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Chapter 9 Information systems for Managerial Decision Form of the Reports Line chart Bar chart Pie chart Image Management tasks Planning: goal seeking and strategy design Organisation: develop organisational structures Personnel: hiring , training , nominating Management: motivation and communication Guiding: evaluation of performance and draw conclusions Management roles The management has several roles to play: concerning persons manage contact person concerning information control distribute concerning decisions take problem solving distribution of the resources negotiate Management levels Strategic: strategic planning and management support for the direction committee Tactic: tactic planning and support of the departments by the middle management Operational: planning and support of the operations by the operations management O’Brien p. 352 Information Requirements Decision structure Unstructured Semistructured Structured O’Brien p. 353 Information properties Strategic Management Tactic Management Operational Management Ad hoc Irregular Compact Not frequent Future Oriented External Broad Pre-defined Regular Detailed Frequent Historical Internal Model for the decision making process Research activities Design activities Choice activities Try to find and recognise situations that require a decision Opportunities need to be identified and notified Design and evaluate differences in behaviour An information system has to contribute to create and evaluate opportunities Decide on actions and control the implementation The information system has to contribute to the decision making on the priorities of alternative decisions and has to provide feed-back for the execution Decision making structure Operations Management Unstructured Cash management Partially structured Credit management Production scheduling Daily work distribution Structured O’Brien p. 354 Stock management Billing Tactical Management Strategic Management Work organisation Performance Analysis Planning new business Company reorganisation Personnel evaluation Budgeting Project budgets Production planning Plant location Co-operation Program management Decision Support Systems (DSS) Computer supported Information systems designed to provide interactive and informative support for the managers during the decision making process. DSS use : analytical models specialised databases input and expertise of the person that has to take the decision interactive , automated modelling process to support the usage of partially structured and unstructured decisions by individual managers Ad-hoc quick response systems directed by mangers Architecture Hardware : workstation and communication system Software DSS software packages (DSS generators) • database management • model base management • generate and manage dialogue windows Data company database external databases personal databases for the manager Models : libraries of mathematical models and analytical techniques People What is a decision support system? More precise goal than a standard MIS system. The aim is to deliver capabilities and not only to provide information . Corporate MIS TPS Statistical model Finance Marketing Strategic plan Production Operational model Model Database DBMS database management system MBMS Model base management system DGMS Dialogue generation and management software DBMS MBMS DGMS USER Flowchart analysis of investment decision A Portfolio data Retrieve Portfolio No display performance each industry Yes project Future Performance pick strategy research data Retrieve Research reports Stock OK ? No Still OK ? Yes Pick stock Purchase Stock data graph stock performance A Decision process is frozen as system is developed Client DSS approach to same problem Set of 4 capabilities Representation Portfolio lists Graphs Research reports Simulation outputs Interface language Graph operations Report operations Simulation operations Procedure operations Storage Databases Operations List operations Memory aids Work space representations Control aids Menus Training documents A DSS is a decision-making scratch path , backed up by a database , that decision makers can use to support many decision making processes. Differences Dimension Microcomputing DSS MIS Philosophy Provide computing power to end users and simple models Provide integrated tools, data models and language to users Provide information to end users Objectives Increase productivity of knowledge and office workers Directly impact key decisions and enhance effectiveness of decision making Enhance control and monitoring power of middle managers Systems Analysis Identify what software packages suitable for task at hand Establish what tools are used in the decision process Identify information requirements Design Iterative process never frozen Deliver system based on frozen requirements Customise package to task Three levels of DSS technology Specific DSS software to guide decision making ( spreadsheets , ... ) DSS generators package of hardware and software , providing tools to build specific DDS examples : IFPS ( Interactive Financial Planning System ) EIS ( Executive Information System ) DSS tools building blocks of generators special purpose languages ( APL ) permit rapid development of applications , screens , menus , ... graphics routines , graphics hardware , supporting telecommunications Roles to play Manager or end user responsible for making key organisational decisions a DSS must provide information on how things are going The Intermediary skilled staffer who helps to schedule manager’s or task force work The DSS builder must be familiar with the business problem must have good understanding of how to make the technology work The technical supporter member of the data processing group develops and installs DSS generators and tools DSS requires links to databases , graphic software , ... The Toolsmith develops new technology , new software works often for private vendors Type of Analytical Model What-if analysis Examine how changes in selected variables influence other variables e.g.: what is the impact on sales if we spent 10% less on publicity? Sensitivity analysis Examine how repeated changes in a variable can influence other variables e.g.: Lower the budget for publicity several years with € 5.000 to discover the relationship between publicity budget and sales Goal-seeking analysis Modify selected variables until a specific variable reaches a pre-defined value e.g.: Increase the publicity budget until sales reaches € 10M Optimise Determine optimal value for variables Executive information systems (EIS) Information systems where the characteristics of modern information reporting systems are combined with characteristics of DSS’s . Provide direct and easy access to information on CSF’s. Factors for good EIS: Involvement and support of top-management Knowledge of information sources Concentrate on crucial factors Response times Insight in the level of computer knowledge of managers Learning time for the development team Flexibility Ongoing support Artificial Intelligence Characteristics of intelligent behaviour think and logical reasoning problem solving via logical reasoning learn and getting insight based on experience gather knowledge and apply this creativity and imagination handle complex and chaotic situations react successfully on new situations estimate the relative importance of different factors ability to work with ambiguous or incorrect information AI tries to build computer systems that show this type of behaviour Artificial Intelligence Family Tree Natural Language Expert systems Intelligent machines: AI hardware Robotics Perceptive Systems (vision, hearing) Human and Artificial Intelligence Successful AI systems are neither artificial nor intelligent based on : human expertise knowledge selected reasoning patterns act like textbooks cannot learn without being rewritten existing systems extend the powers of experts they do not substitute experts they have no common sense Knowledge-based Expert Systems An expert system is a knowledge-intensive program that normally requires human expertise. An expert system can assist decision-making by asking relevant questions and explaining the reasons for adopting certain actions. Characteristics: they perform some of the problem-solving work of humans they use knowledge in the form of rules or frames they interact with humans they can consider multiple hypotheses simultaneously Today’s expert systems are quite narrow , they do not think , do not resort to reasoning , do not draw analogies , lack common sense . Three levels assistant helps doing routine analysis Colleague user discusses the problem until a joint decision is reached when system is wrong , user adds additional information Complete expert automaton makes the decisions for the user without questions operates remotely beyond human intervention not yet applied in practical areas Components of an expert system Development team Corpus of Knowledge Expert(s) Knowledge Engineers Shell or Development environment Development Interface Production Rules Semantic nets Frames User Interfaces suggested solutions Answers data Questions Commands Users Expert systems vs. Decision Support Systems DSS Goals ES Support of human decision maker Who makes decisions the man or the system or recommendations? Direction of the man inquiries system inquiry Type of support individuals , groups and Copy or replace human advisor the system type of data manipulation Characteristics of the problem domain Type of problems Database contents Deduction capacity Explain capacity Numeric symbolic complex, broad limited , specialised ad hoc, unique facts no repeating procedures and facts yes , limited limited yes system inquiries man individuals and groups ES applications Decision making management evaluate performances, insurance's , ... Diagnostics / problem solving help desk, error detection in software, ... Maintenance / planning maintenance planning , production planning , training , ... Intelligent text / documentation regulations , security standards , taxation , ... Design / configuration feasibility studies , assembly schema’s, ... Selection / classification material selection, information classification, person identification Process management / Steering machine steering, production control, stock management, ...