Decision Support Systems - PowerPoint PPT Presentation

slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
Decision Support Systems PowerPoint Presentation
Download Presentation
Decision Support Systems

play fullscreen
1 / 40
Decision Support Systems
Download Presentation
Download Presentation

Decision Support Systems

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Decision Support Systems Instructor: YAO Zhong Term: Fall, 2010

  2. Course Arrangement Total 32 hours. Teaching 32 hours and including students’ presentations. Textbook: Efraime Turban, etc. Decision Support Systems and Intelligent Systems, 7/e or 8/e. 杨东涛、钱峰译《决策支持系统与智能系统》 机械工业出版社,2009

  3. Assessing: Total 100 points Assignment works: 30% • Individual Work*.(15%) • Group work.(15%) Class interactive (Including Attendance):20% Examination:50% * If two or above students are the same in their assignments, both they will be ruled out this course.

  4. Chapter 1 Management Support Systems:An Overview

  5. Slide 1 - 1 1.1 Managers and Decision Making • The Nature of Managers’ Work Mintzberg’s 10 Management Roles. • INTERPERSONAL • Figurehead: Symbolic head; Obliged to perform a number of routine duties of a legal or social nature. • Leader: Responsible for the motivation and activation of subordinates; Responsible for staffing, training, and associated duties. • Liaison: Maintain self-developed network of outside contacts and informers who provide favors and information.

  6. Slide 1 - 2 1.1 Managers and Decision Making • The Nature of Managers’ Work Mintzberg’s 10 Management Roles • INFORMATIONAL • Monitor: Seeks and receives a wide variety of specific information (much of it current) to develop a thorough understanding of the organization and environment; emerges as nerve center of the organization’s internal and external information. • Disseminator: Transmits information received from outsides or from subordinates to members of the organization, some information factual, some involving interpretation and integration. • Spokesperson: Transmits information to outsiders on the organization’s plans, policies, actions, results, and so forth; serves as expert on organization’s industry.

  7. Slide 1 - 3 1.1 Managers and Decision Making • The Nature of Managers’ Work Mintzberg’s 10 Management Roles • DECISONAL • Entrepreneur: Searches organization and its environment for opportunities and initiates improvement projects to bring about change; supervises design of certain projects • Disturbance Handler: Responsible for corrective action when the organization faces important, unexpected disturbances • Resource Allocator: Responsible for the allocation of organizational resources of all kinds-in effect the making or approving of all significant organizational decisions • Negotiator: Responsible for representing the organization at major negotiation

  8. Slide 1 - 4 1.2 Managerial Decision Making and Information Systems • Managerial Decision Making • Productivity=Outputs( Products, service) /Inputs (resources) • Factors Affecting Decision Making Technology Increasing -> More alternatives Information/Computers Increasing -> to choose from Structural complexityIncreasing-> Larger Cost of CompetitionIncreasing-> making errors International Markets Increasing-> More uncertainty Political Stability Decreasing-> regarding the Consumerism Increasing-> future. Government intervention Increasing-> • Information Systems

  9. Slide 1 - 5 1.2 Managerial Decision Making and Information Systems • Information Systems As a results of these trends and changes, it is very difficult to rely on a trial-and-error approach to management, especially in decisions involving the factors in above. Managers must become more sophisticated: They must learn how to use new tools and techniques that are being developed in their fields. Some of these tools and techniques are the subject of this course.

  10. Slide 1 - 6 1.3 The Need for Computerized Decision Support and The supporting Technologies • A Computerized decision support system may be needed for various reasons. Here are some common ones: • Speedy computation: The computer allows the decision maker to perform large numbers of computations very quickly and at a low cost. Timely decisions are critical for many situation, ranging from a physician’s decision in an emergency room to that of a stock trader. • Overcoming cognitive limits in processing and storage: Human mind is limited in its ability to process and store information, in an error-free fashion, whenever needed. • Cognitive limits: An individual’s problem-solving capability is limited when diverse information and knowledge are required. Pooling several individuals may help, but problem of coordination and communication may

  11. Slide 1 - 7 1.3 The Need for Computerized Decision Support and The supporting Technologies be created in workgroups. Computerized systems can enable people to quickly access and process vast amount of stored information. Computer can also help in easing the coordination and communication of group-work. • Cost reduction: Assembling a group of decision makers, especially experts, may be costly. Computerized support can reduce the size of the group and enable the group to communicate from different locations (saving travel costs). Also, the productivity of staff support (such as financial and legal analysts) may be increased. Such support is needed by the decision makers: Increased productivity means lower cost. • Technical support: Many decisions involve complex computations. Data may be stored in different databases, possibly outside the organization. The data may include sounds and graphics and there may be a need to transmit

