Lecture

1. 2 Lecture Organisational Information Systems (Unit 2)

2. Different ways in which information can create value for organisations: Customers and markets Add value Organisation A Organisation B Reduce cost Manage risks Transactions and processes Market, financial, legal, operational Organisation C New products, new services, new business ideas Create new reality (Chaffey and Wood, 2005)

3. Information Systems Support of business operations Support of managerial decision making Operations Support Systems Management Support Systems Transaction Processing Systems Process Control Systems Enterprise Collaboration Systems Processing business transactions Control of industrial processes Team and work group collaboration Management Information Systems Decision Support Systems Executive Information Systems Pre-specified reporting for managers Interactive decision support Information tailored for executives Operations and management classification of information systems (James A O’Brien (2004), ‘Management Information Systems, Managing information technology in the business enterprise’, 6th Edition, McGraw-Hill Irwin).

4. Advances in IT and telecommunications Globalisation Digital firms Virtual enterprise

5. “..the increasing integration of economies around the world, particularly through trade and financial flows. .. the movement of people (labour) and knowledge (technology) across international borders.” Globalisation (The IMF Staff (2002) at www,imf.org/external/np/exr/ib/2000/041200.htm)

6. Virtual enterprise A company that: joins with another company operationally, but not physically, to design and manufacture a product; distributed geographically and whose work is coordinated through electronic communications; share skills, costs, and access to one another’s markets

7. Digital firms A firm in which nearly all organisation’s significant business relationships with customers, suppliers, and employees are digitally enabled and mediated. Core business processes are accomplished through digital networks

8. Digital Firms • sense and respond to their environments more rapidly than traditional firms • offer extraordinary opportunities for more flexible global organisation and management. • time shifting and space shifting are the norms

9. The Emerging Digital Firm Customers Factories • Online marketing • Online sales • Built-to-order products • Customer service • Sales force automation • Just-in-time production • Continuous inventory replenishment • Production planning Remote offices and work groups • Communicate plans and policies • Group collaboration • Electronic communication • Scheduling Suppliers Business partners • Procurement • Supply chain management • Joint design • outsourcing (Laudon & Laudon, 9th Edition, 2006:12)

10. Exercise Laudon and Laudon, 10th Edition: Read the case study on Accenture in Chapter 1, page 9 and do the exercises at the end. OR Laudon and Laudon, 9th Edition: Read the case study on CEMEX in Chapter 1, page 14, and do the exercises at the end.

11. Characteristics of organisational problems and solutions Bounded-rationality The rational model Satisficing Optimising Solution Problem structured unstructured Semi-structured

13. Decision Dimensions in an Organisation Strategic management Tactical management Operational management Stair and Reynolds High Impact on reaching corporate goals Decision making authority Problem uniqueness Need for external data Number of people and functions affected by decision Planning horizon Low

14. Decision Support Systems • A set of interactive software programs that provide managers with data, tools, and models to make semistructuredand unstructureddecisions.

15. DSS support management decision making by integrating: • Company performance data • Business rules based on decision tables • Analytical tools and models for forecasting and planning

16. The structure of DSS Dialog Management Knowledge Management Model Management Data Management User DSS Internal and External databases (Information Systems, Zwass, p57)

17. Decision Models Summary statistics, trend projections, hypothesis testing, etc. • Statistical Models • Financial and Accounting Models • Production Models • Marketing Models • Human Resource Models Cash flow, internal rate of return, other investment analysis

18. Examples of Model driven DSS • Voyage estimating system (Laudon & Laudon, Chapter 2, pages 54-57 • More examples in Laudon & Laudon, Chapter 12,

19. 1 Cargo reservation system Flight schedule server Passenger reservation system request Cargo booking agent 2 Confirm/reject Availability/ minimum price Cargo size, rate data CargoProf revenue management system Cargo availability forecast Passenger booking agent Passenger forecast data (Laudon & Laudon, 8th ed., page 351)

20. Data driven DSS • Make use of OLAP and data mining to extract useful information. • With OLAP uses need to have a good idea of what information they are looking for. • OLAP allows data to be viewed from different perspectives, i.e. the same data is viewed in different ways using multiple dimensions.

