UNIT I

Management information system:

A Management Information System is an information system that evaluates, analyzes, and processes an organization's data to produce meaningful and useful information based on which the management can take right decisions to ensure future growth of the organization.

Information systems and technologies have become a vital component of successful businesses and organizations.  They thus contribute an essential field of study in business administration and management.  Information technologies including internet-based information systems can help all kinds of business improve the efficiency and effectiveness of their business processes, managerial decision making, and workgroup collaboration and thus strengthen their competitive positions in a rapidly changing marketplace.

The field of information systems encompasses many complex technologies, abstract behavioural aspects and specialized applications in countless business and non-business areas.  As a manager or business end user, it is not necessary to absorb all of this knowledge. 

A conceptual framework is given which outlines what end users need to know about information systems?  This framework focuses on 5 major areas of information systems knowledge needed by business end users.

i)                    Foundation Concepts:  Fundamental behavioural and technical concepts that will help to understand the importance and use of information systems.

ii)                  Technology concepts:  major concepts, developments and management issues in information technology – (i.e) hardware, software, network, database management and other information processing technologies.

iii)                Application concepts:  The major uses of information systems are for the operations, management, and competitive advantage of an enterprise.

iv)                Development Concepts:  How end users/information specialists develop information systems solutions to business problems using fundamental problem-solving and developmental technologies.

v)                  Management concepts:  The challenges of effectively and ethically managing the resources and business strategies involved in using information technology at the end user enterprise and global levels of a business. 

What is Management Information System (MIS)?

MIS is not new; only its computerization is new.  Before computers, MIS techniques existed to supply managers with the information that would permit them to plan and control operations.  The computer has added one or more dimensions, such as speed, accuracy, and increased volumes of data, that helps in effective decision making by the management.   The scope and purpose of  MIS  is better understood if each part of the term is well defined.  Thus,

Management  Management comprises the processes or activities that describe what managers do in the operation of their organization: plan, organize, initiate, and control operations.  They plan by setting strategies and goals and selecting the best course of action to achieve the plan.  They organize the tasks necessary for the operational plan, set these tasks up into homogeneous groups and assign authority delegation.  They control the performance o fthe work by setting performance standards and avoiding deviations from standard.

            Because decision making is such a fundamental prerequisite to each of the foregoing processes, the job of an MIS becomes that of facilitating decisions necessary for planning, organizing, and controlling the work and functions of the business.

Information

  Data must be distinguished from information, and this distinction is clear and important for our purposes.  Data are facts and figures that are not currently being used in a decision process and usually take the form of historical records that are recorded and filed without immediate intent to retrieve for decision-making.  An example would be any one of the supporting documents, ledgers, and so on that comprise the source material for profit and loss statements. 

            Information consists of data that have been retrieved, processed, or otherwise used for informative purpose, argument or as a basis for forecasting or decision-making.  Example:  ledger to be used by internal management for profit planning and control.

Systems

A system can be described simply as a set of elements joined together for a common objective.  A subsystem is a part of larger system with which we are concerned.  All systems are parts of larger systems.  For ex. Organisation is the system and the parts (divisions, departments, functions, units etc.) are the subsystems.

            Thus MIS is a system that is designed to provide information support to management for decision-making purpose.

Definition of MIS

1) Gordon B.Davis defines Management Information System as

(i)                 An integrated user machine system,

(ii)               For providing information,

(iii)             To support the operations, management and decisionmaking functions in an organization.

The system utilizes:

(i)  Computer hardware and software,

(ii)Manual procedures,

(iii)             Models for analysis, planning, control, and decision-making, and

(iv)             A database.

2) Jerome Kanter defines MIS as

            “A system that aids management in making, carrying out and controlling decisions”

Characteristics of MIS

Jerome Kanter in his work titled “Management Information Systems” mentions several characteristics of MIS.  Some of them are as follows:

(i)                 MIS is management oriented: The designing of MIS takes care of the managers, who meet the information requirement.  The development of the system starts after deciding the management needs and keeping in view the overall objectives of the management.

(ii)               Management directed:  Since MIS requires heavy planning and investment; management is deeply involved in the design, implementation and maintenance of the system.

