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Pertemuan 16. Materi : Understanding Knowledge Management Concept and Application Buku Wajib & Sumber Materi : Turban, Efraim, R. Kelly Rainer and Richard E. Potter (2003). Introduction to Information Technology . Second Edition. John Wiley & Sons, Inc. Bab 11. DSS. Sensitivity Analysis
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Pertemuan 16 • Materi : • Understanding Knowledge Management Concept and Application • Buku Wajib & Sumber Materi : • Turban, Efraim, R. Kelly Rainer and Richard E. Potter (2003). Introduction to Information Technology. Second Edition. John Wiley & Sons, Inc.Bab 11
DSS • Sensitivity Analysis • the study of the effect that changes in one or more parts of a model have on other parts of the model • What-if Analysis • checks the impact of a change in the assumptions or other input data on the proposed solution • Goal-seeking Analysis • find the value of the inputs necessary to achieve a desired level of output
DSS • Components and Structure of DSS • Data Management • Includes the database(s) containing relevant data for the decision situation • User Interface • Enables the users to communicate with and command the DSS • Model Management • Includes software with financial, statistical, management science, or other quantitative models • Knowledge Management • Provides knowledge for solution of the problem; supports any of the other subsystems or act as an independent component
Enterprise Decision Support • Executive Information Systems • Meet information needs of executives • Very limited time • Need to monitor and identify problematic trends • Need external as well as internal information • Rapid access to data needed to executives • Very easy user interface • Highly graphical • Often connected with online information services • Incorporates email
Enterprise Decision Support • Executive Information Systems • Capabilities of EIS • Drill down • Critical success factors and key performance indicators • Status access • Trend analysis • Ad hoc analysis • Exception reporting • Intelligent EIS • Integration with DSS; web accessibility
Enterprise Decision Support • Group Decision Support Systems • Facilitate solution of semistructured and unstructured decisions by a group of decision makers • Help the group be productive by mitigating some negative group behaviors • Support the group’s process by encouraging idea generation, improving communication, and applying analytical tools as needed to the problem
Enterprise Decision Support • GDSS Implementations • Face-to-face meetings – special ‘decision room’ created with linked computers and GDSS software; use is facilitated by trained leader • Corporate ‘war room’– information displayed graphically and analyses conducted for all to see • Support for virtual teams – collaborative team tools for geographically dispersed teams; support discussion, calendars, polling, etc.
What can we do with the stored data? • Data mining – intelligent search of data stored in data marts or warehouses • Find predictive information • Discover unknown patterns • End users perform mining tasks with very powerful tools • Mining tools apply advanced computing techniques (learning, intelligence)
Data Mining and Analysis Concerns • Ethical Issues • Valuable data-mined information may violate individual privacy • Who is accountable for incorrect decisions that are based on DSS? • Human judgment is fallible • Job loss due to automated decision making? • Legal Issues • Discrimination based on data mining results • Data security from external snooping or sabotage • Data ownership of personal data
Data Visualization • Analyzed data can be even more useful if presented using Data Visualization techniques • Visual Interactive Modeling – graphic display of decision consequences • Visual Interactive Simulation – simulation model is animated and can be viewed and modified by decision maker • Geographic Information Systems – display data related to geographic location using digitized maps
What is Knowledge Management? • Key Concepts • Knowledge assets - regarding markets, products, technologies, and organizations that a business owns or needs to own • Best practices - collection of the most successful solutions and/or case studies • Intellectual capital - collection of knowledge amassed by an organization over the years • Knowledge system - collects knowledge, stores it in a database, maintains the database, and disseminates the knowledge to users • Competitive intelligence - collection of competitive information
IT Support for Knowledge Management • Knowledge identification – what is important? • Knowledge discovery and analysis – finding and organizing knowledge • Knowledge acquisition – going and getting needed knowledge by asking or promoting idea generation • Establishment of organizational knowledge bases – storing and organization corporate knowledge • Knowledge distribution and use – ensuring that those who need knowledge can access it
Implementing Knowledge Management • Reorganize as knowledge-based organizations • Created a new position, chief knowledge officer (CKO) • creating knowledge management infrastructure • building a knowledge culture • making it pay off • Facilitate organizational learning • learn from their experiences in order to survive
Promoting Idea Generation • Key source of knowledge is creative idea generation by individuals or groups • Software tools (GDSS) can promote productive idea generation for groups • Software tools also available for individuals to help stimulate creative production of ideas