Unit 2 Decision Support System PDF

Unit 2 Decision Support Systems Decision Support System (DSS), Group Decision Support Systems (GDSS) Executive Information System (EIS/ ESS) Expert System and Knowledge based Expert systems (KES), Artificial Intelligence (AI) ERP ...

Unit 2 Decision Support Systems Decision Support System (DSS), Group Decision Support Systems (GDSS) Executive Information System (EIS/ ESS) Expert System and Knowledge based Expert systems (KES), Artificial Intelligence (AI) ERP  Artificial Intelligen Expert ce Executive System (Robotics Information (Chess, ) Decision System / other games, Support Executive mimics Managemen System / t Support human Group Information Decision System being) Office System Support automation Transactio system (providing System (aid n (Inventory, information) in the process Processing Billing, of DM) (Payroll) / Wordstar) EDP  EDP : Focus on Data OAS : Focus on Communication MIS : Focus on Information DSS : Focus on Decision Support for a specific business problem EIS : Focus on Decision Support for Top Management ES : Focus on Consultation AI : Focus on self-learning/thinking systems MIS at different levels of mangement Top Level -- Strategic Planning Middle Level -- Management Control Junior Level -- Operational Control Clerical Level --- Transaction Processing Summarization Unit 1 An MIS orientation means users have access to decision models and methods for querying the database on an ad hoc basis; the database is also, an essential part of routine transaction processing and reporting. In MIS information is utilized so as to improve decision making and achieve improved organizational effectiveness. MIS is the system, which makes available the right information to the right person, at the right place, at the right time, in the right form and at the right cost. MIS has become necessary due to the increased Business and Management Complexities. These complexities demand not only quantitative but qualitative decision-making. And all managers, as we know, have to take decisions under conditions of Risk, Certainty or Uncertainty. A good manager/decision-maker is one who minimizes, if not eliminates altogether, the elements of risk and uncertainty in decision-making. MIS is helpful in doing precisely this.  What is a decision A choice made out of several options made by a decision maker to achieve some objective in a given situation The DM process is a complex process in the higher hierarchy of management. The personal value of the decision maker plays a major role in decision making There is definite method of arriving at a decision; and it can be put in the form of decision process model.  The DM process requires creativity, imagination and a deep understanding of human behavior. The process covers a number of tangible and intangible factors affecting the decision process. It also requires a foresight to predict the post-decision implications and a willingness to face those implications. All decisions solve a ‘problem’ but over a period of time they give rise to a number of ‘problems’ It is one of the most important managerial function Decisions are made at different levels in the organization Decision made at different levels vary in their content, The decision making process involves the following steps :  Determine existence of problems and/or opportunities.  Generate alternative courses of action.  Analyze/choose/select a course of action.  Implement the course of action.  Monitor, follow-up and initiate course-corrective action.  Types of decision There are 3 types of decision 1. Programmed Decisions – structured decisions 2. Non programmed decisions – unstructured decisions 3. Semi programmed decisions  Programmed Decisions Through this the problem is solved by predefined procedure or algorithm. These decisions are repetitive and routine. Example payroll , inventory A solution manual to problem is prepared. Characteristics of these decisions are These decisions can be delegated, cost of solving a problem is low Such decisions can be made with the help of computer system Routine/structured, Repetitive/short-term Definite procedure is to be followed, there are laid down norms The situations are known Taken at the lower/operating levels in an organization Programmed decisions are also called as If-Then-Else IF sale value > 10,000 THEN offer discount of 3 % ELSE IF sale value > 5,000/- THEN offer discount of 2% ELSE no discount In these cases the sales person is provided with the rules to offer the discount. Structured/Programmed decision strictly follow the pre- determined rules. The results of the are deterministic in nature. Generally made at lower level of management The DM rules are established by middle level and top level management The techniques used for taking programmed decisions are :  Habit  Standard Operating Procedure (SOP)  Organizational Hierarchy/Structure  Operational Research  Computers If such rules can be developed wherever possible, then the MIS itself can be designed to make a decision and even execute. The system in such a case plays the role of the decision maker based on a given rule or a method. Since the programmed decision are made through MIS, the effectiveness of the rule can be analyzed and the rule can be reviewed and modified from time to time for an improvement. The programmed decision making can be delegated to a employees working at the lower level of management  Non programmed decisions Unstructured, occasional, of high consequence, complex and major commitments. No predefined program or set decision available. Example advertising budget, new product decision. Characteristics of NPD 1. Difficult to structure in logical mathematical terms 2. Cannot be delegated based on management