Week 9

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1. Chapter 4.1.2 ( week 9) Problem solving Through information system (Decision Support Systems) McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc.…
  • 1. Chapter 4.1.2 ( week 9) Problem solving Through information system (Decision Support Systems) McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
  • 2. Learning Objectives <ul><li>Identify the changes taking place in the form and use of decision support in business </li></ul><ul><li>Identify the role and reporting alternatives of management information systems </li></ul><ul><li>Describe how online analytical processing can meet key information needs of managers </li></ul><ul><li>Explain the decision support system concept and how it differs from traditional management information systems </li></ul>10-
  • 3. Learning Objectives <ul><li>Explain how the following information systems can support the information needs of executives, managers, and business professionals </li></ul><ul><ul><li>Executive information systems </li></ul></ul><ul><ul><li>Enterprise information portals </li></ul></ul><ul><ul><li>Knowledge management systems </li></ul></ul><ul><li>Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business </li></ul>10-
  • 4. Learning Objectives <ul><li>Give examples of several ways expert systems can be used in business decision-making situations </li></ul>10-
  • 5. Decision Support in Business <ul><li>Companies are investing in data-driven decision support application frameworks to help them respond to </li></ul><ul><ul><li>Changing market conditions </li></ul></ul><ul><ul><li>Customer needs </li></ul></ul><ul><li>This is accomplished by several types of </li></ul><ul><ul><li>Management information </li></ul></ul><ul><ul><li>Decision support </li></ul></ul><ul><ul><li>Other information systems </li></ul></ul>10-
  • 6. Case 1: Hillman Group, Avnet, and Quaker Chemical <ul><li>BI refers to a variety of software applications used to analyze an organization’s raw data (e.g., sales transactions) and extract useful insights from them. </li></ul><ul><li>BI projects can transform business processes. BI tools, coupled with changes to business processes, can have a significant impact on the bottom line. </li></ul><ul><li>Major impediment to using BI that transforms business processes is that most companies don’t understand their business processes well enough to determine how to improve them. </li></ul><ul><li>Companies that use BI to uncover flawed business processes are in a much better position to successfully compete than those companies that use BI merely to monitor what’s happening. </li></ul>10-
  • 7. Case Questions <ul><li>What are the business benefits of BI deployments such as those implemented by Avnet and Quaker Chemical? What roles do data and business processes play in achieving those benefits? </li></ul><ul><li>What are the main challenges to the change of mindset required to extend BI tools beyond mere reporting? What can companies do to overcome them? Use examples from the case to illustrate your answer. </li></ul><ul><li>Both Avnet and Quaker Chemical implemented systems and processes that affect the practices of their salespeople. In which ways did the latter benefit from these new implementations? How important was their buy-in to the success of these projects? Discuss alternative strategies for companies to foster adoption of new systems like these. </li></ul>10-
  • 8. Levels of Managerial Decision Making 10-
  • 9. Information Quality <ul><li>Information products made more valuable by their attributes, characteristics, or qualities </li></ul><ul><ul><li>Information that is outdated, inaccurate, or hard to understand has much less value </li></ul></ul><ul><li>Information has three dimensions </li></ul><ul><ul><li>Time </li></ul></ul><ul><ul><li>Content </li></ul></ul><ul><ul><li>Form </li></ul></ul>10-
  • 10. Attributes of Information Quality 10-
  • 11. Decision Structure <ul><li>Structured (operational) </li></ul><ul><ul><li>The procedures to follow when decision is needed can be specified in advance </li></ul></ul><ul><li>Unstructured (strategic) </li></ul><ul><ul><li>It is not possible to specify in advance most of the decision procedures to follow </li></ul></ul><ul><li>Semi-structured (tactical) </li></ul><ul><ul><li>Decision procedures can be pre-specified, but not enough to lead to the correct decision </li></ul></ul>10-
  • 12. Decision Support Systems 10- Management Information Systems Decision Support Systems Decision support provided Provide information about the performance of the organization Provide information and techniques to analyze specific problems Information form and frequency Periodic, exception, demand, and push reports and responses Interactive inquiries and responses Information format Prespecified, fixed format Ad hoc, flexible, and adaptable format Information processing methodology Information produced by extraction and manipulation of business data Information produced by analytical modeling of business data
