Management Information System 3


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Management Information System 3

  1. 1. Amity School of Business Jitendra TomarAmity School of Business, Amity University, UP 09650512300 0120 4392867 MIS - Orator
  2. 2. Amity School of Business • Organizations, Management & Information. • Information Technology Infrastructure.• Managing and Organizing Support Systems for the Firm. • Building Information Systems in the Digital Firm. • Managing Information Systems in the Digital Firm. MIS - Curriculum
  3. 3. Amity School of BusinessManagers & their Prolific need.• Strategic Management – Typically, a board of directors and an executive committee of the CEO and top executives. – Develop overall organizational goals, strategies, policies, and objectives as part of a strategic planning process. – Monitor strategic performance of the organization and its overall direction in the political, economic, and competitive business environment. – Decisions made at this level are highly structured. Managers & Support Systems
  4. 4. Amity School of BusinessManagers & their Prolific need.• Tactical Management – Business professionals in self directed teams as well as business unit managers. – Develop short and medium range plans, schedule and budgets. – Specify the policies, procedures, and business objectives for the subunits of their company and allocate resources. – Monitor the performance of their organizational subunits, including departments, divisions, process teams and workgroups. – Decisions made at this level are semi-structured. Managers & Support Systems
  5. 5. Amity School of BusinessManagers & their Prolific need.• Operational Management – The members of self directed teams or operating managers. – Develop short-range plans such as weekly production schedules. – Direct the use of resources and the performance of tasks according to procedures and within budgets. – Establish the schedules for the teams and other workgroups of the organization. – Decisions made at this level are highly unstructured. Managers & Support Systems
  6. 6. Amity School of BusinessManagers & their Information Systems.• Employees at different levels in an organization must make decisions that vary in scope and type.• In pyramidal view of an organization we have seen the types of information systems needed for an organization’s different operational and managerial levels.• The information systems used at different levels of management are: – Transaction Processing System (Shop-floor Level), – Decision Support System (Tactical & Strategic Level), – Executive Information System (Strategic Level), & – Expert System (Tactical & Strategic Level).• Also, with growing need for information at different levels, these traditional correlations can become blurred. Managers & Support Systems
  7. 7. Amity School of BusinessDSS - Defined.• Decision Support Systems are computer based information systems that provide interactive information support to managers and business professionals during the decision- making process.• Decision Support Systems use – Analytical Models, – Specialized databases, – A decision makers own insight and judgments, and – An interactive, computer-based modeling process, to support the making of business decisions. Decision Support Systems
  8. 8. Amity School of BusinessDSS – Phases in Decision Making.A Decision Making is a three phase process.• Intelligence Phase – Collect data from inside the organization. – Collect data from outside the organization. – Collect information on all possible ways to solve the problem.• Design Phase – Organize the data in a definite structure. – Produce reasonable, potential courses of action. It could be more than one.• Choice Phase – Select the course of action. Decision Support Systems
  9. 9. Amity School of BusinessDSS – Problem types.Depending upon the amount of data and the availability of data analysis methods, the problems can be classified as:• Structured Problem – Optimal solution can be reached in a single set of steps. – Solution with same data will always yield the same answer. – Sequence of steps followed is called algorithm. – Categories of data is known as parameters. – It is referred as programmable problem.• Unstructured Problem – There is no standard algorithm for optimal solution because • Either there is no enough information • So many potential factors are there that no algorithm can be formulated. – Closely related to uncertainty. Decision Support Systems
  10. 10. Amity School of BusinessDSS – Components.Depending upon the amount of data and the availability of data analysis methods, the problems can be classified as:• The Data Management Module – It is a database or data warehouse. – Retrieves and manipulates relevant data.• Model Management Module. – Maintains alphanumeric and graphical models, formulas and algorithms. – Best Model is selected for typical decision making problems.• The Dialog Module – It allows the user to access the database. – Select data for decision process. Decision Support Systems
  11. 11. Amity School of BusinessDSS – Analytical Models.Using DSS involved four types of analytical models:• What-If Analytical Model – Observing how changes to selected variables affect other variables. – E.g.: What if we cut advertising by 10% ? What would happen to sales?• Sensitivity Analytical Model – Observing how repeated changes to a single variable affect other variables. – E.g.: Let’s cut advertising by $100 repeatedly so we can see its relationship to sales. Decision Support Systems
  12. 12. Amity School of BusinessDSS – Analytical Models.Using DSS involved four types of analytical models:• Goal-Seek Analytical Model – Making repeated changes to select variables until a chosen variable reaches a target value. – E.g.: Lets try increases in advertising until sales reach $1 Million• Optimization Analytical Model – Finding an optimum value for selected variables, given certain constraints. – E.g.: What’s the best amount of advertising to have, given our budget and choice of media? Decision Support Systems