direction thinking and deliberations 3. Computers cannot be used directly  used only for processing large volumes of necessary data The major characteristics of the non-programmed decisions are :  Novel-not cut and dried  Innovative  New/complex situations  Important and critical  Strategic  Long-term MIS in the NPD situation, can help to some extend, in identifying the problem, giving the relevant information to handle the specific decision making situation. These types of decisions cannot be delegated at lower level of management It can develop DSS in the non-programmed decision making situation The techniques used for taking non-programmed decisions are : Judgment  Intuition  Business acumen  Creativity  Complex/specially designed computer programs  Training executives  Semi-programmed decisions At least one but not more than two of the above stages can be handled by a well defined preset procedure. An example of such a decision is the intelligent phase, which is well structured, having diverse kinds of variance analysis. Here a comparison with a budget is undertaken in a well defined way to indicate the need for a decision. Subsequent stages of design and choice are, however not handled by any set procedure.  Control & Feedback Feedback is data about the performance of a system. Control is monitoring and evaluating feedback to determine whether the system is moving towards the achievement of its goals. It then makes necessary adjustments if any, to the input to ensure that proper output is produced. With these controls the system is self-monitoring and self regulating. A reliable and effective control system has the following features :- 1. Early Warning Mechanism 2. Performance Standard 3. Strategic Control  Controlling critical success factors. 4. Feedback 5. Accurate and Timely 6. Realistic. 7. Information Flow 8. Exception Principle should selectively approve some significant deviations from the performance standards on the principle of management by exception. A standard is meaningful when it is achievable and provides a challenge to the achiever.  Feedback as integral part of a system INPUT PROCESSOR OUTPUT Information Recorded, Stored, Decision Retrieved etc Feedback on effective decisions To various functions  Usefulness of feedback Desired Performance Actual Performance Actual Performance Implement Course Measurement Correcting Programmed Programme for corrective Actual Vs Standard action Performance Compared Analyze Causes for Deviation Identify Deviation  Law of requisite variety In a given control system there are several subsystems. Each subsystem has a possible control state. Elements constituting a system may malfunction and there has to be an appropriate mechanism to ensure that their malfunctioning is detected and corrected To control each possible state of the system elements, there must be a corresponding control state. The entire system cannot be controlled through a single point. The control system, is effectively  Law of requisite variety The law of requisite variety also means that for a system to be controlled, each controller – human and machine must be provided with : Enough control responses (what to do in each case) to cover all possible conditions the system may face Decision rules for generating all possible control responses The authority to become self organizing system in order to generate control responses.  Points to be remembered :- Don’t give managers what he said he wanted but what he meant. MIS brings about a qualitative decision making and not quantitative DM MIS minimizes risk and surprise (cannot eliminate) Helps bringing about a proactive decision making Think Globally act locally Decision Support System Refers to a class of systems, which support the process of decision making, it emphasis on support rather than on automation of decisions. DSS allows the DM to retrieve data and test alternative solutions during the process of problem solving. DSS can also be defined as a set of well integrated , user friendly, computer based tools that combine data with various decision making models– qualitative and quantitative – to solve semi structured and Decision Support Systems (DSSs) are interactive information systems that rely on an integrated set of user-friendly hardware and software tools to produce and present information that is targeted to support the management in the decision-making process. The decision support systems assist management decision- making by combining data, sophisticated analytical models and user-friendly software into a single powerful system that can support semi-structured or unstructured decision- making. The decision support system is under user control, from early inception to final implementation and daily use. Decision support system helps to close the information gap to enable managers to improve quality of their decisions DSS refers to a class of systems, which support in the process of decision making and does not always give a decision itself. These systems can be used to validate decision by performing sensitivity analysis on various parameters of the problem  Helps DM in decision making Designed to solve semi structured and unstructured problem Support decision maker at all levels, but is most effective at tactical and strategic levels Makes general purpose models, works as a tool Interactive, user friendly system that can be used by the DM with little or no assistance from an MIS professional Readily adapted to meet the information requirements for any decision environment  Provides mechanism for decision maker DSS has the capability to interface with the corporate database Not executed in accordance with pre-established production schedule Flexible enough to accommodate a variety of mgmt styles. Facilitates communication between levels of decision making DSS helps to close the information gap to enable managers to improve quality of their decision  DSS definition Refers to a class of systems, which support the process of decision making, it emphasis on support rather than on automation of decisions. DSS allows the DM to retrieve data and test alternative solutions during the process of problem solving. DSS can also be defined as a set of well integrated , user friendly, computer based tools that combine data with various decision making models– qualitative and quantitative – to solve semi structured and unstructured problems.  