21. Data driven DSS • Data mining is more discovery driven. • Finds hidden patterns and relationships. • Data mining can yield associations, sequences, classifications, clusters, and forecasts.

22. Types of Analytical Modelling • What-if Analysis • Change selected variables and observe its effect on other variables • Sensitivity Analysis • Observe how repeated changes to one variable affect other variables • Goal-seeking Analysis (how-can) • Make repeated changes to selected variables until a chosen variable reach a target value • Optimisation Analysis • Finding an optimum value for selected variables, under a set of given constraints

23. Group Decision Support Systems (GDSS) • Computer-based systems that enhance group decision making and improve the flow of information among group members.

24. GDSS Alternatives [Figure 10.14] Stair & Raynolds

25. Decision Room • Decision makers are located in the same building or geographic area. • Decision makers are occasional users of the GDSS approach. Decision room alternative Stair & Raynolds

26. Local Decision network Schultheis & Sumner

27. GDSS Alternatives • Teleconferencing alternative • -Location of group members is distant. • -Decision frequency is low. • -Group meetings at different locations are tied together

28. Teleconferencing chairs terminals table video cameras public screen Schultheis & Sumner Robert Schulthesis and Mary Sumner

29. Wide area decision network Wide area decision network • Location of group members is geographically remote. • Decision frequency is high. • Virtual workgroups • Groups of workers located around the world working on common problems via a GDSS Stair & Raynolds

30. The Executive Support System

31. The Executive Support System (ESS) • An IS that is focused on meeting the strategic needs of the organisation • Designed explicitly for the purposes of senior management • Used by senior management without technical intermediaries Easy to use, easy to learn

32. Use state-of-the-art integrated graphics, text, and communication technology Web browsing, e-mail, groupware tools, DSS and Expert System capabilities • Also known as an Executive Information System (EIS)

33. The Executive Support System (ESS) • Require a greater proportion of information from outside the business Competitors, government, trade associations, consultants, etc. • Are linked with value added business processes

34. ESS Support: • defining an overall vision • strategic planning • strategic organising and staffing • strategic control • crisis management

35. Expert Systems • Knowledge Based Information System (KBIS) • Expert System (ES): • A KBIS that uses its knowledge about a specific area to act as an expert consultant to the end user

36. Expert System Software Inference Engine INPUT IF… and IF … and IF … and IF … THEN QUERY User Interface Programs EXPERT ADVICE OUTPUT User Interface Programs Expert System USER Knowledge Base Fact… Fact… Realtionship … Fact … Realtionship … Realtionship …

37. Knowledge Engineering Expert System Development THE EXPERT and/or THE KNOWLEDGE ENGINEER Knowledge Acquisition programme Components of an Expert System, and the components involved in building the knowledge base. (Adapted from O’Brien (2004:293) and Oz(2006:333))

38. Whale Watcherhttp://www.aiinc.ca/demos/whale.html

39. Expert Systems Applications in Business Chapter 11, Minicase 2, Page 501-502 of Turban etal. Pages 438-439, Laudon and Laudon http://www.exsys.com/exsys.html - Case Studies

40. Expert Systems Applications in Business CLUES (Countrywide’s Loan Underwriting Expert Systems) Intelligent help desk - IBM, Microsoft, Compaq CADS (Consumer Appliance Diagnostic System) - Whirlpool

41. Web-based Expert Systems • Disseminating knowledge and expertise • Transferring ESs over the Net to human users and other computerised systems • Also supports the spread of multimedia-based ES (intellimedia systems)

42. Laudon & Laudon, p47 Executive support systems (ESS) Management Information systems (MIS) Decision support systems (DSS) Knowledge systems (ES and office systems) Transaction processing systems (TPS)

43. Artificial Intelligence Robotics Applications Cognitive Science Applications Natural Interface Applications Natural languages Speech recognition Multisensory interfaces Virtual reality Expert systems Learning systems Fuzzy Logic Genetic Algorithms Neural Networks Intelligent Agents Visual perception Tactility Dexterity Locomotion Navigation The major application areas of AI (O’Brien, 2002:223)

44. Intelligent Support Systems • Systems that augment a manager’s intelligence and expertise • Expert Systems(ES) • Artificial intelligence • Natural Language processing • Neural networks • Fuzzy Logic • Intelligent agents