  12. Slide 1 - 8 1.3 The Need for Computerized Decision Support and The supporting Technologies them quickly, and economically. • Quality Support: Computers can improve the quality of the decisions made. For example, more alternatives can be evaluated, risk analysis can be performed quickly,views of experts (some of whom are in remote locations) may be collected quickly and at a lower cost. Such expertise may be derived directly by a computer system. Using computers, decisions makers can perform complex simulation, checking many possible scenarios, and assess diverse impacts quickly and economically. All these capabilities lead to better decisions. • Competitive edge: business process reengineering and empowerment.Competitive pressures make the job of decision making difficult. Competition is not just on price, but also on quality, timeless, customerization of products, and customer support. Organization must be able to

  13. Slide 1 - 9 1.3 The Need for Computerized Decision Support and The supporting Technologies frequently and rapidly change their mode of operations, reengineer processes and structures, empower employees, and innovate. Decisions support technologies such as expert systems may be enable meaningful empowerment by allowing people make good decision quickly, even if they lack some knowledge. Decision support systems are used in business process reengineering: research into competitor’s activities, customerization of products, and customer services can be facilitated by computerized voice systems. • The primary Decision Support Technologies Decision Support can be provided by one or more decision support technologies (tools). The major decision technologies are:

  14. Slide 1 - 10 1.3 The Need for Computerized Decision Support and The supporting Technologies The major decision technologies are: Management Support System Technologies (Tools) • Decision support systems (DSS) /Business Intelligence • Group Support Systems (GSS), including Group DSS (GDSS) • Executive Information Systems (EIS) • Experts Systems (ES) • Artificial Neural Networks (ANN) • Hybrid Support Systems. In this text, the term management support systems (MSS) refers to the application of any technology, either as an independent tool or in combination with other information technologies.

  15. Slide 1 - 11 1.4 A Framework for Decision Support According to Simon (1977) and Anthony (1965), the framework is as follows.

  16. Slide 1 - 12

  17. Slide 1 - 13 1.4 A Framework for Decision Support • The left side of table is based on Simon’s idea that decision-making processes fall among a continuum that ranges from highly structured (sometimes called programmed) to highly unstructured (nonprogrammed) decisions. • Structured processes are routine and repetitive problems for which standard solution exist. The procedures for obtaining the best (or at least good enough) solution are known. Whether the problem involves finding an appropriate inventory level or choosing an optimal investment strategy, the objectives are clearly defined. Common objectives are cost minimization or profit maximization.

  18. Slide 1 - 14 1.4 A Framework for Decision Support • Unstructured processes are fuzzy, complex problems for which there are no cut-and–dried solutions. The human intuition is often the basis for decision making. Typical unstructured problems including planning new service, hiring an executive, or choosing a set of R&D projects for next year. • Semistructured problems fall between the structured and unstructured, having some structured elements and some unstructured elements. Solving problem involving a combination of both standard solution procedures and human judgment.

  19. Slide 1 - 15 1.4 A Framework for Decision Support • Second half of this framework is based on Anthony taxonomy. • Strategic planning, or the long-term goals and the policies for resource allocation; • Management Control, or the acquisition and efficient use of resources in the accomplishment of organizational goals; • Operational control, or the efficient and effective execution of specific tasks.

  20. Slide 1 - 16 1.4 A Framework for Decision Support Simon also described the decision-making process as a three-phase process of intelligence, design, and choice. • intelligence, Searching for conditions that call for decision • design, inventing, developing, and analyzing possible courses of action • choice:selecting a course of action from those available. • (Implementation) Sprague[1980].