Characteristics of DSS Helps DM in decision making Designed to solve semi structured and unstructured problem Support decision maker at all levels, but is most effective at tactical and strategic levels Makes general purpose models, works as a tool Interactive, user friendly system that can be used by the DM with little or no assistance from an MIS professional Readily adapted to meet the information requirements for any decision environment Provides mechanism for decision maker DSS has the capability to interface with the corporate database Not executed in accordance with pre-established production schedule Flexible enough to accommodate a variety of mgmt styles. Facilitates communication between levels of decision making  Decision making and MIS DSS is a special class of system which is used as a support in decision making. Making of the DM situation at all levels of management are such that its occurrence is infrequent but the methodology of DM is known, the same is proven and widely used. Such applications are separated as DSS These systems use data from the general MIS and are used by a manager or decision maker, for decision support. The DSS could be an internal part of MIS When decision making is required in real time dynamic mode all such systems are designed to read, measure, monitor, evaluate and analyze and act as per decision guidance embedded in the system. MIS becomes more useful when decision making is made person independent and executed with well designed DSS. If decision cannot be automated through MIS, it directly effect decision making ability of a manger  Some more facts about DSS Developed jointly by user and System Analyst Uses the principles of economics, science, engineering and tools and techniques of mgmt Data used in DSS is drawn from information systems developed in the company Developed in isolation and form an independent system subset of MIS The most common use of DSS is to test the decision alternatives and also to test the sensitivity of the result to the change in the system and assumption The data and information for the DSS are used from internal sources such as the database and conventional files and for external sources,  Attributes of Decision Support System Flexibilit flexible so that semi structured or y unstructured decision making situation can be tackled with ease and speed. Simple The systems use simple models of decision models making. The only change is that a different set of information is sought for the use of different models. The choice of a model depends upon the complexity of decision making. Database Information being common, input to the system is from the database. Factors in Decision Support Systems Success and Failure 1. User Training Involvement 2. User Experience 3. Top Management Support 4. Orientation towards Top Management 5. Length of use 6. Novelty of application 7. Return on investment Components of DSS Then DSS has three basic components 1. The database 2. A Model Base 3. DSS Software System  The database The DSS database is a collection of current or historical data from a number of applications or groups. It is organized in such a manner that it provides easy access for a range of applications. Adequate precaution is taken to ensure the data integrity while controlling the processing that keeps the data current. DSS do not create or update data, but rather use live organizational data so that the decisions could be taken based upon actual conditions. It would also be imperative to remember that most DSS do not have direct access to organizational data but usually use data that have been extracted from relevant databases – both internal and external - and stored specifically for the DSS.  The Model Base Decision Support System Operations Behavioral Management Research Model Science Model Model A model is an abstract representation that illustrates the components or relationships of a phenomenon. A model can be physical model, a mathematical model or a verbal model. DSS can and does make use of different types of models. The models could be broadly classified into three types as above a. Behavioral Model : The focus of behavioral models of DSS is on studying / understanding the behavior/trends amongst the variables. Decision could then be arrived at with due regards to such behavioral relationships. Trend Analysis, Forecasting, Co-relation, Regression are examples of Behavioral Models of DSS. b. Management Science Model : These models are developed based upon the Principles of Management, Management Accounting and Econometrics, among others. Budgetary Systems, Cost Accounting, Capital Budgeting, Inventory Management etc. are examples of Management Science Model of DSS among others. c. Operations Research Model : ‘Operations Research’ is basically application of mathematical formulae for arriving at optimum solutions. As such Operations Research Models are mainly mathematical models. These models represent real life problems/ situations in terms of variables and parameters expressed in algebraic equations form. Linear Programming, ABC Analysis, Mathematical Programming Techniques, Material Requirement Planning are some of the examples of the Operations Research Model.  