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Internal Information Systems MIS 2101: Management Information Systems Based on material from Information Systems Today: Managing in the Digital World, Leonard Jessup and Joseph Valacich, Pearson Prentice Hall, 2007 Also includes material by David Schuff, Paul Weinberg, and Cindy Joy Marselis. Learning Objectives 2 Learning Objectives 3 Decision-Making Levels of an Organization 4 Operational Level Day-to-day business processes Interactions with customers Information systems used to: Decisions: 5 Automate repetitive tasks Improve efficiency Structured Recurring Can often be automated using IS Examples? Managerial Level Functional managers Monitoring and controlling operational-level activities Providing information to executive level Midlevel managers • Focus on effectively utilizing and deploying resources • Goal of achieving strategic objectives Managers’ decisions Semi-structured Contained within business function Moderately complex Time horizon of few days to few months Examples? 6 Executive Level The president, CEO, vice presidents, board of directors Decisions Long-term strategic issues Complex and nonroutine problems Unstructured decisions Long-term ramifications 7 Examples? 7-7 Comparison of Decision-Making Levels Operational Level Managerial Level Executive Level Who Foreman or supervisor Midlevel managers and functional managers Executive-level managers What Automate routine and repetitive activities Automate the monitoring and controlling of operational activities Aggregate summaries of past organizational data and projections of the future Why Improve organizational efficiency Improve organizational effectiveness Improve organizational strategy and planning IS Transaction Processing Systems (TPS) Management Information Systems (MIS) Executive Information Systems (EIS) 8 Learning Objectives 9 General Types of Information Systems Input-process-output model Basic systems model Payroll system example 10 Transaction Processing System Operational level Purpose: Processing of business events and transactions Increase efficiency • Automation • Lower costs • Increased speed and accuracy Examples Payroll processing Sales and order processing Inventory management Etc. 11 Architecture of a TPS 12 Architecture of a TPS: Inputs Source Documents 13 Different data entry methods Architecture of a TPS: Processing Online processing Batch processing 14 Immediate results Transactions collected and later processed together Used when immediate notification not necessary Architecture of a TPS: Outputs Counts, summary reports Inputs to other systems Feedback to systems operator 15 Summary of TPS Characteristics 16 Management Information Systems Managerial level Purpose: Produce reports Support of midlevel managers’ decisions Examples Sales forecasting Financial management and forecasting Manufacturing, planning and scheduling Inventory management and planning Etc. 17 Architecture of an MIS 18 Architecture of an MIS: Processing Aggregation Summary 19 Architecture of an MIS: Outputs 20 Summary of MIS Characteristics 21 Executive Information Systems A.k.a. Executive support system Executive level Purpose Examples 22 Aid in executive decision-making Provide information in highly aggregated form Monitoring of internal and external events and resources Crisis management Etc. Architecture of an EIS 23 Architecture of an EIS: Inputs Hard data Facts and numbers Generated by TPS & MIS Purchased data Soft data Nonanalytical information Web-based news portals • Customizable • Delivery to different media 24 Architecture of an EIS: Processing Summarizing Graphical interpreting 25 Architecture of an EIS: Outputs Summary reports Trends Simulations 26 EIS Output: Digital Dashboards Digital dashboard Presentation of summary information Information from multiple sources Ability to drill down if necessary 27 Summary of EIS Characteristics 28 Summary So what’s the trend as you go down the list/up the pyramid? Executive Information Systems Highest level summary of information Management Information Systems Aggregate and collect data Transaction Processing Systems Collect data 29 Summary: Types of Information Systems Weaker EIS MIS Controls and Security TPS Stronger Operations Staff Transaction Processing Source: Business Driven Technology, by Haag, Baltzan, Phillips, McGraw Hill, 2006 (with modifications) 30 Summary: Decision Levels Decision Level Description Example Type of Information Executive Competitive advantage Market leader Long term New products that change the industry External