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Decision Support Systems: A Summary,Problems, and Future Trends
M.C. ER, Decision Support Systems 4 (1988) 355-363
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Introduction Electronic Data Processing (EDP)
Transaction processing type of applications Solving the problems of tedious calculations Automating manual works
Management Information System (MIS) Processing and supplying all information needed by management
Decision Support System (DSS) [Keen and Scott Morton, 1978] Provision of information for supporting management decision
making “The application of available and suitable computer-based
technology to help improve the effectiveness of managerial decision making in semi-structured tasks.”
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Characteristics and Components of DSS Characteristics of DSS [Sprague and Carlson, 1982]
“They tend to be aimed at the less well structured, under-specified problems that upper-level managers typically face.”
“They attempt to combine the use of models or analytic techniques with traditional data access and retrieval functions.”
“They specifically focus on features that make them easy to use by non-computer people in an interactive mode.”
“They emphasize flexibility and adaptability to accommodate changes in the environment and decision-making approach of the user.”
“They support but do not replace upper-level managers in decision making (M.C. Er, 1988).”
Components of DSS [King, 1983] Decision models, interactive computer hardware and software, a data base,
a database management system, graphical and other sophisticated displays, a modeling language that is 'user friendly'.
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Decision, Support and Systems Decision
Problem solving Support
Use of computer and software technologies Passive support; Traditional support; Extended support; Normative
support Systems
A system of man-machine interactions and its design and implementation
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Types of Problems and Decision Style(1/2) Combinations of the type of problems and the levels of
the management activities (Huff, 1985)
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Types of Problems and Decision Style(2/2) Four decision style
Systematic (ST) Use quantitative measures on information Prefer cost-benefit analysis and evaluation research
Speculative (NT) Speculate future possibilities Prefer decision trees with sensitivity analysis
Judicial (SF) Concentrate on current situation Prefer the use of decision groups
Heuristic (NF) Place great emphasis on current possibilities Prefer reaching decisions through mutual adjustment
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DSS Development(1/2) Four-stage process for developing a DSS (continue)
1. Decision support analysis Structured interviews Decision analysis Data analysis Technical analysis Conceptual DSS orientation Plans and prioritization
2. DSS software evaluation and selection Identification of candidate vendors Feature analysis Benchmarks External site surveys
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DSS Development(2/2) Four-stage process for developing a DSS
3. Prototype development Scoping of prototype Project evaluation criteria Detailed design System construction Testing Demonstration Evaluation
4. Operational deployment and support Functional orientation Operational training Deployment Maintenance
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DSS Applications DSS Applications
Corporate financial planning Marketing analysis Real estate investments Mineralogical exploration Transportation routing Portfolio analysis……
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Problems Facing DSSs
Problems Facing DSSs Data capture and collection
How to capture and collect data Non-compatibility of purchased DSSs with existing databases and computer netwo
rks Data integrity and security Unstructured problems
How to solve unstructured problems which are commonly faced by top executives Management of DSSs Cost-effectiveness
“Is a DSS cost effective?” Standardization Individual versus group DSSs
How to support individual decision makers during a group meeting Data are not independent of spreadsheets
Industrial standard for all spreadsheets
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Future Trends of DSS Future Trends of DSS
Group DSS Decision support centre
“A decision support centre is usually located in close proximity to top management so that instant decision support can be provided.”
Strategic DSS Intelligent DSS
The adaptation of artificial intelligence (AI) and expert systems techniques to DSS
Decision Support Systems and Expert Systems: A Comparison
F. Nelson Ford, Information & Management vol. 8, pp21-26, 1985
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Decision Support Systems Definition of DSS
A DSS helps decision-makers utilize data and models to solve unstructured and or semi-structured problems
Rapidly increasing: the late 1970s and early 1980s Requiring symbiosis between users and the system
Interplay between user and computer that produces a total effort greater than that attained by the user and the computer operating independently
providing synergistic decision making
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Characteristics of DSS Focusing on the less well structured, under specified
problems that typically face upper-level managers Lower levels of management: normally dealing with well
structured problems for which known solutions exist Integrating the use of management science methods
with traditional data processing functions Focusing on features that make them easy and
convenient to use interactively by non-computer people Reducing the intimidation often felt by managers unaccustomed to
computer use Emphasizing flexibility and adaptability to
accommodate changes in decision-making
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Structure of DSS The Dialog-Data-Models DSS Frameworks
Dialog subsystem All the capabilities of the DSS must be articulated and implemented through dialog
subsystem Data subsystem
Performing all data-related tasks(maintains, stores and retrieves data from the database, extracts data from various sources, …)
Models subsystem Containing the library of models and routines to maintain and manage them
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User
DataSubsystem
ModelsSubsystem
DialogSubsystem
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Expert Systems Definition of ES
A problem-solving program that achieves good performance in a specialized problem domain that generally requires specialized knowledge and skill
Characteristics of ES Human expert: performing the task well and its available to help develop the
knowledge base(special knowledge, judgment, experience) Employing heuristic problem solving
Rule of thumb or intuition instead of optimization and formal reasoning Containing and using three different general kinds of information
Task-specific: relevant only to current ES analysis Domain-specific: the knowledge base, including problem solving rules and data rel
evant to the field Control: the inference engine, which applies the axiomatic knowledge in the knowl
edge base to the task specific data to arrive at possible solutions
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Structure of ES Essential Components ES Structure
An Expanded ES Sturucture
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Knowledge Base
Inference Engine Task-specific Database
User
Knowledge Base
Explanation System
Task-specific Database
User
Inference Engine
Knowledge base
development system
User interface system
User interface system: executing all dialog and communication between the user and the ESExplanation system: providing the underlying logic or reasoning processKnowledge base development system: facilitating the creation and maintenance of the knowledge base
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Comparison of DSS and ES (1/2) Objectives and Intents
The functional goal of DSS and ES: basically the same! To improve the quality of the decision The objective of a DSS
To support the user in making a decision by providing quick and easy access to data and models relevant and applicable to that decision
The objective of an ES To provide to the user a conclusion or decision that is correct all the
same To provide conclusions or decisions to the non-expert user that are more
likely to be correct than user could provide
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Comparison of DSS and ES (2/2) Operational differences
DSS Allowing the user to confront a problem in a flexible, personal way User chooses relevant data and models and directs their use to explore
and analyze the problem and possible solutions ES
The user has little or no flexibility Executing appropriate segments of the knowledge base, as directed by
the inference engine While the user of a DSS directs and controls its various components, the
user of an ES is directed by the system Comparison of users
DSS Primarily applied in a business or organizational arena Middle and upper-level business management
ES Researchers in a narrow field of study ES are mainly built to “clone” the knowledge and experience of experts
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