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Efraim Turban and Jay E. Aronson Decision Support Systems and Intelligent Systems.

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Presentation on theme: "Efraim Turban and Jay E. Aronson Decision Support Systems and Intelligent Systems."— Presentation transcript:

1 Efraim Turban and Jay E. Aronson Decision Support Systems and Intelligent Systems

2 CHAPTER 1 Management Support Systems

3 DECISION MAKING AND COMPUTERIZED SUPPORT n Management Support Systems (MSS) Computerized technologies n Objectives –Support managerial work –Support decision making

4 Management Support Systems An Overview Emerging and Advanced Computer Technologies for Supporting Managerial Problem Solution n Changing Organizational Structure n Enabling Business Transformation n Changing Management Methods

5 Managers and Decision Making: Why Computerized Support? n Competition n Speed n The MANAGERS are always responsible for decision making

6 The Nature of Managers’ Work [Make Decisions!] Mintzberg (1980) (Table 1.1) Roles n Interpersonal –Figurehead –Leader –Liason n Informational –Monitor –Disseminator –Spokesperson n Decisional –Entrepreneur –Disturbance Handler –Resource Allocator –Negotiator Managers need information and use computers to support decision making

7 Managerial Decision Making and Information Systems n Management is a process by which organizational goals are achieved through the use of resources n Resources: Inputs n Goal Attainment: Output n Measuring Success: Productivity = Outputs / Inputs

8 n Management is decision making n The manager is a decision maker n Now fast changing, complex environment n Trial-and-error: not a great approach n Factors affecting decision making (Figure 1.1) Management

9 Factors Affecting Decision Making (Figure 1.1) n Technology / Information / Computers n Structual Complexity / Competition n International Markets / Political Stability / Consumerism n Changes, Fluctuations

10 Managers and Computerized Support n Information Technology: vital to the business n Support technologies extensively implemented

11 Computer Applications Evolving from TPS and MIS to Proactive Applications (DSS) New modern management tools in n Data access n Online analytical processing (OLAP) n Internet / Intranet / Web for decision support

12 Need for Computerized Decision Support and the Supporting Technologies n Speedy computations n Overcome cognitive limits in processing and storage n Cognitive limits may restrict an individual’s problem-solving capability n Cost reduction n Technical support n Quality support n Competitive edge

13 Decision Support Technologies Management Support Systems (MSS) n Decision Support Systems (DSS) n Group Support Systems (GSS) n Enterprise (Executive) Information Systems (EIS) n Enterprise Resource Planning (ERP) and Supply-Chain Management (SCM) n Knowledge Management Systems n Expert Systems (ES) n Artificial Neural Networks (ANN) n Hybrid Support Systems n Intelligent DSS

14 Framework for Decision Support n Figure 1.2 (Gorry and Scott Morton, 1971) Combination of n Simon (1977) Taxonomy n Anthony (1965) Taxonomy

15 Decision Support Framework Type of Control OperationalManagerialStrategic ControlControlControl Type of Decision Structured Semistructured Unstructured

16 Decision Making Along a Continuum (Simon) Highly Structured (Programmed) Decisions Highly Unstructured (Nonprogrammed) Decisions Semistructured Decisions

17 Three Phase Decision-making Process (Simon) n Intelligence--searching for conditions that call for decisions n Design--inventing, developing, and analyzing possible courses of action n Choice--selecting a course of action from those available

18 n Unstructured problem has no structured phases n Semistructured problem has some (or some parts with) structured phases n Structured problem has all structured phases –Procedures for obtaining the best solution are known –Objectives are clearly defined –Management support systems can be useful

19 n Unstructured problems often solved with human intuition n Semistructured problems in between Solve with standard solution procedures and human judgment n A Decision Support System can help managers understand problems in addition to providing solutions n Goal of DSS: Increase the effectiveness of decision making

20 Anthony’s Taxonomy (1965) n Encompass ALL managerial activities –Strategic planning –Management control –Operational control n Combine Anthony’s and Simon’s Taxonomies n DSS for semistructured and unstructured decisions n MIS and management science approaches insufficient

