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MIS 301 Information Systems in Organizations Dave Salisbury [email protected] (email) http://www.davesalisbury.com/ (web site) Why We Invest in IS&T Revenue + Strategic Systems + Management Support & Decision Systems IS&T Investment – Operational Systems Profit – Costs Decisions in Business Decision Characteristics Unstructured Semi-structured Strategic Management Tactical Management Structured Operational Management Ad Hoc Unscheduled Summarized Infrequent Forward Looking External Broad Scope Prespecified Scheduled Detailed Frequent Historical Internal Narrow Focus Short Time Frame Management Reports Periodic Scheduled Reports Exception Reports Major Management Information Systems Reports Demand Reports and Responses Push Reports Management Roles Interpersonal - figurehead, leader, liaison Informational - monitor, disseminator, spokesperson Decisional - entrepreneur, problem solver, resource coordinator, and negotiator Simon & the Rational Person Humans can be rational actors, their rationality is bounded by their limitations Humans tend to satisfice, or settle on the first acceptable option, rather optimizing Information stored in computers can increase human rationality if accessible when needed The central problem is not how to organize to produce efficiently, but how to organize to make decisions (i.e. process information) IT Provides Assistance to... Communicate and/or distribute knowledge Collaborate with other workers Routinize procedures Capture and codify knowledge Create knowledge Two Key Issues Uncertainty Lack of information Ambiguity Lack of structure Data, Information, Knowledge Data are a collection of: Information is organized or processed data that are: Facts Measurements Statistics Timely Accurate Knowledge is information that is: Contextual Relevant Actionable Knowledge Types Explicit Knowledge Facts, figures Easily codified Easily transmitted People to Documents Learn by studying Codify in programs and systems Tacit Knowledge Experiences Not easily codified Hard to transmit People to People Learn by doing Share by networking holders of the knowledge Knowledge Management Structuring of knowledge enables Knowledge management initiatives focus on effective and efficient problem solving dynamic learning strategic planning decision making. identifying knowledge how it can be shared in a formal manner leveraging its value through reuse. Knowledge management can promote organizational learning help solve problems Knowledge Management Systems Communication technologies allow users to access needed knowledge and to communicate with each other. Collaboration technologies provide the means to perform group work. Storage and retrieval technologies (database management systems) to store and manage knowledge. Knowledge & IT Codify knowledge for transfer Easily reusable People to documents Individual-level standardization a.k.a process in your book Knowledge & IT Create networks among expert knowledge holders Knowledge lies in experts, not easily reusable Person to person Individual-level uniqueness and innovation a.k.a practice in your book Knowledge Management Systems IT that helps gather, organize, and share business knowledge within an organization Hypermedia databases that store and disseminate business knowledge. May also be called knowledge bases Best practices, policies, business solutions Entered through the enterprise knowledge portal Enterprise Information Portals & DSS Internet Extranet Intranet Enterprise Information Portal Gateway Enterprise Information Portal User Interface Search Agents Data Mining OLAP DSS What-If Models Sensitivity Models Goal-Seeking Models Optimization Models Knowledge Management Database Management Functions Data Mart Operational Database Other Business Applications Analytical Database Knowledge Base Online Analytical Processing Enables interactive examination/manipulation of detailed & consolidated data from many perspectives Consolidation The aggregation of data. From simple roll-ups to complex groupings of interrelated data Drill-Down Analyze complex relationships to discover patterns, trends, and exception conditions in real time Display detail data that comprise consolidated data Slicing and Dicing The ability to look at the database from different viewpoints. When performed along a time axis, helps analyze trends and find patterns Decision Support Systems What If-Analysis Sensitivity Analysis Important Decision Support Systems Analytical Models Goal-Seeking Analysis Optimization Analysis Data Mining for Decision Support Software analyzes vast amounts of data Attempts to discover patterns, trends, & correlations May perform regression, decision tree, neural network, cluster detection, or market basket analysis Management Support Systems Decision Support Systems (DSS) provide support primarily to analytical, quantitative types of decisions. Executive (Enterprise) Support Systems (ESS) support the informational roles of executives. Group Decision Support Systems supports managers and staff working in groups. Intelligent Systems Decision Process Define the Process or Problem Intelligence phase Develop Modeling Alternative Courses of Action Select The “Best” One phase Choice phase Review It Act on it Implementation phase Models as decision making aids A model (in decision making) is a simplified representation of reality. The benefits of modeling in decision making are: Cost of virtual experimentation is much lower Simulated compression of time. Manipulating the model is much easier The cost of mistakes are much lower Modeling for “what-ifs” Analysis and comparison of a large number alternatives Models enhance and reinforce learning Group Decision Support Systems Decision making is frequently a shared process involving groups using group decision support systems (GDSS). Groups Co-located Dispersed Process structuring Problem structuring Executive Information & Support Systems Serves top management Original intent – provide executives with immediate, information about the firm “critical success factors” Features of an EIS Information presented in forms tailored to the preferences of the users Most stress use of graphical user interface and graphics displays May also include exception reporting and trend analysis Very user friendly Supported by graphics Provide drill down (investigating information in increasing detail). ESS goes beyond EIS to include: Analysis support Communications Office automation Intelligence support Artificial Intelligence Artificial Intelligence Cognitive Science Applications •Expert Systems •Fuzzy Logic •Genetic Algorithms •Neural Networks Robotics Applications Natural Interface Applications •Visual Perceptions •Locomotion •Navigation •Tactility •Natural Language •Speech Recognition •Multisensory Interface •Virtual Reality AI Application Areas in Business Neural Networks Fuzzy Logic Systems Genetic Algorithms Virtual Reality AI Application Areas in Business Intelligent Agents Expert Systems Intelligent Agents Interface Tutors Presentation Agents Search Agents User Interface Agents Information Management Agents Information Brokers Network Navigation Agents RolePlaying Agents Information Filters Expert Systems The Expert System Expert Advice User User Interface Programs Inference Engine Program Knowledge Base Workstation Expert System Development Knowledge Engineering Knowledge Acquisition Program Workstation Expert and/or Knowledge Engineer Expert System Applications Decision Management Diagnostic/Troubleshooting Maintenance/Scheduling Design/Configuration Major Application Categories of Expert Systems Selection/Classification Process Monitoring/Control