  13. 13. Amity School of BusinessEIS - Defined.• In 1980’s, the rapid development of microcomputer processing power, application software packages, and telecommunications networks gave birth to the phenomenon of end-user computing.• End-users could now use their own computing resources to support their job requirements instead of waiting for the indirect support of centralized corporate information service department.• Gradually it became evident that most top corporate executives, due to information overload, could not effectively use either the generated reports of Information Systems or the Analytical Modeling capabilities of DSS and hence the concept of Executive Information System. Executive Information System
  14. 14. Amity School of BusinessEIS - Defined.• EIS provides critical information from wide variety of internal and external sources in easy-to-use displays to executives and managers.• It provides high ranking managers with the most essential information.• It is useful in parting down the information for executives who always suffer from information overload.• EIS do not contain analytical models.• EIS consolidate and summarize internal and external data.• It displays the data in a way so that exceptions are easily spotted. Executive Information System
  15. 15. Amity School of BusinessKnowledge Management.• Knowledge Base - A computer-accessible collection of knowledge about a subject in a variety of forms, such as facts and rules of inference, frames, and objectives.• Knowledge Management – Managing the Knowledge Base i.e. the process of organizing and sharing the diverse forms of Business Knowledge and Knowledge Bases within an organization. It includes project & enterprise libraries, discussion DB, intranet DB, and similar knowledge bases.• Knowledge Workers - People whose primary work activity includes creating, using, and distributing information.• Knowledge Engineers – The specialists who works with experts to capture the knowledge they possess in order to develop a knowledge base for expert systems and other knowledge- based systems. Knowledge Management
  16. 16. Amity School of BusinessKnowledge Management & Research.• There are two types of knowledge about a subject: – Awareness: The explored and unexplored information about the subject, – Source: Where to locate the known and unknown facts about the subject.• Knowledge is accumulated through experience and kept at places that are not readily available with the people: – People’s Mind – Discussion Transcript – Paper Notes.• Knowledge Management puts procedures & technologies to: – Transfer individual knowledge into DBs or KBs. – Recognize most relevant information / knowledge. – Allow the people to share the information / knowledge. Knowledge Management
  17. 17. Amity School of BusinessMethods of Knowledge Representation.• Case-Based Reasoning - Represent knowledge in the ES’s knowledge base in the form of cases, i.e. examples of past performance, occurrence, and experience• Frame-Based Reasoning - Knowledge represented in the form of a hierarchy or network of frames. A frame is a collection of knowledge about an entity consisting of a complex package of data values describing its attributes.• Object-Based Reasoning - Knowledge represented as network of objects. An object is a data element that includes both data and the methods or processes that act on those data.• Rule-Based Reasoning - Knowledge represented in the form of rules and statements of fact. Rules are statements that typically take the form of a premise and a conclusion such as: If (Condition), Then (Conclusion). Knowledge Management
  18. 18. Amity School of BusinessArtificial Intelligence – What’s That?• AI concept foresee machines having Human Intelligence.• AI Technologies are used in variety of ways to improve decision support provided to managers and business pros.• AI-enabled applications are at work in information distribution and retrieval, database mining, product design, manufacturing, inspection, training, user support, surgical planning, resource scheduling, and complex resource management.• For anyone who schedules, plans, allocate resources, design products, use the Internet, develop the software, is an investment professional, heads the IT, uses IT, or operates in any other capacities and arenas, AI technologies already may be in place and providing competitive advantage to them. Artificial Intelligence & Expert Systems
  19. 19. Amity School of BusinessArtificial Intelligence – Early Encounters.• In late 50’s and early 60’s, scientists tried to build a system that could perform intelligent tasks.• They tried to build a system that could mimic humans.• These efforts failed because the programs needed for the task would have to be unrealistically huge and very complex in nature.• They started with designing of programs to solve problems in specific domain by utilizing expert knowledge and reasoning.• The programs are referred as the Expert Systems, which are based on the concept of Artificial Intelligence. Artificial Intelligence & Expert Systems
  20. 20. Amity School of BusinessArtificial Intelligence – Matching the Human Intelligence.Some of the attributes of Intelligent Human Behavior are given below. AI is attempting to duplicate these capabilities in computer-based systems.• Think and Reason.• Use reason to solve problems.• Learn or understand from experience.• Acquire and apply knowledge.• Exhibit creativity and imagination.• Deal with complex or perplexing situations.• Respond quickly and successfully to new situations.• Recognize the relative importance of elements in a situation.• Handle ambiguous, incomplete, or erroneous information. Artificial Intelligence & Expert Systems
  21. 21. Amity School of BusinessArtificial Intelligence – The Domains.AI applications are grouped under three major areas: Artificial Intelligence Cognitive Natural Robotics Science Interface Applications Applications Applications •Learning Systems •Visual Perception •Natural Languages •Fuzzy Logic •Tactility •Speech Recognition•Genetic Algorithms •Dexterity •Multi-sensory •Neural Networks •Locomotion Interfaces •Intelligent Agents •Navigation •Virtual Reality Artificial Intelligence & Expert Systems