  • 13. Decision Support Trends <ul><li>The emerging class of applications focuses on </li></ul><ul><ul><li>Personalized decision support </li></ul></ul><ul><ul><li>Modeling </li></ul></ul><ul><ul><li>Information retrieval </li></ul></ul><ul><ul><li>Data warehousing </li></ul></ul><ul><ul><li>What-if scenarios </li></ul></ul><ul><ul><li>Reporting </li></ul></ul>10-
  • 14. Business Intelligence Applications 10-
  • 15. Decision Support Systems <ul><li>Decision support systems use the following to support the making of semi-structured business decisions </li></ul><ul><ul><li>Analytical models </li></ul></ul><ul><ul><li>Specialized databases </li></ul></ul><ul><ul><li>A decision-maker’s own insights and judgments </li></ul></ul><ul><ul><li>An interactive, computer-based modeling process </li></ul></ul><ul><li>DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers </li></ul>10-
  • 16. DSS Components 10-
  • 17. DSS Model Base <ul><li>Model Base </li></ul><ul><ul><li>A software component that consists of models used in computational and analytical routines that mathematically express relations among variables </li></ul></ul><ul><li>Spreadsheet Examples </li></ul><ul><ul><li>Linear programming </li></ul></ul><ul><ul><li>Multiple regression forecasting </li></ul></ul><ul><ul><li>Capital budgeting present value </li></ul></ul>10-
  • 18. Applications of Statistics and Modeling <ul><ul><li>Supply Chain : simulate and optimize supply chain flows, reduce inventory, reduce stock-outs </li></ul></ul><ul><ul><li>Pricing : identify the price that maximizes yield or profit </li></ul></ul><ul><ul><li>Product and Service Quality : detect quality problems early in order to minimize them </li></ul></ul><ul><ul><li>Research and Development : improve quality, efficacy, and safety of products and services </li></ul></ul>10-
  • 19. Management Information Systems <ul><li>The original type of information system that supported managerial decision making </li></ul><ul><ul><li>Produces information products that support many day-to-day decision-making needs </li></ul></ul><ul><ul><li>Produces reports, display, and responses </li></ul></ul><ul><ul><li>Satisfies needs of operational and tactical decision makers who face structured decisions </li></ul></ul>10-
  • 20. Management Reporting Alternatives <ul><li>Periodic Scheduled Reports </li></ul><ul><ul><li>Prespecified format on a regular basis </li></ul></ul><ul><li>Exception Reports </li></ul><ul><ul><li>Reports about exceptional conditions </li></ul></ul><ul><ul><li>May be produced regularly or when an exception occurs </li></ul></ul><ul><li>Demand Reports and Responses </li></ul><ul><ul><li>Information is available on demand </li></ul></ul><ul><li>Push Reporting </li></ul><ul><ul><li>Information is pushed to a networked computer </li></ul></ul>10-
  • 21. Online Analytical Processing <ul><li>OLAP </li></ul><ul><ul><li>Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives </li></ul></ul><ul><ul><li>Done interactively, in real time, with rapid response to queries </li></ul></ul>10-
  • 22. Online Analytical Operations <ul><li>Consolidation </li></ul><ul><ul><li>Aggregation of data </li></ul></ul><ul><ul><li>Example: data about sales offices rolled up to the district level </li></ul></ul><ul><li>Drill-Down </li></ul><ul><ul><li>Display underlying detail data </li></ul></ul><ul><ul><li>Example: sales figures by individual product </li></ul></ul><ul><li>Slicing and Dicing </li></ul><ul><ul><li>Viewing database from different viewpoints </li></ul></ul><ul><ul><li>Often performed along a time axis </li></ul></ul>10-
  • 23. Geographic Information Systems (GIS) <ul><li>DSS uses geographic databases to construct and display maps and other graphic displays </li></ul><ul><li>Supports decisions affecting the geographic distribution of people and other resources </li></ul><ul><li>Often used with Global Positioning Systems (GPS) devices </li></ul>10-
  • 24. Data Visualization Systems (DVS) <ul><li>Represents complex data using interactive, three-dimensional graphical forms (charts, graphs, maps) </li></ul><ul><li>Helps users interactively sort, subdivide, combine, and organize data while it is in its graphical form </li></ul>10-
  • 25. Using Decision Support Systems <ul><li>Using a decision support system involves an interactive analytical modeling process </li></ul><ul><ul><li>Decision makers are not demanding pre-specified information </li></ul></ul><ul><ul><li>They are exploring possible alternatives </li></ul></ul><ul><li>What-If Analysis </li></ul><ul><ul><li>Observing how changes to selected variables affect other variables </li></ul></ul>10-
  • 26. Using Decision Support Systems <ul><li>Sensitivity Analysis </li></ul><ul><ul><li>Observing how repeated changes to a single variable affect other variables </li></ul></ul><ul><li>Goal-seeking Analysis </li></ul><ul><ul><li>Making repeated changes to selected variables until a chosen variable reaches a target value </li></ul></ul><ul><li>Optimization Analysis </li></ul><ul><ul><li>Finding an optimum value for selected variables, given certain constraints </li></ul></ul>10-
