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IS312 Information Systems for Business

Learn how businesses make profit using the value chain model, how information systems add value and support decision making, and how they enhance decision making and span organizational boundaries.

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IS312 Information Systems for Business

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  1. IS312 Information Systems for Business Lecture 2 Information Systems for Value Driven Business [ Ch. 2 ]

  2. LEARNING OBJECTIVES How business make profit (Value Chain) How IS create added value How business make decision (Organizational Pyramid) How IS help in decision making process

  3. How Business Survive/Make Profit:Value Chain Model VALUE FIRM INFRASTRUCTURE HUMAN RESOURCE MANAGEMENT TECHNOLOGY DEVELOPMENT PROCUREMENT INBOUND LOGISTICS OPERATIONS OUTBOUND LOGISTIC MARKETING & SALES LOGISTIC SERVICE MARGIN COST

  4. How Business Survive/Make Profit:Value Chain Model . . .

  5. Value-Added Activities • Customer-Value-Added Activity (maximize) • a business process that a customer is willing to pay for • Business-Value-Added Activity (minimize) • a business process that is essential to managing an organization • Non-Value-Added Activity (eliminate) • customer will not pay for; business value will not be increased • Goals of a business system: effective(do right thing), efficient(do thing right), competitive (do thing differently).

  6. How Information Systems Add Values ? • Automating: doing things faster/cheaper • Organizational Learning: doing things better way (from lessons learned) • Supporting Strategy: doing things smarter than competitors to meet customer’s needs.

  7. What IT/IS can do • IT/IS improves or innovates the use of knowledge in operations of the value chain and value system • IT/IS improves products or services by increasing quality, reducing costs, or adding desirable features • IT/IS provides timely and reliable information to enhance the decision-making process • IT/IS improves communication between internal as well as external business entities to increase efficiency in production and distribution

  8. Value Chain & Five Forces Model Revisited

  9. What’s in a Name . . . • Computer Engineering – Hardware (~ Chemistry) • Computer Science – Software (~ Pharmacy) • Information Systems (~ Medicine) • IS Specialist (~ Physician) • YOU, YOUR BUSINESS (~Patient) • Systems (~over counter vs. prescribed drugs) • Business failures (~ DEATH !!!)

  10. IT vs. IS Combinations of hardware, software, and telecom networks that people build and use to collect, create, and distribute useful datain organizations (for decision making) Combinations of hardware, software, and telecom networks use to process data

  11. Information Systems Combination of : Hardware Software Data Telecommunications networks People Procedures (business rules)

  12. Decision-Making Levels of an Organization

  13. Decision-Making Levels of an Organization • Executive level • Long-term decisions (Strategies) • Unstructured decisions • Managerial level • Decisions covering weeks and months (Tactics) • Semi-structured decisions • Operational level • Day-to-day decisions (Operations) • Structured decisions

  14. Operational Level

  15. IS Architecture

  16. Managerial Level

  17. IS Architecture

  18. MANAGERIAL SUPPORT SYSTEMS Interaction Between a TPS and DSS

  19. MANAGERIAL SUPPORT SYSTEMS • Four quantitative models used by DSSs include • What-if analysis: assess impact of a change in a variable/assumption on the model • Sensitivity analysis: assess impact on other variables when one variable is changed repeatedly • Goal-seeking analysis: find necessary inputs for a desired level of output • Optimization analysis: find optimum value for output when other inputs are changed repeatedly

  20. Executive Level

  21. IS Architecture

  22. STRATEGIC SUPPORT SYSTEMS • Executive information system (EIS) – A specialized DSS that supports senior level executives within the organization • Granularity: level of details in the model/process • Visualization: graphical display of patterns/relationships of large amount of data • Digital dashboard: visual summary for tracking critical success factors and key performance indicators

  23. STRATEGIC SUPPORT SYSTEMS Interaction Between a TPS and EIS

  24. STRATEGIC SUPPORT SYSTEMS • Most EISs offering the following capabilities • Consolidation: aggregation of data • Drill-down: ability to view details of data at different levels of aggregation • Slice-and-dice: ability to look at information at different perspectives.

