MANAGEMENT INFORMATION SYSTEM

DATA: data is raw facts and figures typically about both physical phenomena or business transactions. More specifically data are objective measurement of attributes (characteristics) of entities (such as people, place, things and events).

INFORMATION: Processed data is information. Thus we can define information as data that have been converted into a meaningful and useful context for specific end users.

Difference between Data and Information:

DATA INFORMATION

Data is generally disorganised and disintegrated in the form

Information is properly arranged, classified and organised.

Data is in raw form Information is in finished form

Data can not be understood or made use of by the users

Information can be understood or made used by the users

Data does not depends upon information

Information is based upon and derived from the data.

DATA PROCESS INFORMATION DECISION

ACTION

SPECIFIC IMPLEMENTATION

CLASSIFICATION OF INFORMATION SYSTEM

INFORMATION SYSTEM

OPERATION SUPPORT SYSTEM

MANAGEMENT SUPPORT SYSTEM

T.P.S. P.C.S. E.C.S. M.I.S. D.S.S. E.I.S.

T.P.S.- Transaction Process System

P.C.S.- Process Control System

E.C.S.- Enterprise Collaboration System

M.I.S.- Management Information System

D.S.S.- Decision Support System

E.I.S.- Executive Information System

Operation Support System

The information system which supports day to day operations at the lower level management such as cash management, credit management, billing, invoice, selling, purchasing, inventory management, salary and wage records, etc.

TPS (Transaction Processing System)

Transaction is a process where 2 or more parties are involved in order to exchange of 1 commodity for exchange of other. There are 2 types of processing:

a) Batch Processing

b) Real Time Processing

Batch Processing Real Time Processing

Processing does not happen then and there but after a stipulated period of time

Processing happens then and there.

It is slow process It is fast process

Provides obsolete and old information Provides most updated information

Cost effective/less costly because load is divided into batches

Costly because good and advance quality of processor is required to support the load

Less possibility of errors eg. Depositing a cheque in a bank manually

More prone to errors eg. When we get cash bill after purchasing items.

P.C.S. (Process Control System)

System regulating any kind of process. PCS consists of that broad category of information system in which any kind of production process which is physical, chemical, biological, bio-chemical, production process related to drugs, automobiles etc. In any of these process, production is controlled with help of information system.

E.C.S. (Enterprise Collaboration System)

ECS is that category of information system which helps in collaboration and coordination among the various stakeholders of business using the internet platform such as intranet and extranet, where in the basic idea is to formulate a cross functional, multi disciplinary team in order to share assets, resources and take GD on virtual basis overcoming the barriers related to time, cost, infrastructural and distance.

Some ECS: mobile conferencing, video conferencing, audio conferencing, WAP, electronic meeting system, GD, e-mail, voice mail, extranet, e-mail, voice mail, FTP

MANAGEMENT SUPPORT SYSTEM

It supports critical decision taking at top level, middle level and top level management. MSS is more specialized system.

D.S.S. (Decision Support System)

Decision means selecting the best alternative among different available alternatives.

Intelligence Phase

Design Phase

Choice Phase

Identifying Problem

Develop Alternatives

Selection of Best Alternative

Herbert Simon approach to Decision Making

Problem can be faced at any stage of an organisation. In this phase in order to understand the problem you are required to apply your brain, intelligence, various statistical data, logical ability etc., designing various alternative which can be developed for a single problem

MANAGEMENT INFORMATION SYSTEM

Provide information in the form of prescribed reports and displays to support business decision making. Eg. Sales analysis, production performance, and cost trend reporting system.

EXECUTIVE INFORMATION SYSTEM

Provide critical information from many sources tailored to the information needs of executives. Eg. Systems for easy access to analyses business performance, action of competitors and economic developments to support strategic planning.