21 Computer Support for Structured Decisions n Since the 1960s n Repetitive in nature n High level of structure n Can abstract and analyze them, and classify them into prototypes n Solve with quantitative formulas or models n Management Science (MS) / Operations Research (OR)

22 Management Science Scientific approach to automate managerial decision making 1. Define problem 2. Classify problem 3. Construct mathematical model 4. Find and evaluate potential solutions 5. Choose and recommend a solution Modeling: Transforming the real-world problem into an appropriate prototype structure

23 Decision Support Systems Concept n DSS are interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems (Scott Morton, 1971). n Decision support systems couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computer-based support system for management decision makers who deal with semi-structured problems (Keen and Scott Morton, 1978). Content-free expression n There is no universally accepted definition of DSS Umbrella term vs. narrow definition (specific technology)

24 Major DSS Characteristics (DSS In Action 1.5: Houston Minerals Case) n Initial risk analysis (management science) n Model scrutiny using experience, judgment, and intuition n Initial model mathematically correct, but incomplete n DSS provided very quick analysis n DSS: flexible and responsive. Allows managerial intuition and judgment

25 Why Use DSS? Perceived benefits –decision quality –improved communication –cost reduction –increased productivity –time savings –improved customer and employee satisfaction

26 Major Reasons n Unstable economy n Difficulty in tracking numerous business objectives n Increased competition n Electronic commerce n Existing systems did not support decision making n IS Department is too busy n Special analysis n Need accurate information n Organizational winner n New or timely information needed n Mandated by management n Cost reductions n End-user computing

27 Group Support Systems (GSS) n Decisions often made by groups n Supports groupwork, anytime, anyplace Also called n Groupware n Electronic meeting systems n Collaborative computing

28 Executive Information (Support) Systems (EIS, ESS) n Organizational view n Information needs of executives / managers n Customized user seductive interface n Timely and effective tracking and control n Drill down n Filter, compress, and track critical data / information n Identify problems / opportunities

29 EIS n Mid-1980s - large corporations n Now global n Affordable to smaller companies n Serves managers as enterprise-wide systems

30 Expert Systems (ES) n Experts solve complex problems n Experts have specific knowledge and experience n Expert systems mimic human experts n ES performance comparable to or better than experts in a specialized and usually narrow problem area

31 Intelligent Agents n Help automate various tasks n Increase productivity and quality n Learn how you work

32 Artificial Neural Systems n Artificial Neural Networks (ANN): n Mathematical models of the human brain n ANN learn patterns in data n ANN can work with partial, incomplete, or inexact information

33 Knowledge Management Systems (KMS) n Capture and reuse knowledge at the organizational level n Knowledge repository for storage n Organizational impacts can be dramatic

34 ERP and SCM n Enterprise Resource Planning (Management) n Supply Chain Management including Customer Resource Management (CRM) n Enterprise-level cost cutters

35 Cutting Edge Intelligent Systems n Genetic Algorithms Work in an evolutionary fashion n Fuzzy Logic Continuous logic (NOT just True / False) n Intelligent Agents In search engines, , electronic commerce

36 Hybrid Support Systems n Combines MSS technologies n Use strengths of each n Goal: successful solution of the managerial problem n Tools support each other n Tools can add intelligence to traditional MSS

37 Computerized Decision Aids Evolution and Attributes n Computerized procedures development aids decision making (Table 1.2) n DSS supports specific questions (Table 1.3)

38 Evolutionary View of CBIS 1. Time Sequence n mid-1950sTransaction Processing Systems (TPS) n 1960sMIS n 1970sOffice Automation Systems DSS n 1980s DSS Expanded Commercial applications of expert systems Executive Information Systems n 1990s Group Support Systems Neural Computing Integrated, hybrid computer systems

39 2. Computer evolved over time 3. Systemic linkages in how each system processes data into information Relationship among these and other technologies (Figure 1.3)

40 Relationship Among Technologies n Each technology unique n Technologies interrelated n Each supports some aspects of managerial decision making n Ever expanding role of information technology improving management n Interrelationship and coordination evolving

41 Summary n DSS has many definitions n Complexity of managerial decision making is increasing n Computer support for managerial decision making n Several MSS technologies including hybrids


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