1. DSS: An Overview

2. 2 教科書 Decision Support Systems In the 21 st Century – George M. Marakas 參考書 Decision Support Systems and Intelligent systems – Efraim Turban and Jay E. Aronson

3. 3 DSS DEFINITIONS Gorry & Scott Morton(1971)— 互動式電腦化系統，此系統幫助決策者利用資 料與模式解決非結構化問題 Little(1970)— model-based set of procedures for processing data and judgments to assist a manager in his decision making.

4. 4 DSS DEFINITIONS —cont. Bonczek et al.(1980)— A computer-based system consisting of 1. A language system 2. A knowledge system 3. A problem-processing system Alter(1980)—

5. 5 DSS DEFINITIONS —cont. Moore and Chang(1980)— 1. Extendible systems 2. Capable of supporting ad hoc data analysis and decision modeling 3. Oriented toward future planning 4. Used at irregular, unplanned intervals Keen(1980)— DSS apply “to situations where a ‘final’ system can be developed only through an adaptive process of learning and evolution”.

6. 6 DSS DEFINITIONS —cont. Holesapple and Whinston(1981)— 能用來幫助決策者，應用資料及相關模式釐清、 解決問題並作決策的互動式的資訊系統 Keen and Scott Morton(1978)— 決策支援系統結合個人智力資源與電腦能力， 來改善決策品質。為以電腦為基礎，支援決策 者處理半結構化問題的系統。

7. 7 DSS DEFINITIONS —cont. There are many definitions of a DSS, but all have three themes: (1) applied to unstructured problems, (2) supports but does not replace the decision process, (3) is under the user ’ s control.

8. 8 Common DSS Characteristics Employed in semistructured or unstructured decision contexts Intended to support decision makers rather than replace them Supports all phases of the decision-making process Focuses on effectiveness of the process rather than efficiencyeffectiveness efficiency Is under control of the DSS user

9. 9 Efficiency / Effectiveness Efficiency 效率 Effectiveness 效能 公式 追求 minmax Peter Drucker do the thing rightdo the right thing 資源使用目標達成

10. 10 Common DSS Characteristics —cont. Uses underlying data and models Facilitates learning on the part of the decision maker Is interactive and user-friendly Is generally developed using an evolutionary, iterative process Can support multiple independent or interdependent decisions Supports individual, group or team-based decision- making

11. 11 What A DSS Can and Cannot Do The DSS is expected to extend the decision maker ’ s capacity to process information. The DSS solves the time-consuming portions of a problem, saving time for the user. Using the DSS can provide the user with alternatives that might go unnoticed. It is constrained, however, by the knowledge supplied to it. A DSS also has limited reasoning processes. Finally, a “ universal DSS ” does not exist.

12. 12 History of Decision Support Systems The concept was born in the early 1970s, attributed to articles by J.D. Little and Gorry and Scott Morton. Little observed that managers did not use management science models because they were not simple, robust or adaptive. The Mortons coined the term DSS and developed a two-dimensional framework for computer support of managerial activity.

13. 13 Decision support framework (Anthony & Simon)

14. 14 Decision support framework --Gorry and Scort Morton Type of Control Anthony → Operational Control Management Control Strategic Planning

15. 15 Decision support framework --Gorry and Scort Morton Type of Control Simon↓ Operational Control Management Control Strategic Planning Type of Decision Structured Semi- structured Unstructured

16. 16 Decision support framework --Gorry and Scort Morton Type of Control Operational Control Management Control Strategic Planning Type of Decision Structured Inventory control Budget analysis Financial management Semi- structured Securities trading Credit evaluation Building new plant Unstructured Selecting a cover for a magazine Negotiating R & D planning

17. 17 Decision support framework --Gorry and Scort Morton Type of Control Operational Control Management Control Strategic Planning Type of Decision Structured Inventory control Budget analysis Financial management Semi- structured Securities trading Credit evaluation Building new plant Unstructured Selecting a cover for a magazine Negotiating R & D planning

18. 18 Decision support framework --Gorry and Scort Morton Type of Control Operational Control Management Control Strategic Planning Type of Decision Structured Inventory control Budget analysis Financial management Semi- structured Securities trading Credit evaluation Building new plant Unstructured Selecting a cover for a magazine Negotiating R & D planning

19. 19 Decision support framework --Gorry and Scort Morton Type of Control Operational Control Management Control Strategic Planning Type of Decision Structured Inventory control Budget analysis Financial management Semi- structured Securities trading Credit evaluation Building new plant Unstructured Selecting a cover for a magazine Negotiating R & D planning

20. 20 Decision support framework --Gorry and Scort Morton Type of Control Operational Control Management Control Strategic Planning Support Needed Type of Decision Structured Inventory control Budget analysis Financial management MIS Semi- structured Securities trading Credit evaluation Building new plant DSS Unstructured Selecting a cover for a magazine Negotiating R & D planning DSS ES

21. 21 Decision support framework -- Sprague(1980) DatabaseModel Base DBMSMBMS Dialog Management Dialog Interface

22. 22 Ingredients of a DSS The data management system The model management system The knowledge engine The user interface The users

23. 23 Data and Model Management An increasing focus on the value of data to an organization pointed out that the quality and structure of the database largely determines the success of a DSS. A database organizes data into a logical hierarchy based on granularity of the data. The hierarchy contains four elements: 1. Database2. Files 3. Records4. Data elements

24. 24 Hierarchy of Data

25. 25 The Database Management System Even though the data within each file have a common structure (the record), the files themselves may be quite diverse. The important role of organizing the files and databases goes to the DBMS. The two main responsibilities of the DBMS are: 1. Coordinating the tasks related to storing and accessing information. 2. Maintenance of the logical independence between the data in the DSS database and the DSS application.