  25. Enhancing Decision Making With Information Systems

  26. Information Systems that Span Organizational Boundaries

  27. Information Systems Supporting the Functional Areas

  28. Functional Area Information Systems

  29. Information Systems inside Organizations

  30. Functional Area Information Systems

  31. Information Technology outside Organization

  32. Capabilities of Information Systems Perform high-speed, high-volume numerical computations Provide fast, accurate communication and collaboration within and among organizations Store huge amounts of information in small space Allow quick, inexpensive access to vast amounts of information worldwide Interpret vast amounts of data quickly and efficiently Increase effectiveness and efficiency of people working in groups in one place or around the world Automate semiautomatic business process and manual tasks

  33. Why Information Systems Important to Organizations & Society ? IT will reduce the number of middle managers. IT will change the manager’s job. IT impacts employees at work. IT provides quality-of-life improvements.

  34. MAKING BUSINESS DECISIONS • Managerial decision-making challenges • Analyze large amounts of information • Apply sophisticated analysis techniques • Make decisions quickly

  35. DECISION-MAKING PROCESS • The six-step decision-making process • Problem identification • Data collection • Solution generation • Solution test • Solution selection • Solution implementation

  36. METRICS: MEASURING SUCCESS • Critical success factors (CSFs) – The crucial steps companies make to perform to achieve their goals and objectives and implement strategies • Create high-quality products • Retain competitive advantages • Reduce product costs • Increase customer satisfaction • Hire and retain the best professionals

  37. METRICS: MEASURING SUCCESS . . . • Key performance indicators (KPIs) – The quantifiable metrics a company uses to evaluate progress toward critical success factors • Turnover rates of employees • Number of product returns • Number of new customers • Average customer spending • External (e.g., market share) vs. Internal KPI (e.g., ROI)

  38. Efficiency and Effectiveness Metrics • Efficiency MIS metrics – Measure the performance of MIS itself, such as throughput, transaction speed, and system availability • Effectiveness MIS metrics –Measures the impact MIS has on business processes and activities, including customer satisfaction and customer conversation rates

  39. The Interrelationship Between Efficiency And Effectiveness Metrics • Ideal operation occurs in the upper right corner

  40. The Interrelationship Between Efficiency And Effectiveness Metrics • Benchmark – Baseline values the system seeks to attain • Benchmarking – A process of continuously measuring system results, comparing those results to optimal system performance (benchmark values), and identifying steps and procedures to improve system performance

  41. SUPPORT: ENHANCING DECISION MAKING WITH IS • Model – A simplified representation or abstraction of reality that helps managers to • Calculate risks • Understand uncertainty • Change variables • Manipulate time to make decisions

  42. THE FUTURE: ARTIFICIAL INTELLIGENCE (AI) • Artificial intelligence (AI) – Simulates human intelligence such as the ability to reason and learn • Intelligent system – Various commercial applications of artificial intelligence

  43. ARTIFICIAL INTELLIGENCE (AI) 1. Expert system – Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems 2. Neural Network – Attempts to emulate the way the human brain works • Fuzzy logic – A mathematical method of handling imprecise or subjective information

  44. ARTIFICIAL INTELLIGENCE (AI) 3. Genetic algorithm – An artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem - Shopping bot – Software that will search several retailer websites and provide a comparison of each retailer’s offerings including price and availability

  45. ARTIFICIAL INTELLIGENCE (AI) 4. Intelligent agent – Special-purpose knowledge-based information system that accomplishes specific tasks on behalf of its users 5. Virtual reality - A computer-simulated environment that can be a simulation of the real world or an imaginary world

  46. EVALUATING BUSINESS PROCESS • Businesses gain a competitive edge when they minimize costs and streamline business processes • Customer facing (front-office) process • Business facing (back-office) process

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