![STAGESOF DECISION MAKING
(FROM HERBERT SIMON)
• 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]](https://image.slidesharecdn.com/dss-180427141709/85/Decision-Support-System-DSS-6-320.jpg)
Decision Support System ( DSS )
- 1. Siddhesh Palkar & Sumit Lambe DECISION SUPPORT SYSTEMS
- 2. INTRODUCTION • Decision makers are faced with increasingly stressful environments – highly competitive, fast-paced, near real-time, overloaded with information, data distributed throughout the enterprise, and multinational in scope. • The combination of the Internet enabling speed and access, and the maturation of artificial intelligence techniques, has led to sophisticated aids to support decision making under these risky and uncertain conditions. • These aids have the potential to improve decision making by suggesting solutions that are better than those made by the human alone. • They are increasingly available in diverse fields from medical diagnosis to traffic control to engineering applications.
- 3. DECISION SUPPORT SYSTEM • A Decision Support System (DSS) is an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions. • Decision Support System is a general term for any computer application that enhances a person or group’s ability to make decisions. • Also, Decision Support Systems refers to an academic field of research that involves designing and studying Decision Support Systems in their context of use.
- 4. THEDECISION SUPPORT PARADIGM Inquiring Organization Decision Making Process for DSS Knowledge Management New Decision Making Paradigm for DSS Singerian Organizational Model Unbounded Systems Thinking (UST)
- 5. HISTORY OF DSS • The concept of decision support has evolved mainly from the theoretical studies of organizational decision making done at the Carnegie Institute of Technology during the late 1950s and early 1960s, and the implementation work done in the 1960s. • DSS became an area of research of its own in the middle of the 1970s, before gaining in intensity during the 1980s. In the middle and late 1980s, executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS) evolved from the single user and model-oriented DSS.
- 6. STAGESOF DECISION MAKING (FROM HERBERT SIMON) • 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]
- 7. STRUCTUREDVS UNSTRUCTURED DECISION STAGES • Each stage can be Structured (automated) or Unstructured • “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. • Any decision stage that is not structured is unstructured
- 8. DSS CONCEPT • Anthony (1965) • Categories of Management Activities • Strategic Planning, Management Control, Operational Control • Simon (1960) • Description of Decision Type • Decision problems as existing on a continuum from programmed to non- programmed • Gorry & Morton (1971)
- 9. STRUCTURED,SEMI-STRUCTURED, AND UNSTRUCTURED DECISIONS • In a structured decision all three stages are structured • In a non-structured decision all three stages are unstructured • A semi-structured decision is one in which part, but not all, of the decision is structured.
- 10. KEY POINT: • The realm of Decision Support Systems is Semi-Structured and unstructured Decisions…the type of decisions that can benefit from “decision support” but the human decision maker is still involved.
- 11. SOME ORGANIZING FRAMEWORKS AND EXAMPLES OFDSS
- 12. ARCHITECTURE • Three fundamental components of DSS: • the database management system (DBMS), • the model management system (MBMS), and • the dialog generation and management system (DGMS). • the Data Management Component stores information (which can be further subdivided into that derived from an organization's traditional data repositories, from external sources such as the Internet, or from the personal insights and experiences of individual users); • the Model Management Component handles representations of events, facts, or situations (using various kinds of models, two examples being optimization models and goal-seeking models); and • the User Interface Management Component is of course the component that allows a user to interact with the system.
- 13. A DETAILED ARCHITECTURE • Even though different authors identify different components in a DSS, academics and practitioners have come up with a generalized architecture made of six distinct parts: • the data management system, • the model management system, • the knowledge engine, • The user interface, • the DSS architecture and network, and • the user(s)
- 14. TYPICAL ARCHITECTURE • TPS: transaction processing system • MODEL: representation of a problem • OLAP: on-line analytical processing • USER INTERFACE: how user enters problem & receives answers • DSS DATABASE: current data from applications or groups • DATAMINING: technology for finding relationships in large data bases for prediction TPS EXTERNAL DATA DSS DATA BASE DSS SOFTWARE SYSTEM MODELS OLAP TOOLS DATAMININGTOOLS USER INTERFACE USER
- 15. THANK YOU