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CHAPTER 3

CHAPTER 3. Decision Support Systems: An Overview. 3.1 DSS configurations.

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CHAPTER 3

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  1. CHAPTER 3 Decision Support Systems: An Overview

  2. 3.1 DSS configurations Strategic planning is one of the most important tasks ofmodern management. It involves all functional areas in an organization and several relevant outside factors, a fact that complicates the planning process, especially in dealing with long-rum uncertainties. Thus, strategic planning is clearly not a structured decision situation, so it is potential candidate for DSS application. The Gotass-Larsen Shipping Corp. (GLSC), subsidiary of International Utilities (IU), operates cargo ships all over the world. The company developed a comprehensive DSS for performing both short-and long-term planning. The system is composed of two major parts: data and models. The data include both external data (port or cannel characteristics, competitor’s activities, and fares) and All Right Reserved, Yao Zhong, School of E&M, BUAA

  3. 3.1 DSS configurations internal data (existing plans, availability of resources, and individual ship’s characteristics). In addition, users can incorporate their own data or express their attitudes (for example, by adding their own risk assessments). The models include routine standard accounting and financial analysis model (such as cash flow computations and pro forma income and expenses) organized on a per ship, per voyage, per division, and company-wide basis. These models permit elaborate financial analyses. A simulation model is used to analyze short- and long-term plans and to evaluate the desirability of projects. In addition, the system interfaces with a commercially available application program for analyzing individual voyages. All Right Reserved, Yao Zhong, School of E&M, BUAA

  4. 3.1 DSS configurations A highly decentralized 15 month operational planning and control document is prepared within the framework of the long-term strategic plan. This document is used as the basis for detailed goal formation for the various ships and individual voyages. A detailed monitoring and control mechanism is also provided, including a regular variance report and diagnostic analysis. In addition, a detailed performance tracking report is executed (by voyage, ship, division, and entire corporation). Once the assessment of the opportunity of individual projects (such as contracting a specific voyage) is examined, an aggregation is performed. The objective is to determine whether a series of individually profitable project All Right Reserved, Yao Zhong, School of E&M, BUAA

  5. 3.1 DSS configurations Adds to feasible and effective long-range plan. The DSS uses a simulation model that examines various configurations of projects in an attempt to fine-tune the aggregate plan. Specifically, when several projects are selected, resources might be insufficient for all projects. Therefore, modifications in scheduling and financial arrangements might be necessary. This fine-tuning provides a trial-and-error approach to feasibility testing and sensitivity analyses. The what-if capabilities of the DSS are especially important in this case because a trial-and-error approach to managing the organization would be disastrous. The strategic plan of GLSC is very detailed and accurate because of the contractual nature of the sales and some of the expenses. The model is geared to a traditional business policy structure, which helps in assessing the threats and risks in All Right Reserved, Yao Zhong, School of E&M, BUAA

  6. 3.1 DSS configurations The general operating environment and makes possible an examination of the impacts of new opportunity on existing plans. This is an example of large-scale, strategic DSS. We refer to this vignette throughout this chapter. All Right Reserved, Yao Zhong, School of E&M, BUAA

  7. 3.1 DSS configurations • Supports individuals and teams • Used repeatedly and constantly • Two major components: data and models • It supports several interrelated decisions • Web-based • It uses both internal and external data • Uses subjective, personal, and objective data • Has a simulation model • Used in public and private sectors • Has what-if capabilities • Uses quantitative and qualitative models All Right Reserved, Yao Zhong, School of E&M, BUAA

  8. 3.1 DSS configurations This vignette demonstrates some of the potential diversification of DSS. Decision support can be provided in many different configurations. These configurations depend on the nature of the management decision situation and the specific technologies used for support. These technologies are assembled from four basic components (each with several variations): data, models, knowledge, and user interface. Each of these components is managed by software that either is commercially available or must be programmed for the specific task. The manner in which these components are assembled defines their major capabilities and the nature of the support provided. For example, models are emphasized in a model-oriented DSS, as in the opening vignette. Such models can be customized with a modeling language (such as spreadsheet) or can be provided by standard algorithm-based tools such as linear All Right Reserved, Yao Zhong, School of E&M, BUAA

  9. 3.2 What is a DSS programming. Similarly, in a data-oriented DSS, a database (or data warehouse) and its management play the major role. • DSS definitions We have defined the DSS in chapter 1 like this: 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 semistructured problems (Keen and Morton,1987). Why do we redefine it in this chapter? All Right Reserved, Yao Zhong, School of E&M, BUAA

