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DECISION SUPPORT SYSTEMS Lecture Notes Dr. Ir. Sudaryanto, MSc. sudaryanto@staff.gunadarma.ac.id sudaryanto.tugas@yahoo.com Gunadarma University. THE COCEPTUAL FOUNDATION FOR DECISION SUPPORT SYSTEMS Part 1 DSS: Past, Present, Future Dr. Ir. Sudaryanto, MSc.
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DECISION SUPPORT SYSTEMS Lecture Notes Dr. Ir. Sudaryanto, MSc. sudaryanto@staff.gunadarma.ac.id sudaryanto.tugas@yahoo.com Gunadarma University
THE COCEPTUAL FOUNDATION FOR DECISION SUPPORT SYSTEMS Part 1 DSS: Past, Present, Future Dr. Ir. Sudaryanto, MSc. sudaryanto@staff.gunadarma.ac.id Ir. (IPB), MSc (AIT-Thailand), Dr. rer.pol. (Aachen-Germany)
The Background Shorter PLC Global Competition Speed of decision DSS Competitive Intelligence Complexity
Introduction • Evolution of Computer based application • 1st generation • Mainframe computers for transaction processing • 2nd generation • MIS :management reporting • 3rd generation: DSS • To help management to deal with semi structure • and unstructure decision making • Full development during 1970s and 1980s
Management Information Systems Schedule reports for well define Information needs MIS Demand reports for ad hoc Information request The ability to query a database for specific data The ultimate mission of information systems: To improve the performance of information workers in organization through the application of information technology
DSS : The definition • Sprague, 1980: • Computer based systems • Help the decision maker • Confront ill-structure problems • Through direct interaction • With data and analysis model • Scenario of problem solving using DSS
Dichotomy of Information Work Procedure -based Goal -based • High volume of transaction • Low cost/value per transaction • Well structure procedures • Output measures defined • Focus on process • Focus on efficiency • Handling of data • Predominantly clerical workers • Example: back office, payroll • processing • Low volume of transaction • High value (cost) per transaction • ill structure procedures • Output measures less defined • Focus on problems and goals • Focus on effectiveness • Handling of concepts • Managers and profesionals • Example: loan department, planning • department
The Data processing Evolution • Stand alone EDP jobs • Transaction processing • Each program has its own files • Data handling : sorting, classifying, summarizing Basic data processing • Integrated EDP jobs for related function • Sharing files across several program • Develop software for handling files File management DPEV • Software system for dealing with data separate from • Program • MIS capability • Reduction of program maintenance Data base management • Addition of flexible report generator and query • Language Query, Report generation
Principles of DSS • Conceptualization of DSS: DDM paradigm • Three Components/ Sub system • Dialog between the system and the user • Data that support the system • Model to provide analysis capabilities • New technology continues to affect the dialog, • data and models
The Components of a DSS Model Base Data Base ___________ Strategic Models ___________ Tactical Models ___________ Operational Models ___________ Model Buildings Blocks and Subroutines ___________ Finance ___________ Production ___________ Marketing ___________ Personnel ______________ R&D ______________ Other ______________ Other internal data Data Base Management System Model Base Management System Dialog Base Management System Document based data TransactionData External data User
The Dialog Component • What the user knows about • the decision • how to use the DSS • How to train user ? • one to one tutorial • classes /lectures • programmed an computer • aided instruction • command or sequence files • instructions manual - online, • context specific Knowledge base Action language DSS Presentation language
The Dialog Component • How to control DSS • question - answer • menu - driven / oriented • command language • input-output approach • visual oriented interface - icon • voice input • Physical action • Keyboard input • touchscreen, mouse driven Knowledge base Action language DSS Presentation language
The Dialog Component Knowledge base • Printed report • Text • Graphics • Animation • Voice output Action language DSS Presentation language
Dialog Styles Combination or set of option for implementing the knowledge base, the action language and the presentation language Mouse Pull - down menu move icons Graphical presentation
The Data Component • Internal (within organization) • easy to generate and manage • External • popular as “public data base” • In context of DSS :as information source • documents, concept, ideas, opinions Data source Internal External Public Data Base __________________ Socio-economic data Traditional EDP/MIS __________________ Data records, files Record base Corporate Library Word processing records management ____________________ records, opinions, memos, estimate Document base
The Organizational option Traditional application development group Operation research/management Science group DSS Institutional Support Planing department / Staff analysis group within a functional department A stand alone, formally chartered DSS group A DSS group within end user services Information center • Institutional support play a leading role in development and management of DSS system • Support characteristics: • Staff background • Types of services • DSS development methodology
Development of DSS • Affecting factors • PC revolution • Increasing capability and reducing cost • of telecomunication • Increasing availability of public data • Growth of artificial intelligent techniques • Increasing knowledge and computer literacy • Availability of hardware and software • Incereasing availability of mobile computing • and communication
The Challenges • Integrated architecture • Connectivity • LAN • WAN • Document data • More intelligence
DSS Levels • Specific DSS – Developed for supporting one particular type of decision. • DSS Generators – Programs which decision makers and programmers can use to quickly build a specific DSS application. – Spreadsheets, IFPS, @RISK, etc. • DSS Tools – Languages, development tools, text editors, etc., which require more technical sophistication before they can become specific DSS.
DSS Types • Permanent / Institutional DSS – Developed for an on-going decision situation. May be refined or updated as needed. – For repetitive use (operation) • Ad-Hoc DSS – Built for one specific decision requiring immediate support. Often rapidly assembled using DSS generators & tools. May eventually result in permanent DSS. – usually for strategic planning
DSS Benefits – Augment decision maker’s knowledge management abilities – Allow decision maker to solve larger and more complex problems – Make decision making faster and more reliable – Stimulate decision maker’s thoughts about a problem & reveal new ways of thinking – Support decision maker’s decision/position with computational evidence – Organizational competitive advantage
DSS Limitations – DSS do not replace human creativity and experience – DSS is constrained by the knowledge in its databases – DSS is constrained by the models and processes in its model base and programming – DSS is limited by its computer platform – Decision makers are required to communicate with the DSS in its language or interface mode – DSS are often narrow in their area of application