Functions of DSS 1. Model Building allows decision makers to identify the most appropriate model for solving problem on hand. It takes into account input variables, interrelationships amongst variables, problem assumptions and constraints. 2. What If Analysis  This is the process of assessing the impact of changes to model variables, the value of variable or the interrelationships among variable. This helps mangers to be pro- active rather than reactive 3. Goal Seeking Determines the input values required to achieve a certain goal.  4. Risk Analysis Assess the risk associated with the various alternatives. 5.. Graphical Analysis  Helps managers to quickly digest larges volumes of data and visualize the impacts of various courses of action. Graphs can be used the following situations:- a. Seeking a quick summary of data b. Detecting trends over time c. Comparing points and patterns at different variables d. Forecasting activities e. Seeking relatively simple impressions from a vast amount of information.  The DSS Software System Provides a graphic , easy to use, flexible user interface that support the dialogue between the users and the DSS Support tools like online help, pull down menu, error correction mechanism. Interfaces are an important support tool in a DSS Managers recognise the power and potential of DSS, the main problem to its adoption is lack of people with training in computer technologies. In such an environment, good interface can make or break a system.  The DSS Software System Provides a graphic , easy to use, flexible user interface that support the dialogue between the users and the DSS Support tools like online help, pull down menu, error correction mechanism. Interfaces are an important support tool in a DSS Managers recognise the power and potential of DSS, the main problem to its adoption is lack of people with training in computer technologies. In such an environment, good interface can make or break a system. Management Information System Decision Support System The focus is on structured task Focus is on semi/unstructured and routine decisions tasks which require managerial judgement. Identifies information Establishes tools to be used for requirement decision process Emphasis is on data storage Emphasis is on data manipulation Delivers system based on frozen Follows iterative process hence requirements current data can be used. Provides only indirect access to Managers have direct access to data by managers data Relies on computer experts Reliance on managerial judgement Access to data possibility Direct access to computer requiring a ‘wait’ for and data. Hence no wait. manager’s turn MIS manager may not Manager knowing nature of completely understand the decision and decision nature of decision. making environment Emphasis is on efficiency Emphasis is on effectiveness Group Decision Support System  “GDSS is an interactive computer-based system that facilitates the solution of unstructured problems by a set of decision-makers working together as a group ”. When DSS application was suitably extended/expanded to facilitate Group Decision Environment and the DSS for a group came to be known as the Group Decision Support System (GDSS). It is also referred to as a Group Support System or a Computerized Collaborative Work System (CCWS). We would, however, refer to this extended/expanded form of DSS as the GDSS. Under the GDSS Environment, the members of the group utilize the DSS as a group and the user-interface is expanded to include the computers which are suitably connected / networked. In this way, under the GDSS, members of the group can communicate using their computers with DSS or with other members of the group to facilitate optimal decision- making.  GDSS Components The GDSS components are similar to that of the DSS components. The GDSS has three basic components viz. the Hardware , the Software, the People and Procedure. In addition, communication technology would be the most important component to facilitate participation by the group members from various sites/locations. Care must, however, be taken to ensure that the technology supports the group and does not dominate it. Hardware  Input/Output devices, Audio Visual Instruments  Electronic Display Board/Screens, Computer Equipment  Conferencing Infrastructure  Network Systems enabling the linking of different sites/locations and participants to each other. Software (Generally  Database and DBMS, Modeling Capabilities referred as a “Groupware”  Dialogue Management with multiple-user access. or “Workgroup Software”) Specialized Application Programmes to facilitate group access  People and Procedure  Trained Facilitator/s  Decision-making participants  Support Staff  Laid down procedure and modus operandi  The GDSS Features As the GDSS is a group decision-facilitator and extension/expansion of DSS, most of the features/characteristics of the GDSS are similar to that of the DSS. In addition, GDSS must provide for — (a) Anonymous inputs without identifying the source of inputs to enable group decision-makers to concentrate on the merits of the input without considering who gave it. (b) Parallel communication/s to enable every group member to address issues or make comments/suggestions simultaneously. (c) Automated record keeping by anonymously recording each comment that is entered into the PC by the group member, for future review and analysis. Expert System Expert systems are meant to solve real problems which normally would require a specialized human expert (such as a doctor ). Building an expert system therefore first involves extracting the relevant knowledge