  21. Slide 1 -17 1.4 A Framework for Decision Support In addition, lower-level manager will take the more structured and operational control-oriented tasks (cell 1,2,and 4); whereas the tasks in cell 6, 8 and 9 are the responsibility of executives. This means that DSS and EIS, neural computing and ES are more often applicable for people tackling specialized, complex problem. Computer Support for Structured Decisions Structured and semistructured decisions, especially of the operational and managerial control type, have been supported by computers since the 1960s. Decisions of this type are made in all functional areas, especially in finance and production (operations management) Management Science (MS)and Operations Research(OR)

  22. Slide 1 - 18 1.4 A Framework for Decision Support Management Science (MS) and Operations Research(OR) • Defining the problem (a decision situation that may deal with some trouble or with an opportunity) • Classifying the problem into a standard category • Constructing a mathematical model that describes the real-world problem • Finding potential solutions to the modeled problem and evaluation them • Choosing and recommending a solution to the problem

  23. Slide 1 - 19 1.5 The Concept of Decision Support Systems In the early 1970s, Scott Morton first articulated the major DSS concepts. He defined DSS as “interactive computer-based systems, which help decision maker utilize data and models to solve unstructured problems” • Another definition provided by Keen and Morton (1978) is: • Decision support systems couple the intellectual resources of individual 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.

  24. Slide 1 - 20 1.5 The Concept of Decision Support Systems • Note that DSS, like MIS and other MSS technologies, is a content-free expression; that is, it means different things to different people. There is no universally accepted definition of DSS. • DSS as an Umbrella Term DSS is sometimes used as an umbrella term to describe any and every computerized system used to support decision making in an organization. An organization might have an executive information system for its top executives, separate DSS for marketing, finance, accounting, an MRP system for production, and several expert systems for product repair diagnostics and help desks. DSS encounters them all.

  25. Slide 1 - 21 1.5 The Concept of Decision Support Systems • Why use a DSS A survey conducted by Hogue and Watson (1983) identified six main reasons: • Accurate information is needed 67 • DSS is viewed as an organizational winner 44 • New information is needed 33 • Management mandated the DSS 22 • Timely information is provided 17 • Cost reduction is achieved 6 Another reason is the end-user computing movement. End-user are not programmers, so they require easy-to-use construction tools and procedures. These are provided by DSS

  26. Slide 1 - 22 1.5 The Concept of Decision Support Systems • Benefits and Limitations of DSS use • Benefits: Extend the decision maker’s ability to process information and knowledge Extend the decision maker’s ability to tackle large-scale, time-consuming, complex problems Shorten the time associated with making a decision Improve the reliability of a decision process or outcome Encourage exploration and discovery on the part of the decision maker. Reveal new approaches to thinking about a problem space or decision context Generate new evidence in support of a decision or confirmation of existing assumption

  27. Slide 1 - 23 1.5 The Concept of Decision Support Systems Create a strategic or competitive advantage over competing organization. • Limitations: DSSs cannot yet be designed to contain distinctly human decision-making talent such as creativity, imaginativeness,or intuition The power of a DSS is limited by the computer system upon which it is running, its design, and the knowledge it processes at the time of its use Language and command interfaces are not yet sophisticated enough to allow for natural language processing of user directives and inquiries DSSs are normally designed to be narrow in scope of application, thus inhibiting their generalizability to multiple decision-making contexts.

  28. Slide 1 - 24 1.6 Group Decision Support Systems • Many major decisions in an organization are made by groups. Getting a group together in one place and at one time can be difficult and expensive. Furthermore, traditional group meetings can take a long time and the resulting decisions may be mediocre. • Attempts to improve the work of groups with the aid of information technology appear under several names, such as groupware, electronic meeting systems, collaborative systems, and group decision support systems. Of special interest in this course is the area of Group DSS (GDSS).

  29. Slide 1 - 24 1.7 Knowledge Management Systems • Knowledge that is organized and stored in a repository for use by an organization • Can be used to solve similar or identical problems in the future • ROIs as high as a factor of 25 within one to two years • Will talk it in detail.

  30. Slide 1 - 24 1.8 Executive Information System (EIS) • Provide an organization view of operations • Serve the information needs of executives and other managers • Provide an extremely user-friendly interface that meets individual decision styles • Provide timely and effective tracking and control • Provide quick access to detailed information behind text, numbers, or graphics • Filter, compress, and track critical data and information • Identify problems (opportunities) EIS, starting in the mid-1980s in large corporations, has spread around the globe, has become affordable to smaller companies, and are serving many managers as enterprise-wide systems.

  31. Slide 1 - 25 1.9 Expert Systems • When an organization has a complex decision to make or problem to solve, it often turns to experts for advice. These experts have specific knowledge and experience in the problem area. They are aware of the alternatives , the chances of successes, and the benefits and costs the business may incur. Companies engages experts for advice on such matters as which equipment to buy, mergers and acquisitions, and advertising strategy. The more unstructured the situation, the more specialized ( and expensive) is the advice. Expert systems attempt to mimic human experts. • Typically, an expert systems (ES) is a decision-making or problem-solving computer package that can reach a level of performance comparable to –or even exceeding-that of a human expert in some specialized and usually narrow problem area.