PROCESS OF GENERATING INFORMATION

Process of generating information begins with process of data collection. There are several methods of data collection. The choice of method has an impact on the quality of information. Some of the methods of data collections are discussed as under:

ObservationIt is a first hand knowledge by a person who is responsible for collecting data. Example: Visit to the customer for assessing the customer complaints. A visit to assess the accidental damage for insurance payment purpose. The main advantage of first hand knowledge is less response bias. An accuracy of observation will decide the response.

ExperimentationConducting an experiment can collect the information on a specific parameter. For example: conducting a control experiment can assess the impact of a new fertilizer dose on the yield of a crop. Conducting a test market trial can assess the impact of a new packaging of a product. The quality of information will be a function of design of experiment.

Survey

Under this method a part (sample) of population is covered on specific aspects for the purpose of information collection, However, the quality of the information depends on the instruments such as questionnaire used for collecting the information, Examples of Survey are market surveys, opinion polls, census etc.

Subjective EstimationIn the absence of experiment, surveys, and first hand information,

expert opinion may be called to collect the information. The information may be collected from more than one expert and in more than one round of collection from the same expert. The multiple set of information/data can be analyzed/processed to get the right information with minimum bias. Data pertaining to future like alternate source of energy, the life style and food habits of later half of 21st century are collected using subjective estimations. These estimates are called subjective since no probability law is being used for collecting the information.

Transaction ProcessingSources of data for this method are ledgers, payrolls, stock statements and sales reports of an organization. The data collected from these sources will require the processing to get meaningful information.

PublicationsIn this method, data are collected from secondary sources. The sources are publication of financial institutions, industrial organization, universities, consulting firm's etc. This method of data collection is less costly.

Government AgenciesSome of the state agencies in all countries publish reports about the basic parameters of the economy and other facets of the society. For example: Publications of Central Bank of a country, in case of India publications such as RBI Annual Report, Report on Currency and Finance, Economic survey etc. falls in this category. These reports are available to researchers, planners and policy makers. In addition, these reports are also available to public. However, this information may not be directly useful but one can make use of this information. In fact all activities in an organization generate data.

Strategic Roles of Information System

A company has competitive advantage over other companies when it sustains marketability and greater market share. The area of specialisation is above any other company in the industry. i.e. you are ahead your competitors.

Who are you competitors?

1. Me tools

2. Substitutes

3. New entrants

Me tools: These are identical products from different companies. i.e. the have similar types product, similar technology and similar target area. Eg. Refrigerators from samsung and LG

Substitutes: replacement of products i.e. tea and coffee

New Entrants: who are now coming up with new product of the same category. i.e. LG producing electronics now entering in to FMCG

If any firm can overcome 5 forces of business the firm is able to achieve competitive advantage in the market

Michael Porter’s 5 forces Model

THREATS FROM

NEW ENTRANTS

BARGAINING POWER OF SUPPLIERS

BARGAINING POWER OF CUSTOMERS

INTERNAL RIVALRY AMONG

FIRMS

THREATS FROM

ME TOOLS &SUBSTITUTE

FIRM’SCOMPETITIVE ADVANTAGE

Bargaining power of customer is due to high supply and low demand. Customer become choosy.

Bargaining power of supplier is due to high demand and low supply. Eg. Maggi

STRATEGIES TO ACHIEVE COMPETITIVE ADVANTAGES

1. Cost Leadership

2. Innovation: New offer and never before

3. Differentiation: Unique product and features

4. Diversification

Related Diversification- Johnson & Johnson

Non Related Diversification-ITC

5. Strategic Alliances: Alliance means ASSOCIATION

Mergers: A& B – AB company

Acquisition/Takeover: A buys B

Joint Ventures: A&B for project. Will separate after project completes

Technology Collaboration: Technical Know how is provided by one company to another

ARTIFICIAL INTELLIGENCE

Artificial Intelligence is that branch of science which deals with computer in which the goal is to develop computer which can think, see, hear, talk and feel or in other words developed computer which can perform functions equivalent to human intelligence.

