently pay attention to details.
ESs can increase the productivity of help – desk employee, or even automate this function.
Sensors can collect information that an ES interprets, enabling human workers to avoid hot, humid, or toxic environments.
Expertise from anywhere in the world can be obtained and used.
ESs can provide consistent advise and reduce error rates.
ESs can configure for each custom order. Increasing production capabilities
Description
Neural Networks
Neural networks are a system of programs and data structures that approximates the operation of the human brain.
Neural networks are particularly good at recognizing subtle, hidden, and newly emerging patterns within complex data as well as interpreting incomplete inputs.
Fuzzy Logic
Fuzzy logic deals with the uncertainties by simulating the process of human reasoning, allowing the computer to behave less precisely and logically than conventional computers do. Involves decision in gray areas. Uses creative decision-making processes.
Simulation Systems
Simulation generally refers to a technique for conducting experiments (such as "what-if") with a computer on a model of a management system. Because DSS deals with semi structured or unstructured situations, it involves complex reality, which may not be easily represented by optimization or other standard models but can often be handled by simulation. Therefore, simulation is one of the most frequently used tools of DSS.
Advantages of Simulation. Allows for inclusion of the real-life complexities of problems.
Is descriptive.
Can handle an extremely wide variation in problem types.
Can show the effect of compressing time.
Can be conducted from anywhere.
Why Managers Need IT Support
A key to good decision making is to explore and compare many relevant alternatives. The more alternatives that exist, the more computer-assisted search and comparisons are needed.
Typically, decisions must be made under time pressure. Frequently it is not possible to manually process the needed information fast enough to be effective.
Why Managers Need It Support Contd..
It is usually necessary to conduct a sophisticated analysis in order to make a good decision. Such analysis requires the use of modelling.
Decision makers can be in different locations and so is the information. Bringing them all together quickly and inexpensively may be a difficult task.
Managerial Issues
Cost justification, intangible benefits. While some of the benefits of management support systems are tangible, it is difficult to put a dollar value on the intangible benefits of many such systems.
Documenting personal DSS. Many employees develop their own DSS to increase their productivity and the quality of their work. It is advisable to have an inventory of these DSS and make certain that appropriate documentation and security measures exist.
Security. Decision support systems may contain extremely important information for the livelihood of organizations. Taking appropriate security measures, especially in Web-based distributed applications, is a must.
Ready-made commercial DSS. With the increased use of Web-based systems and ASPs, it is possible to find more DSS applications sold off the shelf, frequently online. The benefits of a purchased or leased DSS application sometimes make it advisable to change business processes to fit a commercially available DSS.
Managerial Issues (Continued)
Intelligent DSS. Introducing intelligent agents into a DSS application can greatly increase its functionality.
Organizational culture. The more people recognize the benefits of a DSS and the more support is given to it by top management, the more the DSS will be used.
Embedded technologies. Intelligent systems are expected to be embedded in at least 20 percent of all IT applications in about 10 years. It is critical for any prudent management to closely examine the technologies and their business applicability.
Ethical issues. Corporations with management support systems may need to address some serious ethical issues such as privacy and accountability.
The DSS Hierarchy
Suggestion systemsSuggestion systems Optimization systemsOptimization systems Representational Representational
modelsmodels Accounting modelsAccounting models Analysis information Analysis information
systemssystems Data analysis systemsData analysis systems File drawer systemsFile drawer systems
File Drawer Systems
They are the simplest type of DSS Can provide access to data items Data is used to make a decision ATM Machine Use the balance to make transfer of funds
decisions
Data Analysis Systems
Provide access to data Allows data manipulation capabilities Airline Reservation system No more seats available Provide alternative flights you can use Use the info to make flight plans
Analysis Information Systems
Information from several files are combined Some of these files may be external We have a true “data base” The information from one file, table, can be
combined with information from other files to answer a specific query.
Accounting Models
Use internal accounting data Provide accounting modelling capabilities Can not handle uncertainty Use Bill of Material
Calculate production cost Make pricing decisions
Representational Model
Can incorporate uncertainty Uses models to solve decision problem
using forecasts Can be used to augment the capabilities of
Accounting models Use the demand data to forecast next years
demand Use the results to make inventory decisions.
