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WHAT IS A DSS ?

WHAT IS A DSS ?. Gorry and Scott-Morton’s: “A model based set of procedures for processing data and judgment to assist a manager in his decision making.” According to them, to be successful, such system must be: - Simple - Robust - Easy to control - Adaptive

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WHAT IS A DSS ?

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  1. WHAT IS A DSS ? Gorry and Scott-Morton’s: “A model based set of procedures for processing data and judgment to assist a manager in his decision making.” According to them, to be successful, such system must be: - Simple - Robust - Easy to control - Adaptive - Complete on important issues - Easy to communicate with

  2. Implicit in the definition is the assumption that : - The system is computer-based. - The system serves as an extension of the user’s problem solving capabilities. Gorry and Scott-Morton’s definition was accepted throughout most of the 1970’s by practitioners and researchers.

  3. Several other definitions emerged from the literature : Alter (1980), Moore and Chang (1980), Bonczek, Holsapple, and Whinston (1980), Keen (1980) The tableau below provides a good summary of their various views: Source DSS defined in term of ________________________________________________________________________________________________________________________________________ Gorry and Scott-Morton Problem Type, System Function(support) Little System Function, Interface Characteristics Alter Usage Pattern, System Objectives Moore and Chang Usage Pattern, System Capabilities Bonczek et al System Component Keen Development Process

  4. Working definition of an ideal DSS: A DSS is an interactive, flexible, and adaptable CBIS that utilizes decision rules, models, and model base coupled with a comprehensive database and the decision maker own’s insights, leading to specific, implementable decisions in solving problems that would not be amenable to management science optimization models per se. Thus, a DSS supports complex decision making and increases its effectiveness.

  5. Type of Control

  6. Intelligence Phase Organizational Objectives Search and scanning procedures Data collection Problem Identification Problem classification Problem statement Examination Reality Design Phase Validation of the model Formulate a model Set criteria for choice Search for alternatives Predict and measure outcomes Success Verification, testing of proposed solution Choice Phase Solution to the model Sensitive analysis Selection of best alternative Plan for implementation Design of a control system Implementation of solution Failure

  7. Some Characteristics and Capabilities of DSS-I 1. DSS provides support for decision makers mainly in unstructured and semi structured situations. DSS is different from EDP, TP and MIS. 2. Support is provided for various managerial levels 3. Support is provided to individuals as well as groups - GDSS. 4. DSS provides support for interdependent as well as sequential decisions 5. DSS supports all phases of decision making process : Intelligence design, choice and implementation 6. Support is provided for a variety of decision problems. 7. DSS must be adaptive over time

  8. Some Characteristics and Capabilities of DSS - Contd. 8. DSS should be easy to use. 9. DSS improves the effectiveness of decision making (accuracy, timeliness and quality) rather than efficiency (computer time close form solution). 10. Decision maker has complete control over all steps of the decision making process in solving the problems. 11. DSS leads to learning. 12. Should be easy to construct (?) Should be easy to alter by its users.

  9. Box 3.2: The Major Benefits of DSS 1. Ability to support the solution of complex problems. 2. Fast response to unexpected situations that result in changed conditions. A DSS enables a thorough, quantitative analysis in a very short time. Even frequent changes in a scenario can be evaluated objectively in a timely manner. 3. Ability to try several different strategies under different configurations, quickly and objectively. 4. New insights and learning. The user can be exposed to new insights through the composition of the model and an extensive sensitivity “what if” analysis. The new insights can help in training inexperienced managers and other employees as well. 5. Facilitated communication. Data collection and model construction experimentations are being executed with active users’ participation, thus greatly facilitating communication among mangers. The decision process can make employees more supportive of organizational decisions. The “what-if” analysis can be used to satisfy skeptics, in turn improving teamwork.

  10. Box 3.2: The Major Benefits of DSS-continued 6. Improved management control and performance. DSS can increase management control over expenditures and improve performance of the organization. 7. Cost savings. Routine applications of a DSS may result in considerable cost reduction, or in reducing (eliminating) the cost of wrong decisions. 8. Objective decisions. The decisions derived from DSS are more consistent and objective than decisions made intuitively. 9. Improving managerial effectiveness, allowing managers to perform a task in less time and/or with less effort. The DSS provides managers with more “quality” time for analysis, planning, and implementation.

  11. Support Provided by DSS DSS may provide several types of support. The following structure is based on Alter(1). Each level of support contains and adds on the previous level (but may also contribute to the previous level). DSS Answers to Provides Questions: Raw data and status access What is . . . . . . ?  General analysis capabilities What is / Why . . . . .?  Representation models (financial What will be . . . . . .? statements). Casual models (forecasting diagnosis). What will be / Why . . . ?  Solution suggestions, evaluation What if . . . . . . . ?  Solution selection What is best / What is good enough . . . . . . ?