events, rivals, sales, costs quality, trends. Management Improve operations without restructuring Operations Day-to-day actions keep company running 31 New tools to Expenses, cut costs or impschedules, sales rove efficiency models, forecast Scheduling employees, placing orders. Transactions, accounting, HRM, inventory Learning Objectives 32 Information Systems Today: Managing in the Digital World 7-32 Seven Information Systems that Span Organizational Boundaries 33 1. Decision Support Systems Decision making support for recurring problems Used mostly by managerial level employees (can be used at any level) Interactive decision aid What-if analyses 34 Analyze results for hypothetical changes Architecture of a DSS 35 Common DSS Models 36 Information Systems Today: Managing in the Digital World 7-36 Using DSS to Buy a Car Selling price – $22,500 Down payment – $2,500 Monthly payment – about $400 Interest rate information from the bank 37 2. Intelligent Systems Artificial intelligence Simulation of human intelligence Reasoning, learning, sensing, hearing, walking, talking, etc. 38 Intelligent Systems Three types Expert systems Neural networks Intelligent agents 39 Expert Systems Use reasoning methods Manipulate knowledge rather than information System asks series of questions Inferencing/pattern matching 40 Matching user responses with predefined rules If-then format Neural Network System Approximation of human brain functioning Training to establish common patterns Past information New data compared to patterns E.g., loan processing 41 Example: Neural Network System Loan processing system relying on a neural network 42 -42 Intelligent Agent Systems Program working in the background Bot (software robot) Provides service when a specific event occurs 43 Intelligent Agent Types 1. Buyer agents (shopping bots) – search for best price 2. User agents – perform a task for the user 3. Monitoring and sensing agents – keep track of key information 4. Data-mining agents – analyze large amounts of data 5. Web crawlers (web spiders) – browse the Web for specific information 6. Destructive agents – malicious agents designed by spammers 44 3. Data Mining and Visualization Systems Application of sophisticated statistical techniques What-if analyses to support decision making Capabilities can be embedded into a large range of systems 45 Visualization Display of complex data relationships using graphical methods Visualization of a weather system 46 Text Mining Extraction of information from textual documents Web crawlers used to extract information from Internet 47 4. Office Automation Systems Developing documents, scheduling resources, communicating Examples Word processing Desktop publishing Electronic calendars E-mail 48 5. Collaboration Technologies Increased need for flexible teams Virtual teams – dynamic task forces Forming and disbanding as needed Fluctuating team size Easy, flexible access to other team members 49 Need for new collaboration technologies Video Conferencing Costs – few thousand dollars to $500,000 Dedicated videoconferencing systems Located within organizational conference rooms Highly realistic 50 Groupware Enables more effective team work Distinguished along two dimensions 51 Benefits of Groupware 52 6. Knowledge Management Systems Generating value from knowledge assets Collection of technology-based systems Knowledge assets Skills, routines, practices, principles, formulas, methods, heuristics and intuition Used to improve efficiency, effectiveness and profitability Documents storing both facts and procedures Examples • Databases, manuals, diagrams, books, etc. 53 Benefits and Challenges of Knowledge Based Systems 54 7. Functional Area Information Systems Cross-organizational-level IS Support specific functional area Focus on specific set of activities 55 Business Processes Supported by Functional Area Information Systems 56 Cases 57 Amazon.com • 35 million customers worldwide • Innovations leading to satisfaction Fraud protection Personalized greeting Memory for recent purchases Targeted “gold box” offers and bargains Shipping vs. billing address comparison Method of shipment checks Credit card sources checks “One-click” shopping 58 The Growing Blogosphere One of the fastest growing phenomena in the digital world 59 Too Much Technology? RFID and Privacy RFID tags Latest in technological tracking devices Information imprinted on a tag Tag generates signature signal Special RFID reader interprets signal Use of RFID tags Pharmaceutical industry • Tracking of medication from factory to pharmacy Retail businesses 60