26. 26 General Functions of the DBMS Data definition – providing a data definition language and allowing for interrelation of data Data manipulation – providing a query language, allowing for capture and extraction Data integrity – allows user to describe rules that maintain integrity and check for errors

27. 27 General Functions of the DBMS (cont.) Access control – allows identification of users, controls access and tracks usage Concurrency control – provides procedures for controlling the effects of simultaneous access Transaction recovery – provides mechanisms for restart and reconciliation in the event of hardware failure

28. 28 The Model Base A model is a simplification of some event constructed to help study the event. The model base is the modeling counterpart to the database; it stores and organizes the various models the DSS uses in its analyses. The MBMS (or model base management system) is the counterpart to the DBMS. The model base is what differentiates a DSS from other information systems.

29. 29 General Functions of the MBMS Modeling language – allows for creation of decision models, provides a mechanism for linking multiple models Model library – stores and manages all models, provides a catalog and description. Model manipulation – allows for management and manipulation of the model base with functions (run, store, query, etc.) similar to those in a DBMS.

30. 30 DSS Knowledge Base Any true decision requires reasoning, which requires information. The knowledge base is where all of this information is stored by the DSS. Knowledge can just be raw information, or rules, heuristics, constraints or previous outcomes. This knowledge is different from information in either the database or model base in that it is problem-specific.

31. 31 Contents of the Knowledge Base Knowledge in the base can be categorized into two simple groups. Facts represent what we know to be true at a given time. Hypotheses represent the rules or relationships we believe to exist between the facts. The next slide shows how credit rules operate on facts about an individual that has applied for a loan.

32. 32 Examples of Credit Rule Combinations

33. 33 Knowledge Acquisition and Retrieval One or more people called knowledge engineers gather the information for the knowledge base. These people are specially trained in techniques for extracting this from experts in the domain. The inference engine is the part of knowledge base that applies the rules to pull the information out in the form the user desires. These concepts are discussed in more depth in Chapters 7 and 8.

34. 34 User Interfaces An interface is a component designed to allow the user to access internal components of a system. In general, the more common the interface, the less training need be provided to users. Think, how many Windows programs use the same menu structure as Microsoft Word? The general functions of a DSS interface are the communication language and the presentation language.

35. 35 General functions of the DSS Interface Communication language – allows for interaction with the DSS in a variety of ways, identifies form of input (see the next slide), provides support to DSS users, captures previous dialogues so future interactions can be improved. Presentation language – provides for presentation of data in a variety of formats, allows for detailed report generation, can provide multiple views of the data.

36. 36 Common Input Devices

37. 37 1-7: The DSS User In a DSS, the user is as much a part of the system as the hardware and software. User roles: Alter classified users into five categories (decision maker, intermediary, maintainer, operator and feeder). Patterns of DSS use: Alter further classifies the various user roles into one of four basic patterns of use. The next slide illustrates those patterns.

38. 38 Alter’s Decision Maker Patterns of Usage

39. 39 Patterns of DSS Use Subscription mode – the decision maker receives regularly scheduled reports. Terminal mode – the decision maker interacts directly with the DSS. Clerk mode – the decision maker uses the system directly, but not online. Output response may take some time. Intermediary mode – the decision maker interacts through the use of one or more intermediaries.

40. 40 1-8: Categories and Classes of DSSs A variety of methods attempt to categorize DSSs: Data-centric and model-centric Formal and ad hoc systems Directed versus nondirected DSSs Procedural and nonprocedural systems Hypertext systems Spreadsheet systems Individual and group DSSs The unique characteristics of a particular scheme may be important in determining the best approach to the design of a new system.

41. 41 Data-Centric and Model-Centric DSSs The classification scheme in Figure 1-1 (seven DSS types) collapses down to two support orientations.

42. 42 Formal and Ad Hoc Systems Donovan and Madnick proposed a scheme based on attributes of the problem-solving context. Directed Versus Nondirected DSSs Silver classifies DSSs by the degree to which the system provides guidance. The next slide illustrates his two-dimensional matrix.

43. 43 Silver’s Classification of Decisional Guidance

44. 44 Procedural and Nonprocedural Systems DSSs can be classified according to their degree of procedurality. Hypertext Systems Another classification scheme focuses on how the system manages knowledge. A text-based DSS can use hypertext links to direct the user, as on the following web page.

45. 45 Example of WWW Page With Hypertext Links Hypertext Links

46. 46 Spreadsheet Systems Application programs such as Excel or 1-2-3 can serve as a front end to sophisticated and complex decision support systems. Individual and Group DSSs Finally, we can consider if a DSS supports single decision makers or groups. A group DSS has a prominent communication layer that may be absent in an individual DSS.