  32. Slide 1 - 26 1.9 Expert Systems • The basic idea behind an ES, which is an applied artificial intelligence technology, is simple. Expertise is transferred from the expert to a computer. This knowledge is then stored in the computer and users call on the computer for specific advice as needed. The ES can make inferences and arrive at a specific conclusion. Then, like a human consultant, it advises the non-experts and explains, if necessary, the logic behind the advice. Expert systems are used today in thousands of organizations and they support many tasks. ES are often integrated with other information technology (IT).

  33. Slide 1 - 27 1.10 Artificial Neural Networks • The application of the previous technologies was based on the use of explicit data, information, or knowledge, which was stored in a computer and manipulated as needed. However, in the complex real world we may not have explicit data, information and knowledge. Thus, people must make decisions that are based on partial, incomplete,or inexact information. Such conditions are created, for example, in rapidly changing environments. Decision makers use their experiences to handle these situations; that is they recall experience and learn from their experiences what to do with new similar situation for which exact replicas are unavailable. • In all the previous technologies there was no element of learning by the computer. A technology that attempts to close this gap is called neural computing, or artificial neural networks.

  34. Slide 1 - 28 1.11 Hybrid Support System • The objective of a computer-based information system (CBIS), regardless of its name or nature, is to assist management in solving managerial or organizational problems faster and better than what can be done without computers. To attain this objective, they may use one or more information technologies. The benefits of integrating the technologies were investigated as 1.5 section. DSS emphasizes the use of technologies whose prime objective is successfully supporting problem solving and decision making.

  35. Slide 1 - 29 1.12 The Evolution of CBIS • The evolutionary view of CBIS has a strong logical basis. First, there is a clear-cut sequence through time: • Mid-1950s, Transaction processing systems (TPS), • 1960s, MIS, • 1970s, Office Automation systems, • 1970s-1980s, DSS, • 1980s, Commercial applications of ES and EIS, • 1990s, GDSS, Neural Computing, Hybrid Integrated computer systems, and • 2000s, E-DSS times.

  36. Slide 1 - 30 1.12 The Evolution of CBIS • The evolutionary view of CBIS has a strong logical basis. The relationships among these and other technologies can be summarized as follows. • Each Tech. Can be viewed as a unique class of IT • The Tech. Are integrated, and each supports some aspects of managerial decision making • The evolution and creation of the newer tools help expand the role of IT for the betterment of management in organization • The interrelationship and coordination among these tools is still evolving. (table 1.1 in Leung (2002))

  37. Slide 1 - 30 1.12 The Evolution of CBIS GDSS Behavior Or. Behav. Keen and Scott Morton (78) Scott Morton (71) EI EIS MIS Sprague (82) Focus MS Bonzek, et al. (81) Database Machine Learning ES Technology AI Networking 1970s 1980s 1990s 2000s Concepts Tech. Devel. Sys. Integra.

  38. Slide 1 - 30 1.13 The Future of DSS • MSS is becoming a Web-based technology • Combining and integration with business intelligence • BI is being combined with a number of Web-based applications • Intelligent systems are being employed in the war against terrorism • Web-based advisory services are being developed • More complex MSS applications are being developed • Trend toward increasing intelligence of systems • Pervasive computing • MSS are being disseminated via ASPs • Natural language based search engines • Semantic web

  39. Slide 1 - 30 1.13 The Future of DSS • Voice technologies are being enriched through use of MSS • CRM improvement • Improvement along supply chain through integration with ERP • Expertise availability on Internet • Initiation of formal knowledge-management programs • More intelligent agents on Internet and other networks • Greater use of wireless technologies • Intelligent agents will roam the Internet, intranets, and extranets to monitor information and assist in decision-making • Increase in groupware technologies for collaboration and communication • DSS for e-commerce • Decision-support tools for e-commerce will be expanded

  40. Slide 1 - 31 Exercise • Individual (above 1,000 Chinese Words). • Write a report by searching the Internet for material regarding the work of managers, the need for computerized support, and the role decision support systems play in providing such support use. (use,, www). How many references to consulting firms, academic departments, and programs did you find? What major areas are represented? Pick five references in one area and report your findings.