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Using Information Systems for Decision Making

Using Information Systems for Decision Making. (Week 13, Thursday 4/5/2007). BUS3500 - Abdou Illia, Spring 2007. LEARNING GOALS. Explain the decision-making process. Describe decision support systems. Explain how Group Decision Support Systems work. Describe executive information systems.

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Using Information Systems for Decision Making

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  1. Using InformationSystems forDecision Making (Week 13, Thursday 4/5/2007) BUS3500 - Abdou Illia, Spring 2007

  2. LEARNING GOALS • Explain the decision-making process. • Describe decision support systems. • Explain how Group Decision Support Systems work. • Describe executive information systems. • Describe Expert Systems and Knowledge Work systems.

  3. Recall from previous classes Types of Information Systems:- Transaction Processing Systems- Office Automation Systems- Knowledge Work Systems- Management Information Systems- Decision Support Systems- Executive Information Systems Top ManagementMiddle ManagementLower ManagementOperational workers Officeworkers Officeworkers Questions Officeworkers Officeworkers Knowledgeworkers Q: What kind of IS are designed to provide help for decision makers?Q: What criteria we should look at to distinguish between (1) IS for decisionmaking and (2) other IS?

  4. Systems for Decision Making Task structure level Degree of repetitiveness Type of Information System used EIS, KWS Unstructured Non-repetitive DSS Semi-structured TPS Structured Repetitive

  5. Systems for Decision Making • Decision support systems (DSS) are one tool • A computer-based system that supports and improves human decision making • Helps middle managers analyze complex problems • Group decision support systems (GDSS) • Tool for supporting team decision making • Executive information system (EIS) • Computer-based system that supports the decision-making processes of senior managers • Knowledge Work Systems (KWS) • Computer-based system that supports the decision-making processes of Knowledge workers

  6. The Decision-Making Process • Simon’s model of the decision-making process • Intelligence • Design • Choice

  7. Intelligence Phase Data source • Scan the environment for a problem. • Determine if decision-maker can solve the problem. • Within their scope of influence? • Fully define the problem by gathering more information about the problem. Scan Environment forproblem to be solvedor decision to be made MIS Problem ? No END Yes Problem within scope of influence? No END Yes Gather more informationabout the problem Internal & External data

  8. Design Phase • Develop a model of the problem. • Determine type of model. • Verify model. • Develop and analyze potential solutions. Develop a model ofproblem to be solved Verify that the model is accurate Develop potentialsolutions

  9. Choice Phase • Select the solution to implement. • More detailed analysis of selected solutions might be needed. • Verify initial conditions. • Analyze proposed solution against real-world constraints.

  10. Decision Support Systems • Designed to help individual managers make decisions • Major components • Data management subsystem • Internal and external data sources • Model management subsystem • Typically mathematical in nature • User interface • How the people interact with the DSS • Data visualization is the key • Text • Graphs • Charts UserInterface Model Management - Sensitivity Analysis -> What-if Analysis -> Goal-seeking Analysis Data Management - Transactional Data- Data warehouse- Business partners data- Economic data

  11. Modeling Tools and Techniques • Simulation is used to examine proposed solutions and their impact • Sensitivity analysis • Determine how changes in one part of the model influence other parts of the model • What-if analysis • Manipulate variables to see what would happen in given scenarios • Goal-seeking analysis • Work backward from desired outcome Determine monthly payment given various interest rates. Works backward from a given monthly payment to determine various loans that would give that payment.

  12. Groups Decision Support Systems • Designed to support groups make decisions with the help of a Group Facilitator • GDSS Tools: • Brainstorming tools: Allow users enter ideas simultaneously & anonymously • Commenter tools:Allow users to anonymously comment on others’ ideas • Categorizing tools: Groups ideas into categories • Idea-ranking tools: Ranks ideas. Identify the best ones. • Electronic-voting tools: Allow users to vote for their favorite ideas. Front Screen GDSS tools

  13. Executive Information Systems • Computer-based tool that specifically helps top-level management make strategic decisions • Processes both internal and external data • Presents data in summary form • Drill-down is a key feature – gives the manager the ability to see more details when needed

  14. KWS: Expert Systems • Artificial Intelligence systems that codify human expertise in a computer system • Main goal is to transfer knowledge from one person to another • Wide range of subject areas • Medical diagnosis • Computer purchasing • Knowledge engineer elicits the expertise from the expert and encodes it in the expert system

  15. Example of rules IFfamily is albatross ANDcolor is white THENbird is laysan albatross. IFfamily is albatross ANDcolor is dark THENbird is black footed albatross Expert Systems Components • Knowledge base: database of the expertise, often in IF THEN rules. • Inference engine: derives recommendations from knowledge base and problem-specific data • User interface: controls the dialog between the user and the system • Explanation system: Explain the how and why of recommendations User Domain Expert UserInterface Expertise System Engineer InferenceEngine Knowledge Engineer Encoded expertise Knowledgebase ExplanationSystem

  16. Other KWS • Neural networks – use software to simulate the neural working of the human brain • Intelligent agents (bots) – autonomously handle tasks for humans and act on user’s behalf • Genetic algorithms – Computer instructions that create a population of thousands on potential solutions and evolves the population toward better solutions • Fuzzy logic – a way to get computers to come closer to the ability to see fine distinctions, not just ones and zeros

  17. Summary Questions

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