Decision supportsystems
- 2. Decision Support in Business 2 Companies are investing in data-driven decision support application frameworks to help them respond to Changing market conditions Customer needs This is accomplished by several types of Management information Decision support Other information systems
- 3. Levels of Managerial Decision Making 3
- 4. Information Quality 4 Information products made more valuable by their attributes, characteristics, or qualities Information that is outdated, inaccurate, or hard to understand has much less value Information has three dimensions Time Content Form
- 5. Attributes of Information Quality 5
- 6. Decision Structure 6 Structured (operational) The procedures to follow when decision is needed can be specified in advance Unstructured (strategic) It is not possible to specify in advance most of the decision procedures to follow Semi-structured (tactical) Decision procedures can be pre-specified, but not enough to lead to the correct decision
- 7. Decision Support Systems Management Information Systems Provide information about the performance of the organization Decision support provided Information form and frequency Information format Periodic, exception, demand, and push reports and responses Prespecified, fixed format Information processing methodology 7 Information produced by extraction and manipulation of business data Decision Support Systems Provide information and techniques to analyze specific problems Interactive inquiries and responses Ad hoc, flexible, and adaptable format Information produced by analytical modeling of business data
- 8. Decision Support Trends 8 The emerging class of applications focuses on Personalized decision support Modeling Information retrieval Data warehousing What-if scenarios Reporting
- 10. Decision Support Systems 10 Decision support systems use the following to support the making of semi-structured business decisions Analytical models Specialized databases A decision-maker’s own insights and judgments An interactive, computer-based modeling process DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers
- 11. Applications of Statistics and Modeling 11 Supply Chain: simulate and optimize supply chain flows, reduce inventory, reduce stock- outs Pricing: identify the price that maximizes yield or profit Product and Service Quality: detect quality problems early in order to minimize them Research and Development: improve quality, efficacy, and safety of products and services
- 12. Management Information Systems 12 The original type of information system that supported managerial decision making Produces information products that support many day-to-day decision-making needs Produces reports, display, and responses Satisfies needs of operational and tactical decision makers who face structured decisions
- 13. Online Analytical Processing 13 OLAP Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives Done interactively, in real time, with rapid response to queries
- 14. Using Decision Support Systems 14 Using a decision support system involves an interactive analytical modeling process Decision makers are not demanding pre-specified information They are exploring possible alternatives What-If Analysis Observing how changes to selected variables affect other variables Sensitivity Analysis Observing how repeated changes to a single variable affect other variables Goal-seeking Analysis Making repeated changes to selected variables until a chosen variable reaches a target value Optimization Analysis Finding an optimum value for selected variables, given certain constraints
- 15. Data Mining 15 Provides decision support through knowledge discovery Analyzes vast stores of historical business data Looks for patterns, trends, and correlations Goal is to improve business performance Types of analysis Regression Decision tree Neural network Cluster detection Market basket analysis
- 16. Market Basket Analysis 16 One of the most common uses for data mining Determines what products customers purchase together with other products Results affect how companies Market products Place merchandise in the store Lay out catalogs and order forms Determine what new products to offer Customize solicitation phone calls
- 17. Executive Information Systems 17 Combines many features of MIS and DSS Provide top executives with immediate and easy access to information Identify factors that are critical to accomplishing strategic objectives (critical success factors) So popular that it has been expanded to managers, analysis, and other knowledge workers
- 18. Enterprise Information Portals 18 An EIP is a Web-based interface and integration of MIS, DSS, EIS, and other technologies Available to all intranet users and select extranet users Provides access to a variety of internal and external business applications and services Typically tailored or personalized to the user or groups of users Often has a digital dashboard Also called enterprise knowledge portals
- 20. Expert Systems 20 An Expert System (ES) A knowledge-based information system Contain knowledge about a specific, complex application area Acts as an expert consultant to end users
- 21. Components of an Expert System 21 Knowledge Base Facts about a specific subject area Heuristics that express the reasoning procedures of an expert (rules of thumb) Software Resources An inference engine processes the knowledge and recommends a course of action User interface programs communicate with the end user Explanation programs explain the reasoning process to the end user
- 22. Components of an Expert System 22
- 23. Expert System Application Categories 23 Decision Management Loan portfolio analysis Employee performance evaluation Insurance underwriting Diagnostic/Troubleshooting Equipment calibration Help desk operations Medical diagnosis Software debugging
- 24. Expert System Application Categories 24 Process Monitoring/Control Machine control (including robotics) Inventory control Production monitoring Chemical testing
- 25. Benefits of Expert Systems 25 Captures the expertise of an expert or group of experts in a computer-based information system Faster and more consistent than an expert Can contain knowledge of multiple experts Does not get tired or distracted Cannot be overworked or stressed Helps preserve and reproduce the knowledge of human experts
- 26. Limitations of Expert Systems 26 The major limitations of expert systems Limited focus Inability to learn Maintenance problems Development cost Can only solve specific types of problems in a limited domain of knowledge
- 27. Developing Expert Systems 27 Suitability Criteria for Expert Systems Domain: the domain or subject area of the problem is small and well-defined Expertise: a body of knowledge, techniques, and intuition is needed that only a few people possess Complexity: solving the problem is a complex task that requires logical inference processing Structure: the solution process must be able to cope with ill-structured, uncertain, missing, and conflicting data and a changing problem situation Availability: an expert exists who is articulate, cooperative, and supported by the management and end users involved in the development process
- 28. Development Tool 28 Expert System Shell The easiest way to develop an expert system A software package consisting of an expert system without its knowledge base Has an inference engine and user interface programs
- 29. Knowledge Engineering 29 A knowledge engineer Works with experts to capture the knowledge (facts and rules of thumb) they possess Builds the knowledge base, and if necessary, the rest of the expert system Performs a role similar to that of systems analysts in conventional information systems development
- 30. Information Management Agents 30 Search Agents – help users find files and databases, search for information, and suggest and find new types of information products, media, resources Information Brokers – provide commercial services to discover and develop information resources that fit business or personal needs Information Filters – Receive, find, filter, discard, save, forward, and notify users about products received or desired, including e-mail, voice mail, and other information media