(iii)             Integrated System:  MIS is the ‘Catalyst and Nervecentre’ of an organization.  It has a number of subsystems.  In order to make these systems effective, it becomes necessary that they have to be viewed as an integrated system, so that the result is balanced.  It binds together databases of all subsystems of the business system and through information interchange, integrates the organization.

(iv)             Avoids redundancy in data storage: Since MIS is an integrated system, it avoids unnecessary duplication and redundancy in data gathering and storage.

(v)               Common data flow:  To achieve the objective of integration and to avoid duplication and redundancy, data capturing is usually confined to original source and it is done only once.  Common data flow tries to utilize minimum data processing effort and strives to minimize the number of output documents and reports.  This type of integration can avoid duplication, simplify operations and produce an effective MIS.  But separate files should be opened which is significant to one application with the use of common data flow

(vi)             Heavy Planning element:  Design and implementation of MIS requires detailed and meticulous planning of such activities as acquisition and deployment of hardware, software, human ware, data processing operations, information presentation and feedback.

(vii)           Subsystem concept: MIS gives provision for breaking into various subsystems based on the activity as well the functions of the organizations, so that effective implementation of each subsystem is possible at a time.

(viii)         Common database: It acts as a master that holds the functional subsystems together.  It achieves this aim by allowing access to different master files of data to several functional subsystems.  Data requirements for different levels of management also support the need of more than one database, unique databases and common database.

(ix)             Flexibility and ease of use: The MIS is designed flexible enough to accommodate new requirements.  The system is easy to operate so that not much computer skills are required on the part of the user to access database for information or for carrying out special analysis of data.

Objectives of MIS

 Capturing Data: Capturing contextual data, or operational information that will contribute in decision making    from various internal and external sources of organization.

Processing Data: The captured data is processed into information needed for planning, organizing, coordinating, directing and controlling functionalities at strategic, tactical and operational level. Processing data means:

 making calculations with the data

 sorting data

 classifying data and

 summarizing data

Information Storage: Information or processed data need to be stored for future use.

 Information Retrieval: The system should be able to retrieve this information from the storage as and when required by various users.

 Information Propagation: Information or the finished product of the MIS should be circulated to its users periodically using the organizational network.

CHARACTERISTICS OF MIS

Following are the characteristics of an MIS:

Ø  It should be based on a long-term planning.

Ø  It should provide a holistic view of the dynamics and the structure of the organization.

Ø  It should work as a complete and comprehensive system covering all interconnecting sub-systems within the organization.

Ø  It should be planned in a top-down way, as the decision makers or the management should actively take part and provide clear direction at the development stage of the MIS.

Ø  It should be based on need of strategic, operational and tactical information of managers of an organization.

Ø  It should also take care of exceptional situations by reporting such situations.

Ø  It should be able to make forecasts and estimates, and generate advanced information, thus providing a competitive advantage. Decision makers can take actions on the basis of such predictions.

Ø  It should create linkage between all sub-systems within the organization, so that the decision makers can take the right decision based on an integrated view.

Ø  It should allow easy flow of information through various sub-systems, thus avoiding redundancy and duplicity of data. It should simplify the operations with as much practicability as possible.

Ø  Although the MIS is an integrated, complete system, it should be made in such a flexible way that it could be easily split into smaller sub-systems as and when required.

Ø  A central database is the backbone of a well-built MIS.

TYPES OF MIS

A management information system (MIS) is a computer-based system that provides the information necessary to manage an organization effectively. An MIS should be designed to enhance communication among employees, provide an objective system for recording information and support the organization's strategic goals and direction.

1. TRANSACTION PROCESSING SYSTEM

Transaction-processing systems are designed to handle a large volume of routine, recurring transactions. They were first introduced in the 1960s with the advent of mainframe computers. Transaction-processing systems are used widely today. Banks use them to record deposits and payments into accounts. Supermarkets use them to record sales and track inventory. Managers often use these systems to deal with such tasks as payroll, customer billing and payments to suppliers. 2. OPERATION INFORMATION SYSTEM

Operations information systems were introduced after transaction-processing systems. An operations information system gathers comprehensive data, organizes it and summarizes it in a form that is useful for managers. These types of systems access data from a transaction-processing system and organize it into a usable form. Managers use operations information systems to obtain sales, inventory, accounting and other performance-related information

3. DECISION SUPPORT SYSTEM

A DSS is an interactive computer system that can be used by managers without help from computer specialists. A DSS provides managers with the necessary information to make informed decisions. A DSS has three fundamental components: database management system (DBMS), which stores large amounts of data relevant to problems the DSS has been designed to tackle; model-based management system (MBMS), which transforms data from the DBMS into information that is useful in decision-making; and dialog generation and management system (DGMS), which provides a user-friendly interface between the system and the managers who do not have extensive computer training.

