Chapter 1: DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE

1. Chapter 1:DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE, Eighth Edition

2. Changing Business Environments and Computerized Decision Support • The business pressures-responses-support model • The business environment • Business environment factors divided into four categories: markets, consumer demands, technology, and societal.

3. Changing Business Environments and Computerized Decision Support (cont.) • Organizational responses: be reactive, anticipative, adaptive, and proactive • Employ strategic planning • Use new and innovative business model • Restructure business process • Use new IT to improve communication. • : • :

4. Changing Business Environments and Computerized Decision Support (cont.) • Computerized support • It used to facilitate closing the gap between the current performance and the desired performance.

5. Changing Business Environments and Computerized Decision Support (cont.)

6. Management Support Systems (MSS) • Four major information technologies have been successfully used to support managers. • DSSs: provide support primarily to analytical, quantitative types of decisions. • Executive (enterprise) support systems: support the informational roles of executives. • Group decision support systems: support managers working in groups. • Intelligent systems: provide mulitfunctional support.

7. DSS Definition • Decision support system (DSS) are used to make business decision often based on data collected by On-Line-Analytical-Processing system (OLAP) • Example of data used for making decision : • Retail sales transaction detail • DSS as an Umbrella term: Describes any computerized system that supports decision making in an organization

8. Why Use of DSS • Why use decision support systems? • Speedy computations • Improved communication and collaboration • Increased productivity of group members • Improved data management • Managing giant data warehouses • Quality support • Overcoming cognitive limits in processing and storing information

9. Why Use of DSS(cont.) • Using the Web • Anywhere, anytime support

10. Decision Making and Management • Management is a process by which organizational goals are achieved through the use of resources (people, money, energy, materials, space, time). • These resources are considered to be inputs, and the attainment of the goals is viewed as the outputof the process. Measuring success: Productivity= output/input

11. Decision Making and Management (cont.) • Management is decsion making • The manager is decsion maker

12. Decision Making and Management (cont.) • The nature of managers’ work • Interpersonal : figurehead, leader, liaison. • Informational: monitor, disseminator, spokesperson. • Decisional: entrepreneur, disturbance handler, resource allocator, negotiator.

13. Decision Making and Management (cont.) • Why Managers Need IT Support • processing information manually is growing increasingly difficult • computerized modeling • examining numerous alternatives very quickly • providing a systematic risk analysis • being integrated with communication systems and databases • being used to support group work

14. REALITY Examination Intelligence Phase  Verification of the Model Design Phase Verification, Testing of Proposed Solution  Choice Phases SUCCESS Implementation of Solution  FAILURE Phases of the Decision Making

15. Phases of the Decision Making (cont.) • Intelligence phase • Organizational objectives • Search and scanning procedures • Data collection • Problem identification • Problem classification • Problem statement • Result: • Reality is examined • The problem is identified and defined

16. Phases of the Decision Making(cont.) • Design phase • Formulate a model (Assumption) • Set criteria for choice • Search for alternative • Predict and measure outcomes • Result: • Representative model is constructed • The model is validated and evaluation criteria are set

17. Phases of the Decision Making(cont.) • Choice phase • solution to the model • Sensitivity analysis • Selection of Best (Good) alternative • Plan for implementation • Design of control system • Result: • Proposed solution is included to the model • If reasonable, move to implementation phase.

18. Phases of the Decision Making(cont.) • Implementation phase • Put solution into action • Result: • Solution to the original problem

19. Decision Making Processes • The process of decision making • Defining the problem (i.e., a decision situation that may deal with some difficulty or with an opportunity) • Constructing a model that describes the real-world problem • Identifying possible solutions to the modeled problem and evaluating the solutions • Comparing, choosing, and recommending a potential solution to the problem

20. Decision makers: Who are They? • Decision maker classification • Individual decision makers can be single person or a computer system • Multiple decision makers can be: • Team where members support a single decision maker • Groups where all members have a say in the decision • Organization where global agreement is needed.

21. Framework for Computerized Decision Support Type of Control Type of Decision Operational Control Managerial Control Strategic Planning Structured Accounts Receivable Order entry 1 Budget analysis, short-term forecasting, personnel reports, make-of-buy analysis 2 Financial management , warehouse location, distribution systems 3 MIS MS models F & S models 4 5 6 Semi-structured Production scheduling inventory control Credit evaluation, Budget Preparation, plan layout, project scheduling, rewarded systems design Building new plant, mergers and acquisitions, new product planning, compensation planning, quality assurance planning DSS 7 8 9 Unstructured Selecting a cover for a magazine, buying software approving loans Negotiating, recruiting and executive, buying hardware, lobbying R & D planning, new technology development social responsibility planning DSS ES Neural Networks Support Needed MIS, MS MS, DSS, EIS, ES EIS, ES, Neural Networks Support Needed

22. Framework for Computerized Decision Support (cont.) • Three type of decision : 1- Structured problems: are routine problems for which standard solution method exist. • Procedure for obtaining the best solution are known • Objective are clearly defined

23. Framework for Computerized Decision Support (cont.) 2- Unstructured problems: are fuzzy, complex problem for which there are no cut-and direct solution methods. • Have no structure phase • Often solved with human intuition 3- Semi-structured problem: is a decision problem in which some but not all phases are structured. • In between solve with standard solution procedure and human judgment

24. Framework for Computerized Decision Support (cont.) • Types of control in all managerial activities • Strategic planning • the long-range goals & policies for resource allocation; • Management control • the acquisition & efficient utilization of resources in the accomplishment of organizational goals • Operational control • the efficient & effective execution of specific tasks.