Artificial Intelligence is multi disciplinary because it has borrowed its principles from:

• Mathematics

• Operation research

• Statistics

• Psychology

• Engineering

Application areas of Artificial Intelligence

Artificial Intelligence

Cognitive Science Applications

Robotics ApplicationsNatural Interface

Applications

Cognitive Sciences Applications

Something related to cognition i.e. mental ability to solve a problem using reasoning, learning ability.

Cognitive Science. This area of artificial intelligence is based on research in biology, neurology, psychology, mathematics, and many allied disciplines. It focuses on researching how the human brain works and how humans think and learn. The results of such research in human information processing are the basis for the development of a variety of computer-based applications in artificial intelligence.

Applications in the cognitive science area of AI include the development of expert systems and other knowledge-based systems that add a knowledge base and some reasoning capability to information systems. Also included are adaptive learning systems that can modify their behaviors based on information they acquire as they operate. Chess-playing systems are primitive examples of such applications, though many more applications are being implemented. Fuzzy logic systems can process data that are incomplete or ambiguous, that is, fuzzy data. Thus, they can solve unstructured problems with incomplete knowledge by developing approximate inferences and answers, as humans do. Neural network software can learn by processing sample problems and their solutions. As neural nets start to recognize patterns, they can begin to program themselves to solve such problems on their own. Genetic algorithm software uses Darwinian (survival of the fittest), randomizing, and other mathematics functions to simulate evolutionary processes that can generate increasingly better solutions to problems. And intelligent agents use expert system and other AI technologies to serve as software surrogates for a variety of end user applications.

ROBOTICS: Al, engineering, and physiology are the basic disciplines of robotics. This technology produces robot machines with computer intelligence and computer- controlled, humanlike physical capabilities. This area thus includes applications designed to give robots the powers of sight, or visual perception; touch, or tactile capabilities; or skill in handling and manipulation; locomotion, or the physical ability to move over any terrain; and navigation, or the intelligence to properly find one’s way to a destination.

NATURAL INTERFACES:

The development of natural interfaces is considered as a major area of Al applications and is essential to the natural use of computers by humans. For example, the development of natural languages and speech recognition are major thrusts of this area of AI. Being able to talk to computers and robots in conversational human languages and have them “understand” us as easily as we understand each other is a goal of AI research. This involves research and development in linguistics, psychology, computer science, and other disciplines. Other natural interface research applications include the development of multisensory devices that use a variety of body movements to operate computers. This is related to the emerging application area of virtual reality. Virtual reality involves using multisensory human- computer interfaces that enable human users to experience computer-simulated objects, spaces, activities, and “worlds” as if they actually exist.

Expert System

An expert system is a computer based application that guides the performance of ill-structured tasks which usually requires experience and expertise. Using an expert system, a non-expert can achieve performance comparable to an expert in that particular domain. Expert systems can be considered as an instance of a DSS. The unique feature of an expert system is the knowledge base, the data and decision rules which represent the expertise.

The concept of expert systems is based on the assumption that an expert’s knowledge can be captured in computer storage and then applied by others when the need arises.

Components of Expert SystemUser Interface: the user interface allows the user to enter instructions and information to the expert system and receive information from the expert system.

Knowledge Base: the knowledge base contains the facts that describe the problem area, and knowledge representation techniques that describe how the facts fit together in a logical manner.

Inference Engine: the interface engine of an expert system takes the rules that defines how the expert processes his factual knowledge and interprets them as appropriate. Unlike a simple program, the steps are not sequentially determined by the programmer, but follow from the data input and the results obtained at earlier stages in the user system

Development Engine: the development engine is used to create the expert system. The process essentially involves building the rule set. There are two basic approaches: programming languages and expert system shells.

System

• A System is a set of individual components linked together achieve a common goal.

• A group of interrelated components working together towards a common goal by accepting input thereby producing output in an organised transformation process.

• A combination of a group of interrelate or interacting elements that form a unified whole.

System Stakeholders

System stakeholder means any person who has an interest in an existing or proposed information system. Stakeholders may include technical and non- technical workers as well as internal and external workers.