 4. EXPERT SYSTEMS AND ARTIFICIAL INTELLIGENCE

Expert systems and artificial intelligence use human knowledge captured in a computer to solve problems that ordinarily need human expertise. Mimicking human expertise and intelligence requires the computer to do the following: recognize, formulate and solve a problem; explain solutions; and learn from experience. These systems explain the logic of their advice to the user; hence, in addition to solving problems they also can serve as a teacher. They use flexible thinking processes and can accommodate new knowledge.

BENEFITS OF MIS

The benefits of MIS systems to businesses, governments, scientists, universities, students, nonprofits and all other entities are diversified. Some of the examples include the following:

 Implementation of Management by Objectives (MBO) techniques: MIS allows all participants, both management and staff, to view, analyze, and interpret useful data to set goals and objectives.

 Generates competitive advantages: Businesses succeed or fail based on how they face competitive challenges. MIS, if implemented properly, provides a wealth of information to allow management to construct effective plans to meet, and beat, their competitors.

 Fast reaction to market changes: The victory often goes to the quick, not necessarily the best. MIS can deliver facts, data and trends to businesses with lightning speed. Having this information allows companies to react quickly to market changes, regardless of the type (positive or negative) of volatility.

EVOLUTIONS OF MIS

Before the 1960s, the role of most information systems was simple. They were mainly used for electronic data processing (EDP), purposes such as transactions processing, record-keeping and accounting. EDP is often defined as the use of computers in recording, classifying, manipulating, and summarizing data. It is also called transaction processing systems (TPS), automatic data processing, or information processing. Transaction processing systems as the name implies process data gotten from business transactions, update operational databases, and produce business documents. Examples: sales and inventory processing and accounting systems.

In the 1960s, another role was added to the use of computers: the processing of data into useful informative reports. The concept of management information systems (MIS) was born. This new role focused on developing business applications that provided managerial end users with predefined management reports that would give managers the information they needed for decision-making purposes.

By the 1970s, these pre-defined management reports were not sufficient to meet many of the decision-making needs of management. In order to satisfy such needs, the concept of decision support systems (DSS) was born. The new role for information systems was to provide managerial end users with ad hoc and interactive support for their decision-making processes.

Decision support systems (DSS) – provide interactive ad hoc support for the decision-making processes of managers and other business professionals. Examples: product pricing, profitability forecasting and risk analysis systems.  In the 1980s, the introduction of microcomputers into the workplace ushered in a new era, which led to a profound effect on organizations. The rapid development of microcomputer processing power (e.g. Intel‘s Pentium microprocessor), application software packages (e.g. Microsoft Office), and telecommunication 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 a centralized corporate information services department. It became evident that most top executives did not directly use either the MIS reports or the analytical modelling capabilities of DSS, so the concept of executive information systems (EIS) was developed.

Executive information systems – provide critical information from MIS, DSS and other sources, tailored to the information needs of executives. Examples: systems for easy access to analysis of business performance, actions of all competitors, and economic developments to support strategic planning Moreover, breakthroughs occurred in the development and application of artificial intelligence (AI) techniques to business information systems. With less need for human intervention, knowledge workers could be freed up to handle more complex tasks. Expert systems (ES) and other knowledge management systems (KMS) also forged a new role for information systems. ES can serve as consultants to users by providing expert advice in limited subject areas.

Expert systems: knowledge-based systems that provide expert advice and act as expert consultants to users. Examples: credit application advisor, process monitor, and diagnostic maintenance systems.

Knowledge management systems: knowledge-based systems that support the creation, organization and dissemination of business knowledge within the enterprise. Examples: intranet access to best business practices, sales proposal strategies and customer problem resolution systems.

