Chapter 9 Information systems for Managerial Decision Form

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 ð manage ð contact person § concerning information ð control ð distribute § concerning decisions ð take ð problem solving ð distribution of the resources ð 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 ion s cis De on Structured O’Brien p. 353 ati Semistructured rm Strategic Management fo In Unstructured Information properties 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 : ðanalytical models ðspecialised databases ðinput and expertise of the person that has to take the decision ðinteractive , 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 ð DSS software packages (DSS generators) • database management • model base management • generate and manage dialogue windows § Data ð company database ð external databases ð 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 Provide integrated Provide information power to end users tools, data models to end users and simple models and language to users Objectives Increase productivity Directly impact key control of knowledge and decisions and enhance and monitoring office workers effectiveness of power of middle decision making managers Enhance Systems Analysis Identify what software Establish what tools information packages suitable for are used in the requirements task at hand decision process Identify Design Customise package Iterative process to task never frozen based on frozen requirements Deliver system

Three levels of DSS technology Specific DSS ð software to guide decision making ( spreadsheets , . . . ) DSS generators ð package of hardware and software , providing tools to build specific DDS ð examples : IFPS ( Interactive Financial Planning System ) EIS ( Executive Information System ) DSS tools ð building blocks of generators ð special purpose languages ( APL ) ð permit rapid development of applications , screens , menus , . . . ð graphics routines , graphics hardware , supporting telecommunications

Roles to play § Manager or end user ð responsible for making key organisational decisions ð a DSS must provide information on how things are going § The Intermediary ð skilled staffer who helps to schedule manager’s or task force work § The DSS builder ð must be familiar with the business problem ð must have good understanding of how to make the technology work § The technical supporter ð member of the data processing group ð develops and installs DSS generators and tools ð DSS requires links to databases , graphic software , . . . § The Toolsmith ð develops new technology , new software ð 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 € 10 M 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 ð think and logical reasoning ð problem solving via logical reasoning ð learn and getting insight based on experience ð gather knowledge and apply this ð creativity and imagination ð handle complex and chaotic situations ð react successfully on new situations ð estimate the relative importance of different factors ð 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: ð they perform some of the problem-solving work of humans ð they use knowledge in the form of rules or frames ð they interact with humans ð 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 ð helps doing routine analysis § Colleague ð user discusses the problem until a joint decision is reached ð when system is wrong , user adds additional information § Complete expert automaton ð makes the decisions for the user without questions ð operates remotely beyond human intervention ð 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 yes system inquiries man individuals and groups

ES applications § Decision making management ð evaluate performances, insurance's , . . . § Diagnostics / problem solving ð help desk, error detection in software, . . . § Maintenance / planning ð maintenance planning , production planning , training , . . . § Intelligent text / documentation ð regulations , security standards , taxation , . . . § Design / configuration ð feasibility studies , assembly schema’s, . . . § Selection / classification ð material selection, information classification, person identification § Process management / Steering ð machine steering, production control, stock management, . . .