1. CHAPTER 11 Systems Development and Project Managmenet

2. Introduction to the Systems Approach It’s methodology for problem solving The more time spent planning, the better the outcome Note the process is typically iterative Systems approach masters Ed Yourdon Grady Booch The GOF Gamma, Helm, Johnson, Vlissides

3. The Systems Approach (Steps) Problem identification (planning) Systems analysis Systems design Systems development Systems testing Systems deployment (implementation) Systems maintenance

4. The Systems Approach (Problem Identification) An existing system does not meet a need or expectation Conduct feasibility studies If a project seems feasible, assemble a project management plan and team

5. The Systems Approach (Feasibility Domains) Organizational Do we have the human resources Do we have the organizational resources Technical Does the hardware / software exist Economic Cost / benefit analysis Accounting ROI Present value analysis Operational

6. The Systems Approach (Systems Analysis) Analyze information needs of constituents Develop a system’s functional requirements Analysis tools Brainstorming Lateral thinking

7. The Systems Approach (Systems Analysis) Develop a list of functional requirements User interface requirements Processing requirements Storage Controls Input validation Event notification Human controls

8. The Systems Approach (Systems Design) We need to completely understand the existing system If it’s not broke, don’t fix it Understand how users use the existing system Interviews Know what users want out of the new system At times, users don’t know what they want

9. The Systems Approach (Systems Design) Logical design Design how the system will work Design workflow and information flow Design the user interface Screen diagrams Navigation diagrams Appropriate use of color Data design Entity relationship diagrams

10. The Systems Approach (Systems Design) Process design Tools Flowcharts IP charts UML use-case diagrams UML activity diagrams UML Statechart diagrams

11. The Systems Approach (Systems Design) Physical design Select physical hardware and software Note that there may be site preparation requirements

12. The Systems Approach (Development) Hardware and software acquisition Use RFPs and RFQs to evaluate alternatives Hardware and software benchmarking Decisions Make vs. buy Lease vs. buy Internal implementation or outsourcing Documentation For users For IS staff Preserve organizational memory

13. End User Development Positives Users get what they want Negatives Users don’t know what they want Users may have a narrow minded vision of the system They may not see how a system contributes to the organizational mission Loss of centralized control Users are not experienced in system design methodologies

14. Testing My rule is, you cannot ever test too much or be too thorough http://video.google.com/videoplay? docid=2889527841583480458&q=p wnz http://video.google.com/videoplay? docid=2889527841583480458&q=p wnz

15. The Systems Approach (Deployment) User training Data conversion Systems testing Parallel (run 2 systems at once) Pilot study (deploy in limited sited) Phased (deploy functionality in stages) Plunge (only fools rush in) Systems deployment

16. The Systems Approach (Maintenance) Perform a postimplementation audit to determine whether goals were met Revise system as necessary

17. Development Methodologies (1) Waterfall The systems lifecycle operates as a sequence of states Sequential development

18. Development Methodologies (2) Agile processes and iterative development Break a large project into several small projects Deliver results in small stages

19. Development Methodologies (3) Extreme programming It’s an agile methodology at its best Relies on close communication between users and developers Relies on experienced developers Uses small incremental deliverables

20. Development Methodologies (4) Scrum delivers small software pieces every 30 days The term derives from the game of rugby The development effort is monitored and controlled daily Some organizations use a combination of these methodologies

21. Waterfall (Illustration)

22. Scrum (Illustration)

23. Successful Software Development Metrics Control costs – Don’t keep throwing money at a bad project Avoid scope creep and feature creep Test and deliver Involve all constituents

24. Project Management (Introduction) We spend about $1 trillion on IT projects 3 out of 10 project fail One in four does not following business rules and requirements

25. Why Projects Fail

26. Roles in Project Management

27. Choosing Strategic Projects Projects should match organizational goals Projects should be prioritized Perform financial analysis to determine the best projects

28. Project Planning Create a project charter which clearly lists Scope Objectives Constraints Assumptions Create a project plan and timeline Pert and Gantt charts

29. Project Outsourcing We outsource to Tap into outside expertise Focus on core business goals rather than develop extensive IT infrastructure Reduce head count and expenses Minimize technology investment Reduce cost

30. Types of Outsoucring Onshore Nearshore Offshore

33. Artificial Intelligence (Introduction) Designed to leverage human capabilities rather than replace them Goals Develop machines that think We are trying to mimic human intelligence There philosophical and moral debates about AI

34. Artificial Intelligence (The Turing Test) A human interviewer and computer interact The test is passed if: The computer did not know if it was interacting with a person The person did not know if it was interacting with a computer No machine has ever passed the Turing test