The mid- to late 1990s saw the revolutionary emergence of enterprise resource planning (ERP) systems. This organization-specific form of a strategic information system integrates all facets of a firm, including its planning, manufacturing, sales, resource management, customer relations, inventory control, order tracking, financial management, human resources and marketing – virtually every business function. The primary advantage of these ERP systems lies in their Types of Information Systems

Transaction Processing Systems

Transaction processing systems (TPS) are the basic business systems that serve the operational level of the organization. A transaction processing system is a computerized system that performs and records the daily routine transactions necessary to the conduct of the business [4]. At the lowest level of the organizational hierarchy we find the transaction processing systems that support the day-to-day activities of the business

Process Control Systems

Process control systems is Monitor and control industrial or physical processes. Examples: petroleum refining, power generation, and steel production systems. For example, a petroleum refinery uses electronic sensors linked to computers to monitor chemical processes continually and make instant (real-time) adjustments that control the refinery process [1] .A process control system comprises the whole range of: equipment, computer programs, operating procedures

Enterprise Collaboration Systems (Office Automation Systems) Office automation systems are one of the most widely used types of information systems that will help managers control the flow of information in organizations [9]. Enterprise collaboration systems (office automation systems) are enhance team and workgroup communications and productivity [1].Office automation systems are other types of information systems are not specific to any one level in the organization but provide important support for a broad range of users [7]. Office information systems are designed to support office tasks with information technology. Voice mail, multimedia system, electronic mail, video conferencing, file transfer, and even group decisions can be achieved by office information systems

Decision Support Systems

A Decision Support System is a computer based system intended for use by a Particular manager or usually a group of managers at any organizational level in

Expert Systems

Expert systems are the category of AI which has been used most successfully in building commercial applications .According to O’Brien & Marakas  Expert systems are Knowledge-based systems that provide expert advice and act as expert consultants to users. According to Patterson an expert system is a computer program that tries to emulate human reasoning. According to Shim Expert System is a set of computer programs that perform a task at the level of a human expert.

Strategic Information Systems

Strategic information systems apply information technology to a firm’s products, services, or business processes to help it gain a strategic advantage over its competitors. According to Belle, et al.,Strategic information systems are an important special type of organizational information system is used to secure or sustain competitive advantage in the market place

KNOWLEDGE MANAGEMENT SYSTEM

All the systems we are discussing here come under knowledge management category. A knowledge management system is not radically different from all these information systems, but it just extends the already existing systems by assimilating more information.

As we have seen, data is raw facts, information is processed and/or interpreted data, and knowledge is personalized information.

WHAT IS KNOWLEDGE

v  Personalized information

v  State of knowing and understanding

v  An object to be stored and manipulated

v  A process of applying expertise

v  A condition of access to information

v  Potential to influence action

SOURCES OF KNOWLEDGE OF AN ORGANISATION

Intranet

 Data warehouses and knowledge repositories

Decision support tools

 Groupware for supporting collaboration

 Networks of knowledge workers

 Internal expertise

Definition of KMS

A knowledge management system comprises a range of practices used in an organization to identify, create, represent, distribute, and enable adoption to insight and experience. Such insights and experience comprise knowledge, either embodied in individual or embedded in organizational processes and practices.

PURPOSE

Ø  Improved performance

Ø  Competitive advantage

Ø  Innovation

Ø  Sharing of knowledge

Ø  Integration

Ø  Continuous improvement by:

Ø  Driving strategy

Ø  Starting new lines of business

Ø  Solving problems faster

Ø  Developing professional skills

Ø  Recruit and retain talent

Conceptual Structure of MIS

The conceptual structure of MIS is defined as a federation of functional subsystems, each of which is divided into four major information processing components like transaction processing, operational control information system support, management control information support and strategic planning information system support.  Each of the functional subsystems of the information system has some unique data files that are used only by that subsystem.  There are also files that need to be available for general retrieval.  These files are organized into a general database managed by a database management system.  There is also common software in addition to application programs written specially to each subsystem.  Each subsystem has linkage to the common applications that serve multiple functions.  There are also many analytical and decision models that can be used by many applications.