Optimization Systems
Used to estimate the effects of different decision alternative
Based on optimization models Can incorporate uncertainty Assign sales force to territory Provide the best assignment schedule
Suggestion Systems
A descriptive model used to suggest to the decision maker the best action
A prescriptive model used to suggest to the decision maker the best action
May incorporate an Expert System Use the system to recommend a decision Ex: Applicant applies for personal loan
DSS Categories
Support-based categories (Alter 1980)Support-based categories (Alter 1980) Data-based DSSData-based DSS Model-based DSSModel-based DSS
Nature of the decision situation (Donovan & Madnick 1977)Nature of the decision situation (Donovan & Madnick 1977) InstitutionalInstitutional Ad hocAd hoc
User-based categories (Keen 1980)User-based categories (Keen 1980) IndividualIndividual Multi-individualMulti-individual GroupGroup
DSS Categories
Support based DSSSupport based DSS Data-based DSSData-based DSS Model-based DSSModel-based DSS
Structured
Semi-structure
Unstructured
Model-basedDSS
Data-basedDSS
DSS Categories
Based on the nature of the decision situationBased on the nature of the decision situation InstitutionalInstitutional
Culture of the organizationCulture of the organization Regularly used Regularly used Used by more than one personsUsed by more than one persons
Ad hocAd hoc One of kindOne of kind One-time useOne-time use Used by single individualUsed by single individual
DSS Categories Based on number of usersBased on number of users
IndividualIndividual Multi-individualMulti-individual GroupGroup
Benefits Individual Multi-individual
Group
Improving personal efficiency H H L
Expediting problem solving L M H
Facilitating communication L L H
Promoting learning M H H
Increasing control L H M
Usage Modes
Subscription Mode Terminal Mode Clerk Mode Intermediary Mode
Simon’s ModelFlowchart of Decision Process
Intelligence
Design
Choice
Intelligence Phase
Organizational ObjectivesSearch and SCANNING ProceduresData CollectionProblem IdentificationProblem ClassificationProblem Statement
Design Phase
Formulate a ModelSet Criteria for ChoiceSearch for AlternativesPredict and Measure Outcomes
Choice Phase
Solution to the ModelSensitivity AnalysisSelection of best (good) alternative'sPlan for implementation (action)Design of a control system
The role of models in decision-making
A major characteristic of decision-making is the use of models.
A model is a simplified representation or abstraction of reality.
It is usually simplified because reality is too complex to copy.
Basis idea is that analysis is performed on a model rather than on reality itself.
Pounds’ Categories of Models - Expectations against which reality is measured
Historical - expectation based on extrapolation of past experience.
Planning - the plan is the expectation Inter-organizational - Models of other people in the
organization (e.g. superiors, subordinates, other departments, etc.)
Extra-organizational - models where the expectations are derived from competition, customers, professional organizations, etc.
Another classification of models
Iconic ModelsAnalog ModelsMathematical ModelsMental Models
Iconic and Analog Models
Iconic (scale) models - the least abstract model, is a physical replica of a system, usually based on a different scale from the original. Iconic models can scale in two or three dimensions.
Analog Models - Does not look like the real system, but behaves like it. Usually two-dimensional charts or diagrams. Examples: organizational charts depict structure, authority, and responsibility relationships; maps where different colours represent water or mountains; stock market charts; blueprints of a machine; speedometer; thermometer
Mathematical Models
Mathematical (quantitative) models - the complexity of relationships sometimes can not be represented iconically or analogically, or such representations may be cumbersome or time consuming. A more abstract model is built with mathematics.
Note: recent advances in computer graphics use iconic and analog models to complement mathematical modelling.
Visual simulation combines the three types of models.
PPT Slides by Dr. Craig Tyran
A. Decisions and IS Support1. Business people encounter many types of decisions Follow a decision making process Variety of information systems to support decision making
From Haag, et al, MIS for the Information Age, 3rd Edition, 2002.
PPT Slides by Dr. Craig Tyran
B. Decision Making Process1. Simon’s decision
making model– Simple, yet enduring
– Decision process modeled as a “flow” of events
– Can proceed in linear or iterative fashion
2. Information systems can support each phase of process
This gentleman won a Nobel Prize!
PPT Slides by Dr. Craig Tyran
B. Decision Making Process (cont.)3. Intelligence phase
– Gather data that may be used for “intelligence” purposes
– Does there seem to be a problem's) or opportunity's)?
– Define the problem or opportunity
– “Operations Mgr” scenario:• Gather data• Review of production log reveals
significant equipment downtime• Problem: Poor maintenance? (Or
could it be something else?)
• Can IS help? Which type's) of IS could be useful for this phase?
PPT Slides by Dr. Craig Tyran
B. Decision Making Process (cont.)4. Design phase
– Identify key variables– Create model to aid decision making– Validate model– Establish criteria to be used to make a
choice– Identify alternative solutions
– “Operations Mgt” scenario:• Variable: e.g., age of equipment,
cost of maintenance, etc.• Model's): e.g., statistical
regression, cost-benefit forecast model
• Establish criteria: e.g., $$• Alternatives: e.g., repair vs.
purchase for old equipment
• Can IS help? How?
PPT Slides by Dr. Craig Tyran
B. Decision Making Process (cont.)
5. Choice phase– Evaluate potential solutions using
model's) developed earlier• e.g., “What if” analysis,
Sensitivity analysis– Use criteria to choose the
preferred solution
– “Operations Mgr” scenario:• Tasks: See above• Make it easy to explore
different scenarios of interest• Convey useful information
• Can IS help? How?
PPT Slides by Dr. Craig Tyran
B. Decision Making Process (cont.)
6. Implementation phase– Implement the decision– Monitor– Make adjustments
– “Operations Mgr” scenario:• Tasks: See above
• How could and IS provide support for the above?
PPT Slides by Dr. Craig Tyran
D. DSS Components