  • 27. Data Mining <ul><li>Provides decision support through knowledge discovery </li></ul><ul><ul><li>Analyzes vast stores of historical business data </li></ul></ul><ul><ul><li>Looks for patterns, trends, and correlations </li></ul></ul><ul><ul><li>Goal is to improve business performance </li></ul></ul><ul><li>Types of analysis </li></ul><ul><ul><li>Regression </li></ul></ul><ul><ul><li>Decision tree </li></ul></ul><ul><ul><li>Neural network </li></ul></ul><ul><ul><li>Cluster detection </li></ul></ul><ul><ul><li>Market basket analysis </li></ul></ul>10-
  • 28. Analysis of Customer Demographics 10-
  • 29. Market Basket Analysis <ul><li>One of the most common uses for data mining </li></ul><ul><ul><li>Determines what products customers purchase together with other products </li></ul></ul><ul><li>Results affect how companies </li></ul><ul><ul><li>Market products </li></ul></ul><ul><ul><li>Place merchandise in the store </li></ul></ul><ul><ul><li>Lay out catalogs and order forms </li></ul></ul><ul><ul><li>Determine what new products to offer </li></ul></ul><ul><ul><li>Customize solicitation phone calls </li></ul></ul>10-
  • 30. Executive Information Systems (EIS) <ul><ul><li>Combines many features of MIS and DSS </li></ul></ul><ul><ul><li>Provide top executives with immediate and easy access to information </li></ul></ul><ul><ul><li>Identify factors that are critical to accomplishing strategic objectives (critical success factors) </li></ul></ul><ul><ul><li>So popular that it has been expanded to managers, analysis, and other knowledge workers </li></ul></ul>10-
  • 31. Features of an EIS <ul><li>Information presented in forms tailored to the preferences of the executives using the system </li></ul><ul><ul><li>Customizable graphical user interfaces </li></ul></ul><ul><ul><li>Exception reports </li></ul></ul><ul><ul><li>Trend analysis </li></ul></ul><ul><ul><li>Drill down capability </li></ul></ul>10-
  • 32. Enterprise Information Portals <ul><li>An EIP is a Web-based interface and integration of MIS, DSS, EIS, and other technologies </li></ul><ul><ul><li>Available to all intranet users and select extranet users </li></ul></ul><ul><ul><li>Provides access to a variety of internal and external business applications and services </li></ul></ul><ul><ul><li>Typically tailored or personalized to the user or groups of users </li></ul></ul><ul><ul><li>Often has a digital dashboard </li></ul></ul><ul><ul><li>Also called enterprise knowledge portals </li></ul></ul>10-
  • 33. Enterprise Information Portal Components 10-
  • 34. Enterprise Knowledge Portal 10-
  • 35. Case 2: Goodyear, JEA, OSUMC, and Monsanto <ul><li>Advanced technologies such as AI, mathematical simulations, and robotics can have dramatic impacts on both business processes and financial results. </li></ul><ul><li>At Goodyear, designers can perform tests 10 times faster using simulation, reducing a new tire’s time to market from two years to as little as nine months. </li></ul><ul><li>Public Utility Company JEA uses neural network technology to automatically determine the optimal combinations of oil and natural gas the utility’s boilers need to produce electricity cost effectively, given fuel prices and the amount of electricity required. </li></ul><ul><li>The Ohio State University Medical Center (OSUMC) replaced its overhead rail transport system with 46 self-guided robotic vehicles to move linens, meals, trash, and medical supplies throughout the 1,000-bed hospital. </li></ul>10-
  • 36. Case Study Questions <ul><li>Consider the outcomes of the projects discussed in the case. In all of them, the payoffs are both larger and achieved more rapidly than in more traditional system implementations. Why do you think this is the case? How are these projects different from others you have come across in the past? What are those differences? Provide several examples. </li></ul><ul><li>How do these technologies create business value for the implementing organizations? In which ways are these implementations similar in how they accomplish this, and how are they different? Use examples from the case to support your answer. </li></ul><ul><li>In all of these examples, companies had an urgent need that prompted them to investigate these radical, new technologies. Do you think the story would have been different had the companies been performing well already? Why or why not? To what extent are these innovations dependent on the presence of a problem or crisis? </li></ul>10-
  • 37. Artificial Intelligence (AI) <ul><li>AI is a field of science and technology based on </li></ul><ul><ul><li>Computer science </li></ul></ul><ul><ul><li>Biology </li></ul></ul><ul><ul><li>Psychology </li></ul></ul><ul><ul><li>Linguistics </li></ul></ul><ul><ul><li>Mathematics </li></ul></ul><ul><ul><li>Engineering </li></ul></ul><ul><li>The goal is to develop computers than can simulate the ability to thin
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