  10. 3.2 What is a DSS Why do we redefine it in this chapter? Keen and Morton’s definition is identified as a system intended to support managerial decision makers in semistructured decision situations. DSS were meant to be an adjunct to decision makers, to extend their capabilities but not to replace their judgment. It is a computer-based system. Several other definitions appeared that caused considerable disagreement as to what really is a DSS. All Right Reserved, Yao Zhong, School of E&M, BUAA

  11. 3.2 What is a DSS • Little (1970) “model-based set of procedures for processing data and judgments to assist a manager in his decision making” Assumption: that the system is computer-based and extends the user’s problem-solving capabilities. • Alter (1980) Contrasts DSS with traditional EDP(electronic data processing) systems (Table 3.1) All Right Reserved, Yao Zhong, School of E&M, BUAA

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  13. 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 • Bonczek et al. (1980)A computer-based system consisting of 1. A language system -- communication between the user and DSS components 2. A knowledge system 3. A problem-processing system--the link between the other two components All Right Reserved, Yao Zhong, School of E&M, BUAA

  14. Keen (1980) DSS apply “to situations where a ‘final’ system can be developed only through an adaptive process of learning and evolution” • Central Issue in DSSsupport and improvement of decision making These definitions are compared and contrasted by examining the various concepts used to define DSS. All Right Reserved, Yao Zhong, School of E&M, BUAA

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  16. 3.2 What is a DSS • Working Definition of DSS • A DSS is an interactive, flexible, and adaptable CBIS, specially developed for supporting the solution of a non-structured management problem for improved decision making. It utilizes data, it provides easy user interface, and it allows for the decision maker’s own insights • DSS may utilize models, is built by an interactive process (frequently by end-users), supports all the phases of the decision making, and may include a knowledge component All Right Reserved, Yao Zhong, School of E&M, BUAA

  17. 3.3 Characteristics and Capabilities of DSS 1. Provide support in semi-structured and unstructured situations, includes human judgment and computerized information 2. Support for various managerial levels (top to line manager) 3. Support to individuals and groups 4. Support to interdependent and/or sequential decisions 5. Support all phases of the decision-making process 6. Support a variety of decision-making processes and styles (more) All Right Reserved, Yao Zhong, School of E&M, BUAA

  18. 7. Are adaptive 8. Have user friendly interfaces 9. Goal: improve effectiveness of decision making 10. The decision maker controls the decision-making process 11. End-users can build simple systems 12. Utilizes models for analysis 13. Provides access to a variety of data sources, formats, and types, ranging from geographic information systems to object-oriented ones.Decision makers can make better, more consistent decisions in a timely manner. All Right Reserved, Yao Zhong, School of E&M, BUAA

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  20. 3.4 DSS Components 1. Data Management Subsystem Includes the database, which contains relevant data for the situation and is managed by software called DBMS. 2. Model Management Subsystem A software package that includes financial, statistical, management science, or other quantitative models that provides the system’s analytical capabilities and appropriate software management. Modeling language for building custom models are also included. This is often called a MBMS. All Right Reserved, Yao Zhong, School of E&M, BUAA

  21. 3.4 DSS Components 3. Knowledge-based (Management) Subsystem This subsystem can support any of the other subsystems or act as an independent component. It provides intelligence to augment the decision maker’s own. 4. User Interface Subsystem The user communicates with and commands the DSS through this subsystem. 5. The User is considered to be part of system. Researchers assert that some of the unique contributions of DSS are derived from the intensive interaction between the computer and the decision makers. All Right Reserved, Yao Zhong, School of E&M, BUAA

  22. Other Computer-based systems Data: external and internal Data Management Model Management Knowledge Management User Interface Manager (user) All Right Reserved, Yao Zhong, School of E&M, BUAA

  23. 3.5 The Data Management Subsystem • DSS database A database is a collection of interrelated data organized to meet the need and structure of an organization and can be used by more than one person for more than one application. There are several possible configurations for a database. For lager DSS, the database is basically included in the data warehouse (next chapter). For some applications, a special database is constructed as needed. Several databases may be used in one DSS application, depending on the data sources. Data is extracted from internal and external data sources, as well as personal data belonging to one or more users. (Figure 3.3) All Right Reserved, Yao Zhong, School of E&M, BUAA