1. System Owners: Any Information System can have one or more owners. Usually, system owners are the managers of the organisation. Hence, they view an information in terms of cost and benefits to solve problems and exploit opportunities.

2. System Analyst: System analyst is a specialist who studies the problems and needs of an organisation to determine how people, data, process and information technology can best accomplish improvements for the business. The system analyst is a unique stakeholder because he serves as a facilitator, bridges the communication gaps that can naturally developed between the technical system designer and builder and non technical owners and users.

3. System Designers: A technical experts is someone who translates system users, business requirements and constraints into a technical solutions. A system designer can be a database administrator, network architect, web architect, graphics artists, security experts and technology specialists.

4. System Builders: System builder is a technical specialist who constructs information system and components based on the design specifications generated by the system designers.

5. System Users: System user is a person who will use or is affected by an information system on a regular basis. They are the person who are involved in capturing, validating, entering and exchanging data and information. There are broadly two categories of system users:

a) Internal System Users: Internal system users are clerical and service workers, technical and professional staff, supervisors, middle managers and top managers.

b) External System Users: They are also known as remote user (a user who is located at a distant place but needs the information). Example of external user are customers, suppliers, partners, employees etc.

SDLC (System Development Life Cycle)

SDLC describe the various stages through which software goes during its development. Each SDLC stage consists have well Defined activities and methods to perform their job.

Phases of SDLC:

1. Problem Identification: The objective of problem identification phase is to understand the problem. This necessitates the need for preliminary investigation.

2. Preliminary Investigation: The main objective of preliminary investigation is to determine whether the request is valid and feasible.

3. Feasibility Study: Feasibility study involves seeing whether it is possible (feasible) to do the change in the system or build a new one, as per the outcome of preliminary investigation.Types of Feasibility study:

Economical Feasibility: Study to see that whether it will be economically feasible to go ahead with the system development. If the benefits outweigh costs, then the decision is made to design and implement the new system.Technical Feasibility: It involves studying the system for checking that whether it will be technically feasible to develop and implement the system.Behavioral or Operational Feasibility: The study is done to see that weather the users staff, do will actually be the user of the system, and accept the new system. It is very important that the users are covered to use the new system.

4. System Analysis: System analysis is process of studying existing system and its environment. Interviews, outside observation and questionnaires are different tools used for analysis of the system.

5. System Design: System Design consists of design activities that produce system specification satisfying the functional requirements that were developed in the system analysis process. Cost and benefit analysis is also done during this phase.

System Design

• Screen, Form, Data Element Program and Report, and Structure Procedure Dialog Design Design Design

User Interface Design

Data Design

Process Design

6. Coding: Coding the system involves writing programs, the design made during the design period are converted into actual programs.

7. Testing: Testing the system involves checking all the modules developed, during the coding phase for their proper functionality. Testing involves checking the system for the result by comparing the result with the intended output.Testing is the quality- control measure of software development. Testing detects errors in all the phases of software development, discovering requirements, design and coding errors in software.

There are two types of testing techniques:

Black Box Testing: Detects errors in the functional behavior of a program.

White Box Testing: Detects errors in the internal structure of a program.

8. Implementation: Implementation phase of SDLC involves implementation of the system developed at the user site. Implementation involves user training, site preparation and file conversion.

9. Maintenance: When the implementation or installation phase is completed and user staff is adjusted then the system evaluation and maintenance of hardware and software.There are three types of software maintenance:

– Corrective Maintenance: Corrective maintenance is concerned with the removal of errors discovered after delivery of software to the customer.

For example, when the library management system was delivered, the customer found that the software was not displaying the names of all students who checked out books.

– Adaptive Maintenance: Adaptive Maintenance is concerned with changes in the software due to a change in the environment in which the software functions. For example, a banking system showing message starting that the memory is full, after the 1,000th entry.

Perfective Maintenance: Perfective Maintenance implements new functional system requirements generated by the customer. For example, after testing the banking system, the customer realizes that the system should also show the details of daily transactions being carried out.