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Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-1 1-2 TPS : Payroll System MIS EIS Technologies that apply reasoning methodologies in a specific domain Attempts to mimic human experts’ problem solving Examples include: Artificial Intelligence Systems Artificial Neural Networks (neural computing) Genetic Algorithms Fuzzy Logic Intelligent Agents © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-7 Knowledge that is organized and stored in a repository for use by an organization Can be used to solve similar or identical problems in the future ROIs as high as a factor of 25 within one to two years © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-8 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang KARAKTERISTIK PERMASALAHAN 1-9 Structured (automated) “Structured” means that there is an algorithm, mathematical formula, or decision rule to accomplish the entire stage. The algorithm can be implemented manually or it can be computerized, but the steps are so detailed that no little or no human judgment would be needed. established situation, programmable decision, situation fully understood, routine, specialized mfg. process Unstructured emergent situation, creative decision, situation unclear, one-shot, general processes New technologies and better information distribution have resulted in more alternatives for management. Complex operations have increased the costs of errors, causing a chain reaction throughout the organization. Rapidly changing global economies and markets are producing greater uncertainty and requiring faster response in order to maintain competitive advantages. Increasing governmental regulation coupled with political destabilization have caused great uncertainty. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-11 Quick computations at a lower cost Group collaboration and communication Increased productivity Ready access to information stored in multiple databases and data warehouse Ability to analyze multiple alternatives and apply risk management Enterprise resource management Tools to obtain and maintain competitive advantage © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-12 The ratio of outputs to inputs that measures the degree of success of an organization and its individual parts © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-13 The human mind has limited processing and storage capabilities. Any single person is therefore limited in their decision making abilities. Collaboration with others allows for a wider range of possible answers, but will often be faced with communications problems. Computers improve the coordination of these activities. This knowledge sharing is enhanced through the use of GSS, KMS, and EIS. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-14 The support of management tasks by the application of technologies Sometimes called Decision Support Systems or Business Intelligence © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-15 DSS Management Science Business Analytics Data Mining Data Warehouse Business Intelligence OLAP CASE tools GSS EIS © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 1-16 EIP ERM ERP CRM SCM KMS KMP ES ANN Intelligent Agents E-commerce DSS Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-17 Process of choosing amongst alternative courses of action for the purpose of attaining a goal or goals. The four phases of the decision process are: Intelligence Design Choice implementation © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-18 Structure Inputs Processes Outputs Feedback from output to decision maker Separated from environment by boundary Surrounded by environment Input Processes boundary © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Environment 2-19 Output © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-20 Closed system Independent Takes no inputs Delivers no outputs to the environment Black Box Open system Accepts inputs Delivers outputs to environment © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-21 Iconic Small physical replication of system Analog Behavioral representation of system May not look like system Quantitative (mathematical) Demonstrates relationships between systems © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-22 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-23 Intelligence (in the military sense of gathering information) Design (Identifying the alternatives, structuring how the decision will be made) Choice (Picking an alternative or making the judgment) [Implementation – later added by other authors] [Evaluation] Simon’s original three phases: Intelligence Design Choice He added fourth phase later: Implementation Book adds fifth stage: Monitoring © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-25 Scan the environment Analyze organizational goals Collect data Identify problem Categorize problem Programmed and non-programmed Decomposed into smaller parts Assess ownership and responsibility for problem resolution [pemecahan masalah] © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-26 Develop alternative courses of action Analyze potential solutions Create model Test for feasibility Validate results Select a principle of choice Establish objectives Incorporate into models Risk assessment and acceptance Criteria and constraints © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-27 Decision making with commitment to act Determine courses of action Analytical techniques Algorithms Heuristics Blind searches Analyze for robustness © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-28 Putting solution to work Vague boundaries which include: Dealing with resistance to change User training Upper management support © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-29 Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-31 Systems designed to support managerial decision-making in unstructured problems More recently, emphasis has shifted to inputs from outputs Mechanism for interaction between user and components Usually built to support solution or evaluate opportunities © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-32 A DSS is a methodology that supports decision-making. It is: Flexible; Adaptive; Interactive; GUI-based; Iterative; and Employs © 2005Prentice Hall, Decision modeling. Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-33 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-34 KEMAMPUAN DSS KARAKTERISTIK DSS Subsystems: Data management ▪ Managed by DBMS Model management ▪ Managed by MBMS User interface Knowledge Management and organizational knowledge base © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-35 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-36