The Management Information System as a Pyramid

Given below is MIS as a pyramid.  The amount of information processing resources required varies by level of management activity.  Transaction processing is substantially more significant in terms of processing time, data volume etc., than strategic planning and provides the base for all other internal information support.  The concept of  the large transaction processing base and a fairly small strategic planning component can be visualized as a pyramid.  The lower part of the pyramid describes structured, well defined procedures and decisions; while the top part represents more adhoc, unstructured processes and decisions.  The bottom levels are of more use to clerical personnel and lower-level managers, while the higher levels apply primarily to top management.

EXPERT SYSTEMS

• One of the most practical & widely implemented applications of artificial intelligence in business is the development of expert systems and other knowledge-based information systems.
• A Knowledge-Based Information System (KBIS) adds a knowledge base to the major components found in other type of computer-based information systems.
• An Expert System (ES) 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 provides answer to questions in a very specific problem area by making human like inferences about knowledge contained in a specialised knowledge base.
• They must be able to explain their reasoning process and conclusions to a user.
• So expert systems can provide decision support to end users in the form of advice from an expert consultant in a specific problem area.

Components of an Expert System:

            The components of an expert system include a knowledge base and software modules that perform inferences on the knowledge and communicate answers to a user’s questions.

 

Knowledge Base:

• The Knowledge Base of an expert system contains (1) facts about a specific subject area (for ex., John is an analyst) and (2) heuristics (rules of Thumb) that express the reasoning procedures of an expert on the subject (for ex, If John is an analyst, Then he needs a workstation)
• There are many ways that knowledge is represented in expert systems. Examples are rule-based, frame based, object-based and case-based methods of knowledge representation.

Methods of Knowledge Representation:

• Case-Based Reasoning Representing knowledge in an expert system’s knowledge base in the form of cases that is example of past performance, occurrences and experiences.
• Frame-Based Knowledge represented in the form of a hierarchy or not-work 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 knowledge Knowledge represented as a 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 knowledge 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).

Software Resources:

·         An expert system software package contains an inference engine and other programs for refining knowledge and communicating with users.

• The Inference engine program processes the knowledge (such as rules and facts) related to a specific problem.
• It then makes associations and inferences resulting in recommended courses of action for a user.
• User interface programs for communicating with end users are also needed, including an explanation program to explain the reasoning process to a user if requested.
• Knowledge acquisition programs are not part of an expert system but are software tools for knowledge base development, as are expert system shells, which are used for developing expert systems.

Expert System Applications:

• Using an expert system involves an interactive computer based session in which the solution to a problem is explored, with the expert system acting as a consultant to an end user.
• The expert system asks questions of the user, searches its knowledge base for facts and rules or other knowledge, explains its reasoning process when asked, and gives expert advice to the user in the subject area being explored.
• Expert systems are being used for many different types of applications and is used to accomplish one or more generic uses.
• Ex. ADCAD (Advertising Communication Approach Design) is an Expert systems to assist and agencies.

Major Application Categories of E.S.

• Decision Management – Systems that appraise situations or Consider alternatives and make recommendations based on criteria supplied during the discovery process:
• Loan portfolio analysis
• Employee performance evaluation
• Insurance Underwriting
• Demographic forecasts
• Diagnostic/troubleshooting – System that infer underlying causes from reported symptoms & history:
• Equipment Calibration
• Help desk operations
• Software debugging
• Medical diagnosis
• Maintenance/Scheduling – Systems that prioritise and schedule limited or time-critical resources
• Maintenance scheduling
• Production scheduling
• Education scheduling
• Project Management
• Design/Configuration – Systems that help configure equipment components, given existing constraints
• Computer option installation
• Manufacturability studies
• Communication networks
• Optimum Assembly plan
• Selection/Classification – Systems that help users choose products or processes, often from among large or complex sets of alternatives.
• Material selection
• Delinquent account identification
• Information classification
• Suspect identification
• Process Monitoring/Control – Systems that monitor and control procedures or processes
• Machine control (including robotics)
• Inventory Control
• Production Monitoring
• Chemical testing

Developing Expert Systems:

• The easiest way to develop an expert system is to use an expert system shell as a development tool
• An expert system shell is a software package consisting of an expert system without its kernel, that is knowledge base.
• This leaves a shell of software (the interface engine and user interface programs) with generic inferencing and user interface capabilities
• Other development tools (such as rule editors and user interface generators) are added in making the shell a powerful expert system development tool
• Expert system shells are now available as relatively low-cost software packages that help users develop their own expert systems on microcomputers. They allow trained users to develop the knowledge base for a specific expert systems application.
• For ex. One shell uses a spreadsheet format to help end users develop IF-THEN rules, automatically generating rules based on examples furnishing by a user.
• Once a knowledge base is constructed, it is used with the shell is inference engine & user interface modules as a complete expert system on a specific subject area.
• Other software tools may require an IT specialist to develop expert systems.

Knowledge Engineering:

• A Knowledge Engineer is a professional who works with exports to capture the knowledge (facts and rules of thumb) possess.
• The Knowledge engineer then builds the Knowledge base (and the rest of the expert systems if necessary), using an iterative, prototyping process until the expert system is acceptable.
• Thus, Knowledge engineers perform a role similar to that of systems analysts in conventional informational system development.
• Once the decision is made to develop an expert system, a team of one or domain experts and a Knowledge engineer may be found.
• Or experts skilled in the use of expert system shells could develop their own expert systems.
• If a shell is used, facts and rules of thumb about a specific domain can be defined and entered into a knowledge base with the help of a rule editor or other knowledge acquisition to.
• A limited working prototype of the knowledge base is then constructed, tested and evaluated using the inference engine and user interface programs of the shell.
• The knowledge engineer and domain experts can modify the knowledge base, then retest the system and evaluate the results.
• This process is repeated until the knowledge base and the shell result in an acceptable expert system.

The value of Expert Systems:

Obviously,

• Expert Systems are not the answer to every problem facing an organisation
• People using other types of information systems do quite well in many problem situations.
• So, what types of problems are most suitable for expert systems solutions?
• The answer is to look into the current applications of expert systems & criteria for application of expert systems.

Suitability Criteria for Expert Systems:

• 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 neded that only a few people posses.
• Complexity: Solution to the problem is a complex task that requires logical inference processing, which would not be handled as well bly conventional information processing.
• Structure: The solution process must be able to cope with ill-structured, uncertain, missing and conflicting data, and a problem situation that changes with the passage of times.
• Availability: An expert exists who is articulate & Cooperative, and who has the support of the management and end users involved in the development of the proposed system.

Benefits:

• An expert system captures the expertise of an expert of group of experts in a computer-based information system.
• Thus, it can outperform a single human expert in many problem situations
• That’s because an expert system is faster and more consistent, and has the knowledge of several experts, and does not get tired or distracted by overwork or stress.
• Expert systems also help preserve and reproduce the knowledge of exports.
• They allow a company to preserve the expertise of an expert before she leaves the organisation.
• This expertise can then be shared by reproducing the software and knowledge base of the expert system
• This allows novices to be trained & supported by copies of an expert systems distributed throughout an organisation.
• Finally, expert systems can have the same competitive advantages as other type of I.T.
• That is, the effective use of E.S can allow a firm to significantly improve the efficiency of its business processes, or produce new knowledge based products and services.

Limitations:

• Limited focus
• Inability to learn
• Maintenance problems
• Developmental cost
• Excel only in solving specific types of problems in a limited domain of knowledge
• They fail miserably in solving problems requiring a broad knowledge base and subjective problem solving.
• They do well with specific types of operational or analytical tasks, but falter at subjective managerial decision-making.
• For ex. An expert system might help a financial consultant develop alternative investment recommendations for a client. But it could not adequately evaluate the ance of current political, economic & societal developments or the personal dynamics of a session with a client. Such important factors would still have to be handled by the human consultant before a final investment decision could be reached.
• E.S. may also be difficult and costly to develop and maintain properly.
• The cost of knowledge Engineers, lost expert time, and h/w & s/w resources may be too high to offset the benefits expected from some applications.
• Also E.S. can’t maintain themselves (i.e.) they can’t learn from experience but must be taught of any development arises in their subject areas.
• However, some of these limitations can be overcome by combining E.S. with A.I. technologies. Such as fuzzy logic and neural networks or by the use of E.S. developmental tools that make the job of development & maintenance easier.