  22. 22. Amity School of BusinessArtificial Intelligence – Commercial Applications.Decision Support.• AI is used to develop Intelligent work environment that will help in capturing ‘why’ as well as ‘what’ of engineered design and decision making.• AI provides an Intelligent human-computer interface (HCI) systems that can understand spoken language and gestures, and facilitate problem solving by supporting organization wide collaborations to solve particular problems.• AI facilitates Situation Assessment and Resource Allocation software for variety of uses that range from airlines & airports to logistics centers. Artificial Intelligence & Expert Systems
  23. 23. Amity School of BusinessArtificial Intelligence – Commercial Applications.Information Retrieval.• AI-based Intra and Internet systems can be used to distill tidal waves of information into simple presentations.• AI based Natural Language Technology can be used to retrieve any sort of online information, from text to pictures, videos, maps, and audio clips, in response to a verbal query.• AI helps in Database mining for purposes like marketing trend analysis, financial forecasting, maintenance cost reduction, and more. Artificial Intelligence & Expert Systems
  24. 24. Amity School of BusinessArtificial Intelligence – Commercial Applications.Virtual Reality.• AI provides X-ray like vision enabled by enhanced-reality visualization. It enables Automated animation and haptic interfaces that allow users to interact with virtual objects via touch• Brain surgeons to “see through” intervening tissue to operate, monitor, and evaluate disease progression. Medical students can “feel” what it’s like to suture severed aortas.Robotics• Machine Vision inspections systems for gauging, guiding, identifying, and inspecting products and providing competitive advantage in manufacturing are based on AI.• AI leads to development of cutting-edge robotics systems from micro robots and hands & legs to cognitive robotic and trainable modular vision systems. Artificial Intelligence & Expert Systems
  25. 25. Amity School of BusinessExpert System - Defined.• An expert system is a knowledge-based information system that uses its knowledge about a specific, complex application area to act as an expert consultant to end users.• Expert systems provide answers to questions in a very specific problem area by making human like inferences about knowledge contained in a specialized knowledge base.• They also explain their reasoning process and conclusions to a user.• They provide decision support to the end users in form of an advice from an expert consultant in a specific problem area.• The components of Expert System include a knowledge base and software modules that perform inferences on the knowledge in the knowledge base and communicate answers to a user’s questions. Artificial Intelligence & Expert Systems
  26. 26. Amity School of BusinessExpert System - Benefits.• An ES captures the expertise of an expert or group of experts in a computer-based information system.• It can out perform a single human expert in many ways. – It is faster and more consistent. – Can have knowledge of several experts. – Does not get tired or distracted by over work or stress. – They also help preserve and reproduce the knowledge of experts. They allow an organization to preserve the expertise of an expert before he/she leaves the organization, which can later be shared by reproducing the software and knowledge base of the expert system. Artificial Intelligence & Expert Systems
  27. 27. Amity School of BusinessExpert System - Limitations.• ESs can handle only narrow domains – Early attempts to create general problem solvers failed miserably. Current ESs performs well if the domain they handle is precisely defined.• ESs do not possess common sense – With all the sophistication, ESs can not recognize problems that require common sense. The system will be able to solve only those problems it was specifically programmed to solve.• ESs have limited ability to learn – While neural network technology made great strides in the area of machine learning, the ability of computer-based programs to learn remains limited. Knowledge Engineers must coach the systems and provide continual feed back for the systems to learn. It may take many years for scientists to produce an ES that can quickly learn and apply self-learned knowledge. Artificial Intelligence & Expert Systems
  28. 28. Amity School of BusinessExpert System – Suitability Criteria.• Domain – The domain , or subject area, of the problem is relatively small and limited to a well-defined problem area.• Expertise – Solutions to the problem require the efforts of an expert. That is, a body of knowledge, techniques, and intuition is needed that only a few people possess.• Complexity – Solution to a problem is a complex task that requires logical inference processing, which would not be handled as well by conventional information processing.• Structure – The solution process must be able to cope with ill- structured, uncertain, ambiguous, missing, and conflicting data, and a problem situation that changes with the passage of time.• Availability – ES acts as an expert, who is articulate and cooperative, and have the support of the management & end users, is involved in the development of the proposed system. Artificial Intelligence & Expert Systems
  29. 29. Amity School of BusinessExpert System – In Action Globally.• Telephone Network Maintenance – ES at Pacific Bell.• Credit Evaluation – AmEx and FAST of American Express.• Tax Planning – TaxAdvisor for Federal & State Tax laws.• Insider Securities Trading – AMEX at American Stock Exchange.• Detection of common metals – ES at General Electric Corp.• Mineral Exploration – PROSPECTOR• Irrigation & Pest Management – EXNUT at U.S. Department of Agriculture.• Predicting failures of Diesel Engines – ES at Canadian Pacific Railroad.• Medical Diagnosis - ES named CADUCEUS, MYCIN and PUFF.• Class Selection for Students – ES at California State University. Artificial Intelligence & Expert Systems