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ACS-1803 Introduction to Information Systems

ACS-1803 Introduction to Information Systems. Information Systems Frameworks – Part 5 Lecture Outline 11. Instructor: Kerry Augustine. Learning Objectives.

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ACS-1803 Introduction to Information Systems

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  1. ACS-1803Introduction to Information Systems Information Systems Frameworks – Part 5 Lecture Outline 11 Instructor: Kerry Augustine ACS-1803 Introduction to Information Systems

  2. Learning Objectives • Describe the characteristics of six information systems that span the organizational, managerial, and executive levels: Functional Information Systems (Re-cap), Decision Support Systems (DSS), Expert Systems (ES), Office Automation Systems (OAS), Collaboration Technologies, and Global (Geographic) Information Systems

  3. Decision Support Systems p. 288 - 295

  4. Systems That Span Organizational Boundaries

  5. Decision Support Systems *L - designed to help management make semi- structured (or unstructured) decisions - they focus more on what might happen rather than what has happened

  6. Decision Support Systems Decision Support Systems Special-purpose information systems designed to support managerial-level employees in organizational decision making System Details These systems use computational software to construct models for analysis (most common is MS Excel) to solve semi-structured problems (e.g. sales or resource forecasts) Supported Activities: “What-if”analysis – changing one or more variables in the model to observe the effect (e.g. What is the payment if the interest rate increases by 1% ?)

  7. Characteristics of Decision Support Systems

  8. Common Decision Support Systems

  9. System Architecture: Decision Support Systems

  10. Decision Support Systems *L - typically include: a) a data base, perhaps a "data warehouse", extracted from a "live“ database, b) a model base*** that uses the data base [a model is a structured representation of some aspect of reality; it is because of the model that we can examine effects of decisions; but, a model always has assumptions e.g., inflation rate, net earnings level over 5 years; cost increases] c) a user-friendly interface (dialog), often involving graphics

  11. Decision Support Systems *L • a DSS may be developed by people outside of the Information Systems Department • - a DSS also can have capability for ad hoc reporting from the data base (warehouse) • examples of decision support: *L • - should we buy out a company? should we expand into another product line? [why semi-structured?I] • - classic illustration: Houston Oil and Mineral Co

  12. Decision Support Systems *L Fundamentals of Information Systems, Sixth Edition

  13. Components of a Decision Support System • At the core of a DSS are a database and a model base • Dialogue manager: • Allows decision makers to easily access and manipulate the DSS and to use common business terms and phrases Fundamentals of Information Systems, Sixth Edition

  14. The User Interface or Dialogue Manager • Allows users to interact with the DSS to obtain information • Assists with all aspects of communications between user and hardware and software that constitute the DSS Fundamentals of Information Systems, Sixth Edition

  15. The Database • Database management system: • Allows managers and decision makers to perform qualitative analysison data stored in company’s databases, data warehouses, and data marts • Can also be used to connect to external databases • Data-driven DSS: • Performs qualitative analysis based on the company’s databases Fundamentals of Information Systems, Sixth Edition

  16. The Model Base • Model base: • Allows managers and decision makers to perform quantitative analysis on both internal and external data • Model-driven DSS: • Performs mathematical or quantitative analysis • Model management software (MMS): • Coordinates the use of models in a DSS Fundamentals of Information Systems, Sixth Edition

  17. The Model Base (Examples) Fundamentals of Information Systems, Sixth Edition

  18. Three Fundamental DSS Components

  19. Model Driven DSS vs.Data Driven DSS A Model Driven DSS uses various models such as statistical model, simulation model or financial modelfor decision makings. So, decisions are based on models. A Data Driven DSS emphasizes access to and manipulation of a time-series of internal company data and sometimes external data to aid decision makings. So, decisions are based on analyzed data.

  20. DSS Examples *L • A more primitive example of a DSS is a spreadsheet used for “what-if” analysis • There are Excel templates built for certain types of decisions [terms: template, model; explain these] • Can be data driven or model driven • A Model Driven DSS is one in which decision makers use statistical simulations or financial models to come up with a solution or strategy. • A Data Driven DSS model puts its emphasis on collected data that is then manipulated to fit the decision maker’s needs. This data can be internal or external and in a variety of formats. It is important that data is collected and categorized sequentially, for example daily sales, operating budgets from one quarter to the next, inventory over the previous year, etc.

  21. Model-Driven Ex. – Loan Calculator Loan Calculator Model Variables to be Analyzed Analysis Results

  22. A Comparison of DSS and MIS • DSS differs from an MIS in numerous ways, including: • The type of problems solved • The support given to users • The decision emphasis and approach • The type, speed, output, and development of the system used • See comparison of DSS with MIS p. 292

  23. A Comparison of DSS and MIS

  24. Web-based DSS Examples for Customers • Evaluate alternative investment in mortgage portfolios • Fidelity.com (on-line investor center) • Evaluate and compare air fares • Travelocity.ca • Expedia.ca • Evaluate and compare various automobile prices • Edmunds.com

  25. More DSS Examples *MC • Canadian gov’t: PRAIRIE CROP PROTECTION PLANNER • Farmer describes: spraying equipment, size of field, current chemical prices • Model calculates: application rates, costs per acre, amount of chemical needed • US: helps farmers decide in which regions of Nebraska to plant grapevines to avoid freezing

  26. More DSS Examples *MC • Airline industry: DSS helps to find proper pricing to maximize overall revenue from selling seats for each flight • Mgr enters depart. pt, arr. pt, no of stops, times of dep and arr, # days in advance for res, # persons, size of plane, utilized capacity on similar previous flights etc. • System suggests variable ticket prices

  27. The U.S. Airline Industry • Yield management systems are designed to maximize the amount of revenue that an airline generates on each flight. • Yield management systems are the reason that an airfare you’re quoted over the phone can be $100 higher when you call back an hour later.

  28. The U.S. Airline Industry

  29. Medical Clinic Simulation Model • HC-Simulation Software to Optimize Healthcare Processes - (www.Flexsim.com) • FlexsimHeathcare Urgent Care Tutorial • Video 1 • Video 2 • Video 3

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