from the human expert. Such knowledge is often heuristic in nature, based on useful ``rules of thumb'' rather than absolute certainties. Extracting it from the expert in a way that can be used by a computer is generally a difficult task, requiring its own expertise. A knowledge engineer has the job of extracting this knowledge and building the Expert systems have been used to solve a wide range of problems in domains such as medicine, mathematics, engineering, geology, computer science, business, law, defence and education. Within each domain, they have been used to solve problems of different types. Types of problem involve diagnosis (e.g., of a system fault, disease or student error); design (of a computer systems, hotel etc); and interpretation (of, for example, geological data). The appropriate problem solving technique tends to depend more on the Peter Jackson “An expert system is a computer program that represents and reason with knowledge of some specialist subject with a view to solving problems or giving advice” Robert Boworman and David Glover  “Highly specialized computer system capable of simulating that element of a human specialist's knowledge and reasoning tat can be formulated into knowledge chunks, characterized by a set of facts and heuristic rules) (Heuristic rules are rules of thumb accumulated by a human expert through intensive problem solving in the domain of a According to Bruce Buchanan and Reid Smith, an expert system is a compute program that a. Reasons with domain-specific knowledge that is symbolic as well as numerical. b. Uses domain-specific methods that are heuristics (plausible) as well as following procedures that are algorithmic (certain) c. Performs well in the problem area d. Retains “Flexibility” Hossein Bidgoli  ES is a series of computer programs that attempt to mimic human thought, behaviors in a specific area that has successfully being solved by human experts”  Capabilities of Expert System Duplicating Saving the Codifying and Capturing of human the transferring expertise expert’s expertise the time expertise  Characteristic of expert system Ability to Ability to Ability to draw explain their display conclusions Ability to deal reasoning or “Intelligent from complex with certainty suggest behavior” relationship decisions Ability to Not widely Limited to Inability to deal provide used or tested, relatively with mixed portable due to difficulty narrow knowledge knowledge of use problems Limitations with reference to High refine own maintenance knowledge base  Expert Systems Applications Aerospace Technology Airline / Civil Aviation (scheduling /routing) Banking and Finance (credit cards limits etc) Criminology Geological data analysis and interpretation for oil exploration drilling sites Security Analysis Strategic Goal Setting Quality control and monitoring  When to go in for ES ES has both price and value. It is difficult, expensive and time consuming to develop a sophisticated expert system. Therefore we take into consideration the following aspects. Will the system help reduce risk significantly? Will the system provide a high pay-off? Will the system performance be more consistent than human experts? Is the expertise really rare or expensive? Will the system enable developing solution faster than  Limitations of Expert System Not generally expert in managing highly sophisticated sensory inputs May not be able to tackle multi-dimensional problems They would not respond well to situations outside their range of expertise May not be able to make available common knowledge and broad ranging contextual information. Lacks human self awareness and self analysis tools If a problem is not specific and has not been solved previously by an expert then that problem is not considered suitable for the expert system implementation Components of an Expert System User Interface Explanation facility Knowledge acquisition Knowledge base, facts rules Knowledge refining system  Advantages of ES Increases output as an ES Improves quality by providing works faster than human consistent advice and by beings making reduction in error rate. Can perform as a single ES helps to preserve and human expert in many reproduce knowledge of problem situations experts.  Benefits of expert systems 1. Coding of expertise :- Helps in formalizing/codifying the reasoning ability of an organization. This leads to compilation of knowledge regarding the expertise so far held firmly to chest by the experts. 2. Enhanced understanding of business process :- It enhances the understanding of the decision making process that may in turn lead to improvement in the process. During the development process, the existing ways of DM are identified and reviewed. This helps in improving DM process  Benefits of expert systems 3. Timely availability of expertise 4. Easy replication :- Once a ES is successful at one place, it can be replicated at other places having similar decision making environments, without loss of time or opportunity 5. Eliminates routine consultation requests 6. Consistency:- Advices given here do not suffer from overlooking some factors, forgetting some of the step or personal bias 7. Line of logic 8. Strategic applications  Expert Systems Applications Aerospace Technology Airline / Civil Aviation (scheduling /routing) Banking and Finance (credit cards limits etc) Criminology Geological data analysis and interpretation for oil exploration drilling sites Security Analysis Strategic Goal Setting Quality control and monitoring 1. Knowledge base :- Contains facts about a specific subject area where rules of thumb express the reasoning procedures of an expert on the subject. It contains all the information necessary to solve a problem in a specific application