  12. 1 2 Semi structured decisions 14 For managers at different levels Knowledge 13 3 Modeling For groups and individuals 12 4 Ease of construction Interdependent or sequential decisions DSS 11 5 5 Evolutionary usage Support, intelligence, design, choice 6 10 Humans control the machine Support variety of decision styles and processes 7 9 Effectiveness , not efficiency Adaptability and Flexibility 8 Ease of Use

  13. Components of DSS 1. Data includes database(s) which contains all the relevant data for the problem and is managed by software called database management system. 2. Model Management The software package that includes financial statistical, management science, other quantitative models that provide the system analytical capabilities, and an appropriate software management. 3. Communication(Dialog) Subsystem The subsystem through which the user can communicate with and command DSS These components contribute the software portion of the DSS. Also the manager(or user) is considered a part of the problem solving system.

  14. Conceptual Model of DSS Other computer - based systems Data: external and internal Data Management Model Management Knowledge manager Dialog management Manager (user) and tasks

  15. The Capabilities of a DBMS in a DSS - Capture/extracts data for inclusion in a database - Quickly updates (adds, deletes, edits and changes) - Quickly retrieves data from database for queries and reports - Provides comprehensive data security ( protection from unauthorized access and recovery capability) - Handles personal and official data query - Performs complex retrieval and data manipulation tasks based on queries - Tracks usage of data

  16. The Data Management Subsystem - DSS database - Database management system - Data directory - Query facility

  17. Internal data sources External data sources Finance Marketing Production Personnel Other Private personal data Dialog Management Model Management Extraction Knowledge Management Query facility Decision support database • Database ManagementSystem • Retrieval • Inquiry • Update • Report generation • Delete Data directory

  18. On Data And Database System-I - Data external, internal and personal sources - External data are a available on thousands of online commercial databases, dictionaries, directories, reports, etc. - Data for DSS needs to be frequently in the field using one of the several methods - Data for DSS may have problems such as: incorrect data, non timely data poorly measured and indexed data, too many data or no data - Large online databases such as CompuServe and Dow Jones Information service can be a major source of DSS data. - DSS can be programmed with third-generation languages , but it is usually programmed with fourth-generation languages. - Fourth-generation system include many integrated features for data management - Data are organized either in a relational, hierarchical or network architecture. For many MSS relational type is preferable. -

  19. On Data And Database System - Contd. - SQL is a standard access to relational database - There is a trend to have DSS (and other MSS) distributed via networks - Distributed DSS provide the benefit of a PC and the power of a mainframe - Many DSS are being offered on client/server systems - Object-oriented databases are especially suitable for complex DSS such as those in computer integrated manufacturing - Object-oriented databases are easy to use and fast to access. They are especially useful in distributed DSS - Many companies are developing an enterprise-wide approach to data management. IBM’s Information Warehouse is an example

  20. The model management subsystem - Model base- Model base management system - Model execution , Integration and command The ability to invoke run, change, combine and inspect models is a key capability of DSS which differentiates it from other CBIS.

  21. The model base management system (MBMS) MBMS is a software system with the following functions : - Model creation - Using subroutines and other building block - Generation of new routines and reports - Model updating and changing - Data manipulation The MBMS is capable of interrelating models with appropriate linkages through a database.

  22. Models (Model Base) • Strategic, tactical, operational • Statistical, financial, marketing, management • science, accounting, engineering, etc. • Model building blocks Model Directory Model Base Management • Modeling commands : creation • Maintenance - update • Database interface • Modeling language Model execution, integration and command processor. Data Management Dialog Management Knowledge Management

  23. Examples of Components of Models

  24. The Model directory - It is similar to the role of database directory. - Contains the catalog of all models - Contains models definitions - Answers all questions about model’s capability and availability.

  25. The Interface (Dialog) subsystem The dialog component is the software and hardware that provides the user interface for DSS. - Deals with the human-machine interactions - Uses action language to allow communication between user(s) and machine. - Uses presentation language - with graphic screen display…etc. - Uses knowledge base including information that the user must know.

  26. Data Management and DBMS Knowledge Management Model Management and MBMS Dialog Generation and Management System-DGMS Natural Language Processor Input Output Terminal Action Display Languages Languages Printers, Plotters User

  27. Overall Capabilities • Create variety of DSS quickly and easily • Facilitate iterative design process General Capabilities Ease of use Access to a variety of Access to a variety of analysis For routine use, data source, types, and capabilities with some modification and formats for a variety of “suggestion” or guidance construction of DSS problems and contexts. available. Component Capabilities

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