  24. Internal Data Source External Data Source Finance Marketing Production Personnel Other Organizational knowledge base Extraction Private, personal data Query Facility Decision Support database or data warehouse Corporate data Warehouse • DBMS • Retrieval • Inquiry • Update • Report • Delete Interface Management Model Management Data Directory Knowledge Management All Right Reserved, Yao Zhong, School of E&M, BUAA

  25. Internal Data Source External Data Source Finance Marketing Production Personnel Other Organizational knowledge base Extraction Private, personal data Query Facility Decision Support database or data warehouse Corporate data Warehouse • DBMS • Retrieval • Inquiry • Update • Report • Delete Interface Management Model Management Data Directory Knowledge Management All Right Reserved, Yao Zhong, School of E&M, BUAA

  26. 3.5 The Data Management Subsystem Internal data come mainly from the organization’s transaction processing system. Example are payroll monthly. Other internal data are machine maintenance scheduling, forecasts of future sales, cost of out-of-stock items, and future hiring plans. Some times internal data are made available through Web browser over an Internet, an internal Web-based system. External data may include industry data, marketing research data, census data, regional employment data, government regulations, tax rate schedules, or national economic data. Internet also is an important data sources. Private data may include guidelines used by specific decision makers and assessment of specific data or situations. All Right Reserved, Yao Zhong, School of E&M, BUAA

  27. 3.5 The Data Management Subsystem Data Organization Should a DSS have an independent database? It depends. In small ad hoc DSS, data can be entered directly into models sometimes extracted directly from larger database. The organization’s data warehouse is often used for building DSS applications. Some large DSS have their own fully integrated, multiple-source DSS databases. A separate DSS database need not be physically separate from the corporate database. They can be physically stored together for economic reasons. A DSS database can also share a DBMS with other systems. A DSS database may include multimedia objects (such as pictures, maps, or sounds). An object-oriented database is found in some recent DSS. All Right Reserved, Yao Zhong, School of E&M, BUAA

  28. 3.5 The Data Management Subsystem Extraction To create a DSS database, or a data warehouse, it is often necessary to capture data from several sources. This operation is called extraction. It is basically the importing of files, summarization, filtration, and condensation of data. Extraction also occurs when the user produces reports from the data in the DSS database. The extraction process is managed by a DBMS. All Right Reserved, Yao Zhong, School of E&M, BUAA

  29. 3.5 The Data Management Subsystem • Database management system The data base is created, accessed, and updated by a DBMS. Most DSS are built with a standard commercial DBMS that provides capabilities such as those shown in the following list: • Captures/extracts data for inclusion in a DSS database • Updates (adds, deletes, edits, changes) data records and files • Interrelates data from different sources All Right Reserved, Yao Zhong, School of E&M, BUAA

  30. 3.5 The Data Management Subsystem • Retrieves data from the database for queries and reports • Provides comprehensive data security (protection from unauthorized access, recovery capabilities, etc.) • Handles personal and unofficial data so that users can experiment with alternative solutions based on their own judgment • Performs complex data manipulation tasks based on queries • Tracks data use within the DSS • Manages data through a data dictionary All Right Reserved, Yao Zhong, School of E&M, BUAA

  31. 3.5 The Data Management Subsystem • Data directory Data directory is a catalog of all the data in the database. It contains the data definitions, and its main function is to answer questions about the availability of data items, their source, and their exact meaning. The directory especially appropriate for supporting the intelligence phase of the decision-making process by helping scan data and identify problem areas or opportunities. The directory, like any other catalog, supports the addition of new entries, deletion of entries, and retrieval of information on specific object. • Query facility In building and using DSS, it is often necessary to access, manipulate, and query the data. The Query facility performs all these tasks. It accepts requests for data from other DSS All Right Reserved, Yao Zhong, School of E&M, BUAA

  32. 3.5 The Data Management Subsystem • Query facility components, determine how these requests can be filled, formulates the detailed requests, and returns the results to the issuer of the request. The query facility includes a special query language. Important functions of a DSS query system are the selection and manipulation operations. All Right Reserved, Yao Zhong, School of E&M, BUAA