25. Framework for Computerized Decision Support (cont.) • The decision support matrix • For semistructured decisions andunstructured decisions, conventional MIS and MStools are insufficient ; BUT Decision support systems (DSS) are used. • Computer support for structured decisions • Management science (MS) or operations research (OR) are used . • Automated decision systems (ADS) is used.

26. Framework for Computerized Decision Support (cont.) • Management science (MS) or operations research (OR) The application of a scientific approach and mathematical models to the analysis and solution of managerial decision situations (e.g., problems, opportunities) • It adds new step 2 to the process of decision making, that is classify the problem into standard category.

27. Framework for Computerized Decision Support (cont.) • Automated decision systems (ADS) A business rules-based system that uses intelligence to recommend solutions to repetitive decisions (such as pricing)

28. Architecture of a decision system

29. Architecture of a decision system(cont.) • The architecture of DSS • Data • Models manipulate data as related to a specific situation • Knowledge component • User interface * The user themselves are also important components of the architecture

30. Structure of a decision system • A SYSTEM is a collection of object such as people, resources, concepts and procedure intended to perform an identifiable function or to serve a goal. • Three Distinct Parts of Systems • Inputs • Processes • Outputs

31. Structure of a decision system (cont.) Input(s) output(s) Processes Feedback (flow of information

32. Structure of a decision system (cont.) • Inputs are the element that enter the system • Processes convert or transform inputs into outputs • Outputs describe finished products or consequences of being in the system • Feedback is the flow of information from the output to decision maker, who many modify the inputs or the processes (closed loop) • The Environment contains the elements that lie outside but impact the system performance

33. Modeling in DSS • DSS is “ model-base set of procedures for processing data and judgment to assist manager in his decision making” • A model is simplified representation or abstraction of (complex) reality. • With modeling, one can perform virtual experiments and an analysis on a model of reality, rather than on reality itself.

34. Modeling in DSS (cont.) • Four groups of models: • Iconic (scale) Model • An iconic model—the least abstract model—is a physical replica of a system. • Analog Model • does not look like the real system but behaves like it.

35. Modeling in DSS (cont.) • Mathematical Model • Use mathematical relationship to represent complexity used in most DSS analysis • Mental models • provide a description of how a person thinks about a situation

36. Modeling in DSS (cont.) • Benefits of Models: • Time compression • Low cost construction • Models allow for the simulated compression of time. • Manipulating the model (by changing variables) is much easier than manipulating the real system. • Can model large and extermely complex system with possibly infinite soultion. • Low cosst excustion

37. Modeling in DSS (cont.) • Modeling process and solution approach • Trail and Error • Simulation • Optimization • Heuristics

38. Decision analysis • Decision analysis allow us to select a decision from set of possible decision alternatives when uncertainties regarding the future exist. • The goal is to optimize the resulting return (payoff) in term of decision criteria.

39. Decision analysis (cont.) • Type of decision analysis models: • Decision making under certainty • Decision making under uncertainty • Decision making under risk • Decision making with perfect information • Decision making with imperfect information(Bayesian Theory) • Decision making in light of competitive action (Game Theory)

40. DSS and Data Warehouse • Data warehouse is a decision support database. • The data warehouse is an integrated, subject-oriented, time-variant, non-volatile database that provide support for decision making.

41. DSS and Data Warehouse • Integrated: the data warehouse is centralized, consolidated database that integrates data retrieved from the entire organization. • Subject- oriented: data of data warehouse is arranged and optimized to provide answer to questions coming from diverse functional area within a company.

42. DSS and Data Warehouse • Time-variant: the data warehouse represent the flow of data through time • Non-volatile: once data enter the data warehouse, they are never removed.

43. On-Line Analytical Processing (OLAP) • It is an element of DSS. • It is support ad-hoc querying for business analyst. • Multidimensional view of data is foundation of OLAP Multidimensional data

44. DSS knowledge base • Any true decision requires information. • The knowledge base is where all information is stored.

45. CASE STUDY

46. Case: Managing Global Business at 3M Corporation • The Business Problem • The company had difficulties responding to new customers and markets in the global economy as each business unit kept separate databases and conducted independent decision support activities • The Solution • The Company created a global enterprise data warehouse (GEDW)

47. Case: Managing Global Business at 3M Corporation (cont.) • The Results • Distributors and retailers, as well as end-users, now receive information in minutes instead of weeks or months, including the delivery of rich multimedia • Customers can find all their information in one place • Inventories are lower, and better and quicker inventory decisions are made, even in globally remote locations

48. Case: Managing Global Business at 3M Corporation (cont.) • What have we learned from this case?? • The case demonstrates the existence of vast amounts of important data in organizations, and the importance of organizing that data for optimum use • The case shows the need to share a company’s data internally and with business partners and customers, and to make it available in a format that enables end users to process data quickly • The case explains the data warehouse, and its role in supporting managerial decision making

49. Duty # 1 • Each group have present one case study; under these conditions: • define organization • Define business problem • Provide possible solutions • The result.