35. AI (Case Studies) Authorizing financial transactions AMEX fraud detection Configure hardware and software Dell and others Problem diagnosis

36. Applications of AI Decision management Diagnostic Design Product or process selection Process control

37. Domains of AI Expert systems and knowledge- based systems Neural networks Fuzzy logic Soft computing Neural networks Generic Algorithms Robotics Natural Interfaces

38. Expert Systems The machine is acts as the expert They are knowledge-based information systems Types of knowledge bases Case based Frame based Object bases Rule based Pharmacologic interaction Medical diagnosis

39. AI (Neural Networks) Try to mimic the operation of the human brain Software that learns Handwriting recognition Medical diagnosis Pattern recognition Sports betting systems

40. AI (Fuzzy Logic) Deals with uncertainty Near, far, similar to Example Auto-focus cameras

41. AI (Genetic Algorithms and Intelligent agents) Genetic algorithms Conceptually similar to evolution and genetic mutation Intelligent agents Outlook detects spam and deletes it The Roomba vacuum (http://store.irobot.com/corp/index.jsp)http://store.irobot.com/corp/index.jsp

42. AI (Intelligent Agents) Software surrogate for an end user Uses built in rules to make decisions for an end user Adaptive testing Outlook to delete junk e-mail User interface agents Help users run software

43. Data Mining Use data mining to sift through information to uncover hidden patterns More later

44. Business Processes A standardized set of activities that accomplish a specific task Business processes are typically connected together A process should be stable (have few, if any, exceptions)

45. Business Process (Order to Cash) Issue a sales quotation (sales) Receive a purchase order (sales) Issue a sales order (sales) Ship goods (warehouse) Issue an invoice (accounting) Receive payment (accounting

46. Optimizing Business Processes Improving a business process can Speed the checkout process (automated check stands) Reduce cost (online banking and other transactions) Production and manufacturing optimization Business processes exist in every functional area of a business

47. Categorizing Business Processes Customer facing processes Seen by the customer Your Web site Business facing processes Seen by the business Human resource systems

48. Enhancing Business Processes Business Process Improvement Business Process Reengineering Business Process Modeling A graphical description of a business process

49. Business Process Improvement Make incremental improvements on existing business processes Take advantage of new technologies Simple automation tasks Process improvement can be continuous or apply to a discrete processes

50. Business Process Reengineering Redesign workflow and existing business processes Reengineering is a sliding scale From a simple change to a process To a complete overhaul of the way a company does business This can carry a high risk of failure

52. Deciding What to Reengineer Analyze the costs and benefits of the project using financial and accounting methods Perform risk assessment

53. Modeling (General) A model is a simplified, often pictorial, representation of reality We can model many things Architectural plans and drawing 3-dimensional electronic models Models of business processes

54. Business Process Modeling Models can be used reverse engineer as system (as-is process) Models can be used to design new processes and workflows (to-be process) Several diagramming tools are used to model systems Flowcharts / UML diagrams / Use case diagrams / etc…

55. Flowchart of a Business Process

56. Business Process Management We take a proactive and enterprise- wide approach to Understanding processes Optimizing them Integrating processes across functional business units

59. Decision making

60. Introduction to Decision Making How do we make decisions? What methods do we use as a basis for the decisions we make? How do we assess whether a decision was good or bad? Could the decision have been improved? Today, decisions are made using massive amounts of data and quantitative (statistical) analysis Fact-based decision making

62. Decision-making Steps Problem identification Gather facts to Fully understand the problem Who will fix it What recourses are needed Devise possible solutions Evaluate and select Implement

63. Types of Decisions Operational Structured decisions Software systems are making more and more of these Managerial Sem-istructured decisions Strategic Unstructured decisions

64. Measuring IT Performance (1) IT capital expenditures can be huge Software / hardware / training 112 Million for Hershey’s ERP Expenditures need to be measured to determine whether they are worthwhile We measure efficiency and effectiveness The two are interrelated

65. Measuring IT Performance (2) Efficiency metrics (The technology itself) System uptime (availability) Response time (time to render a Web page) Transaction processing performance (database transactions per second) Information accuracy

66. Measuring IT Performance (3) Effectiveness metrics (How well the technology works) Customer satisfaction Sales increases Cost reductions Use accounting and financial methods to assess Cost/benefit analysis, NPV, ROI, cash flow Usability How many clicks to accomplish a task

67. Measuring Success Efficiency and effectiveness metrics Critical success factors These should be quantitative Don’t create to many CSFs Key performance indicators How do we measure those CSFs WHAT YOU MEASURE IS WHAT YOU GET

68. IT Systems and Decision Making Transaction processing systems Management information systems Decision support systems Executive information systems Supply chain systems