  33. 3.5 The Data Management Subsystem • Data Management Issues • Data warehouse • Data mining • Special independent DSS databases • Extraction of data from internal, external, and private sources • Web browser data access • Web database servers • Multimedia databases • Special GSS databases (like Lotus Notes / Domino Server) • Online Analytical Processing (OLAP) • Object-oriented databases • Commercial database management systems (DBMS) All Right Reserved, Yao Zhong, School of E&M, BUAA

  34. 3.6 The Model Management Subsystem • Analog of the database management subsystem(Figure on next slide ) • Model base • Model base management system • Modeling language • Model directory • Model execution, integration, and command processor All Right Reserved, Yao Zhong, School of E&M, BUAA

  35. 3.6 The Model Management Subsystem • Models (Model Base) • Stratigic, tactical,operational • Statistical, Financial, marketing,MS, Accounting, engineering,etc. • Model building blocks Model Directory • Model Base Management • Modeling commands: creation • Maintenance:update • DB interface • Modeling language Model execution, Integration, and command processor Data Management Interface Management. Knowledge management All Right Reserved, Yao Zhong, School of E&M, BUAA

  36. 3.6 The Model Management Subsystem • Model Base A model base contains routine and special statistical, financial, forecasting, management science, and other quantitative models that provide the analysis capabilities in a DSS. The ability to invoke, run, change, combine, and inspect models is a key DSS capability that differentiates it from other CBIS. The models in the model base can be divided into four major categories: strategic, tactical, operational, and model-building blocks and routine. Strategic Models: are used to support top management’s strategic planning responsibilities. Potential applications include developing corporate objectives, planning for mergers and acquisitions, plant location selection,environmental impact analysis, and nonroutine capital budgeting. All Right Reserved, Yao Zhong, School of E&M, BUAA

  37. 3.6 The Model Management Subsystem Mostly external data are used. The GLSC opening vignette includes a long-range planning model. Tactical Models: are used mainly by middle management to assist in allocating and controlling the organization’s resources. Examples of tactical models include labor requirement planning, sales promotion planning, plant layout determination, and routine capital budgeting. Tactical models are usually applicable only to an organizational subsystem such as the accounting department. Their time horizon varies from 1 month to less than 2 years. Some external data are needed, but the greatest requirements are for internal data. The GLSC vignette includes some tactical models for its 15 months plan. All Right Reserved, Yao Zhong, School of E&M, BUAA

  38. 3.6 The Model Management Subsystem Operational Models: are used to support the day-to-day working activities of the organization. Typical decisions are approving personal loans by a bank, production scheduling, inventory control, maintenance planning and scheduling, and quality control. Operational models support mainly manager’s decision making with a daily to monthly time horizon. These models normally use internal data. The models in the model base can also be classified by functional areas ( such as financial models or production control models) or by discipline (such as statistical model, or management science allocation models). The number of models in a DSS can vary from a few to several hundred. All Right Reserved, Yao Zhong, School of E&M, BUAA

  39. 3.6 The Model Management Subsystem • Modeling Language Because DSS deal with semistructured or unstructured problems, it is often necessary to customize models. This can be done with high-level languages. Some examples of these are COBOL, with a spreadsheet or with other fourth-generation languages, and special modeling language such as IFPS/Plus. The Model Base Management System (MBMS) The functions of the model base management system (MBMS) software are model creation using subroutine and other building blocks, generation of new routine and reports, model updating and changing, and model datamanipulation. The MBMS is capable of interrelating models with the appropriate linkages through a database. All Right Reserved, Yao Zhong, School of E&M, BUAA

  40. 3.6 The Model Management Subsystem • Major Functions of the MBMS • Creates models easily and quickly, either from scratch or from existing models or from the building blocks • Allows users to manipulate the models so they can conduct experiments and sensitivity analysis ranging from what-if to goal seeking. • Stores, retrieves, and manages a wide variety of different types of models in a logical and integrated manner • Accesses and integrates the model building blocks • Catalogs and displays the directory of models for use by several individuals in the organization • Tracks model data and application use • Interrelates models with appropriate linkages with the database and integrates them within the DSS All Right Reserved, Yao Zhong, School of E&M, BUAA

  41. 3.6 The Model Management Subsystem • Major Functions of the MBMS • Manages and maintains the model base with management functions analogous to database management: store, access, run, update link ,catalog, and query • Uses multiple models to support problem solving • The Model Directory The role of the model directory is similar to that of a database directory. It is a catalog of all the models and other software in the model base. It contains the model definitions, and its main function is to answer questions about the availability and capability of the models. All Right Reserved, Yao Zhong, School of E&M, BUAA