area. 2. Database :- Stores information relevant to the domain 3. Inference Engine or Controller :- The inference (suggestion/implication) engine consists of encoded computer programs that perform the reasoning function of the expert system. These programs match the user questions and responses to the facts and rules captured in the knowledge base. The process continues through a series of questions until a final result is achieved. The name inference engine is derived from the ability to draw inferences from user supplied facts that are matched to the 4. User Interface :- Provides communication between the user and inference engine. This component controls user interaction, accepts commands from the computer keyboard, and displays results from the inference engine. It also includes the explanatory features, online help facilities, debugging tools, modification systems and other tools to help the user to user the system effectively. 5. Knowledge acquisition program :- These are the software tools for knowledge base development by acquiring from human experts in the form of rules and facts or learning knowledge from different problem domain. Artificial Intelligence AI “Al is a branch of computer science concerned with the study and creation of computer systems that exhibit some form of intelligence : Systems that learn new concepts and tasks, systems that can reason and draw useful conclusions about the world around us, systems that can understand natural languages and perceive and comprehend a visual scene and systems that perform other types of acts that require human types of AI system does not replace people. They liberate experts from solving common/simple problems, leaving the experts to solve complex problems. AI system help to avoid making same mistakes, and to respond quickly and effectively to a new problem situation. Artificial Intelligence (Al) is basically a technology which helps/facilitates the application of computers to areas that require knowledge, perception, reasoning, understanding and cognitive abilities which distinguish the human behavior from machines like computers. It is the science and engineering of making intelligent machines, especially intelligent computer  Artificial Intelligence (definition) “AI is a branch of computer science that is concerned with the automation of intelligent behavior ” “AI is a series of related technologies that attempt to simulate and reproduce human behavior, including thinking, speaking, feeling and reasoning.”  AI canvas (Scope --- Area) Expert systems Intelligent agents Neural Networks Speech recognition Learning systems Fuzzy Logic Natural Language Processing Robotics Vision recognized system  Neural Network A machine learning technique which imitates the processes of the brain Artificial Neural Network :- The concept of ANN came from the biological sensory mechanisms, where the neural signals are transmitted to the rain and processed. Resembles human trail and error learning and has tremendous ability to recognize the underlying relationship between input and output data.  Intelligent Agents An IA is a software program that can automatically accomplish tasks for a person. A agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Basically every agent is characterized by the following :- 1. Environment:- Conditions under which sensors work 2. Sensors 3. Effectors:- Response to that stimulus (perception)that is provided by effectors An intelligent agent should be ready to work with other agents and it should respect real time constraints imposed by the environment. IA have the potential to become one of the most important tool of information technology  Fuzzy Logic Is an approach to computing, based on “degrees of truth” rather than the usual “true or false” (1 or 0). Example today is a sunny day, might be 100% true if there are no clouds, 80% true if there are a few clouds, 50% true if its hazy and )0% true if it rains all day. Fuzzy logic works with ranges of values, solving problems in a way that more resembles human logic For generations, people have attempted to make smart machines to perform business activities that require intelligence. Designed to influence the capabilities of human rather than replace them. AI enabled applications can be used to increase productivity, quality and customer satisfaction. Intelligent systems can be used to facilitate communication and collaboration among people within and between organizations, expanding the capabilities of the latter. Intelligent systems help us overcome the information overloading, enabling us to quickly compare and analyze data and to conduct business better. These systems act as tutors and advisors to people.  Attributes N. I A. I Ability to use sensors (eyes, ears, touch, smell) High Low Ability to be creative and imaginative H L Ability to learn from past experience H L Ability to acquire a large amount of external H H information Ability to make complex calculations L H Ability to transfer information L H Ability to make series of calculations, rapidly and L H accurately  Pre-requisite of AI Should understand what is common sense Understand facts and relationship among facts Be able to manipulate qualitative data Be able to interact with humans in a free format fashion Be able to deal with new situations based on previous learning. Be able to deal with exceptions and discontinuity  AI application Diagnosis and trouble shooting Portfolio Management Asset liability management Criminology Geology (Drilling/Oil Exploration site) Manufacturing, Production and Scheduling Project Management Factory Management One game with strong AI ties is chess. World- champion chess playing programs can see ahead twenty plus moves in advance for each move they