  42. 3.6 The Model Management Subsystem • Model Execution, Integration, and Command The following activities are usually controlled by model management: • Model execution is the process of controlling the actual running of the model. • Model integration means combining the operations of several models when needed (such as directing the output of one model to be processed by another one). • A model command processor is used to accept and interpret modeling instructions from the dialog component and to rout them to the MBMS, the model execution, or the integration functions. All Right Reserved, Yao Zhong, School of E&M, BUAA

  43. 3.6 The Model Management Subsystem • Model Management Issues • Model level: Strategic, managerial (tactical), and operational • Modeling languages • Lack of standard MBMS activities. WHY? • Use of AI and fuzzy logic in MBMS All Right Reserved, Yao Zhong, School of E&M, BUAA

  44. 3.7 The Knowledge Based (Management) Subsystem • Provides expertise in solving complex unstructured and semi-structured problems • Expertise provided by an expert system or other intelligent system • Advanced DSS have a knowledge based (management) component that can provide the required expertise for solving some aspects of problem and providing knowledge. • Silverman [1995] suggested that: • knowledge-based decision aids (support unaddressed problem with mathematics) • Intelligent decision modeling systems (build, apply and manage libraries of models) • Decision analytic expert systems (integrate theoretically rigorous methods of uncertainty into the expert system knowledge bases) All Right Reserved, Yao Zhong, School of E&M, BUAA

  45. 3.7 The Knowledge Based (Management) Subsystem • Knowledge-based DSS can be called intelligent DSS, or DSS/ES, expert support system, or simply knowledge-based DSS. • Data mining application can be one of them. Knowledge worker I –access services Authentication; Translation and transformation for diverse applications and appliances (e.g., browser, PIM, file system, PDA, mobile phone All Right Reserved, Yao Zhong, School of E&M, BUAA

  46. II – Personalization service Personalized knowledge portals; profiling; push-service; process-; project-; or role-oriented knowledge portals III – Knowledge service Collaboration Skill/expertise mgmt, community space, experience mgmt, awareness mgmt. Discovery Search, mining, knowledge maps, navigation, visualization Publication Formats, structuring, contextualization, workflow, o-authoring Learning Authoring, course mgmt, tutoring, learning paths, examinations IV –Integration service Taxonomy, knowledge structure, ontology; multi-dimensional metadata (tagging); directory services; synchronization services. V –Infrastructure service Intranet infrastructure service; groupware services; extract; transformation; loading; inspection service. All Right Reserved, Yao Zhong, School of E&M, BUAA

  47. (1) (2) (3) (4) (5) (6) VI- data and knowledge source (1) Intranet/extranet, Messages, contents of CMS, e-learning platforms (2) DMS documents, files from office information systems, (3) Data from RDMS, TPS, data warehouse, (4) Personal information management data (5) Content from Internet, WWW, newsgroups (6) Data from external online database All Right Reserved, Yao Zhong, School of E&M, BUAA

  48. 3.8 The User Interface (Dialog) Subsystem • Includes all communication between a user and the MSS • Graphical user interfaces (GUI) • Voice recognition and speech synthesis possible • To most users, the user interface is the system • Management of the User Interface Subsystem All Right Reserved, Yao Zhong, School of E&M, BUAA

  49. 3.8 The User Interface (Dialog) Subsystem • Management of the User Interface Subsystem This subsystem is managed by software called the user interface management system(UIMS) • UIMS capabilities: • Provides graphical user interface • Accommodates the user with a variety of input devices • Presents data with a variety of formats and output devices • Gives users help capabilities, prompting, diagnostic and suggestion routines, or any other flexible support • Provides interactions with the database and the model base • Stores input and output data All Right Reserved, Yao Zhong, School of E&M, BUAA

  50. 3.8 The User Interface (Dialog) Subsystem UIMS capabilities: • Provides color graphics, three-dimensional graphics, and data plotting • Has windows to allow multiple functions to be displayed concurrently • Can support communication among and between users and building of MSS • Provides training by example (guiding user through the input and modeling process) • Provides flexibility and adaptiveness so the MSS can accommodate different problems and technologies • Interacts in multiple, different dialog styles • Captures, stores, and analyzes dialog usage to improve the dialog system All Right Reserved, Yao Zhong, School of E&M, BUAA

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