make. In addition, the programs have an ability to get progress-ably better over time because of the ability to learn. Chess programs do not play chess as humans do. In three minutes, Deep Thought (a master program) considers 126 million moves, while human chess-master on average considers less than 2 moves. Herbert Simon suggested that human chess masters are familiar with favorable board positions, and the relationship with thousands of pieces in small areas. Computers on the other hand, do not take hunches into account. The next move It must be remembered that Al Systems are not to replace human decision-making completely. They are meant to replicate/emulate human decision-making for certain types of clearly and well-defined problems – the Chess Matches between Gary Kasporov (Natural Intelligence) and Deep Junior (Artificial Intelligence) being a classic example of AI/ES. Like other computer-based information systems, the overall purpose of Al systems/ applications in business is to help the organizations/managers achieve the goals. Al has, no doubt, started getting acceptance and credibility. The success of Al as a mass-market technology, however, would depend upon a number of practical factors like : Cost Personnel with requisite skills Corporate Management attributes The demonstration of a variety of commercial Al success stories to be a role model for others to follow.  EIS/ESS Executive Information System Executive Support System Used in situations where the TOP Management is bombarded with too much of data leading to INFORMATION OVERLOADING, resulting in confusion and dilemma EIS/ESS is developed to support DM at Top Management Level It is used by the Top Executes as they require specialized support while making strategic decisions ESS/EIS is required and used at fairly senior level including members of the Board of directors and executives with titles of CEO, COO, CFO  What is ESS Specialized DSS that includes all hardware, software, data, procedures and people used to assist senior/top executives within the organization. The primary goal of EIS/ESS is to obtain data from a variety of sources, integrate and aggregate that data and display the resulting information in an easy to use comprehensible format  Definition “A computer based system that serves the information needs to Top Executives. It provides rapid access to timely information and direct access to Management Reports. It is very user friendly and is supported by graphics, providing exception reporting and drill down capabilities. It can also be easily connection with on-line information services and electronic mail” (Drill down capability enables the users to break down data in details and identifies problems and opportunities” “An ESS is a comprehensive executive support system that goes beyond the EIS to include communication, office automation, analysis support and intelligence”. An EIS is a ‘computer based information system that combines the decision-maker’s imagination and judgement with the computer’s ability to store, retrieve, manipulate, compute and report internal and external information  EIS/ESS CAPABILITY Provides access to global information Enables user to use external data extensively Enables to address ad hoc queries/analysis Shows trends, ratios and deviations Provides access to historic and also the latest data Highlights problem indicators and supports open ended problem Filters, compresses and tracks critical data and also provides forecasting capability. Can utilize hypertext and hypermedia EIS/ESS Characteristics Easy to use Produces correct information Relevant and valid information Contains sophisticated GUI Facilitates access from many places Secure, reliable and confidential access and access procedure Supports defining overall Mission, Vision and strategy Supports strategic management Can help in situation where risk / uncertainly is very high  Flexible and ease of use Information al Provides timely information with short response time and quick retrieval Produces correct information EIS/ESS User Characterist Interface ics Produces relevant information Executive / Produces Validated Managerial Information  Contains sophisticated interfaces – GUI Informational Facilitates access from many places EIS/ESS Provides secure, reliable and Characteris confidential access tics User Is custom made to suit various Interface types of management styles Futuristic orientation Managerial Support for strategic management / Executive Can help with situation that have a high degree of risk / uncertainty  Futuristic orientation Informational Support for strategic management Can help with situation that have a high User degree of risk / uncertainty Interface Is linked with value added business EIS/ESS processes Characteristic s Supports access to external databases Has Capabilities such ad Drill Down, Exceptional Reporting and Critical Success Factor Identification Managerial / Executive Has a high result / performance orientation  Factors contributing to EIS/ ESS Internal Factors External Factors  Internal Factors Need for timely & accurate information Need for improved communications Need for access to operational data Need for rapid status updates on various business activities Need for access to corporate databases Need for ability to identify historical trends External Factors Increased and intensifying global competition Rapidly changing business environment Need to be more pro-active Need to access external database  Advantages of EIS Easy and designed for top level executives Provides timely delivery of company summary information Improves tracking information EIS filters data for management Offers efficiency to decision making Does “Root Cause Analysis” instead of “Fix It” mode