MI13 – 01 MANAGEMENT INFORMATION SYSTEM

Q. 1. Briefly explain the approaches of MIS development.

Ans. There are seven approaches, which are used for developing MIS:

1. Top Down Approach: This approach develops a corporate plan as a guide for designing the information system. Here top management takes the lead in formulating objectives, policies and plans and communicates them down the line to middle and supervisory management for translating them into reality.

2. Bottom Up Approach: It consists of following five steps:

i. Individual functional applications are planned separately consisting of transaction processing, updating of files and simple reports.

ii. Files of various functional applications are integrated by means of indexing and chaining into a database.

iii. Various functions are added to operate on the database at management control level.

iv. Integration of models into a model base having a wide variety of analysis, decision and planning models

v. Strategic planning data and planning models are added to the information system.

3. Integrative Approach: This approach permits managers at all levels to influence the design of the information system. Here evaluation, modification and approval of top management continue, till a final design is acceptable to all levels.

4. Traditional Approach: Here activities are performed in sequence. Each activity is undertaken only when the previous activity is completed. Managers and users, consider and review the work performed by MIS professionals during each stage of processing, in order to ensure accuracy and completeness.

5. Prototyping Approach: In order to avoid any possible delay, prototyping approach is used. The goal is to develop a small or pilot version, called a prototype, which is built quickly and at lesser cost with the intention of modifying it when need arises.

6. End User Development Approach: With the increasing availability of low cost technology, end user development is popular in many organizations. Here the end user is responsible for system development.

7. Systematic Approach for Development in Small Organizations: Since fewer MIS professionals shall be working having with variety of responsibilities that they have little time to develop new systems for users. In a very small organization, no MIS profession will exist. This does not mean that they cannot develop management information systems. They develop systems using the following steps:

i. Identify reqwuirements.

ii. Locate, evaluate and secure software development.

iii. Locate, evaluate and secure hardwares

iv. Implement the systems.

Q. 2. Explain the function of DSS.

Ans. The term, Decision Support System (DSS) refers to a class of systems, which support the process of decision making. The emphasis is on support rather than on automation of decisions. DSS allows the decision maker 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 – solve semi structured and unstructured problems.

Functions of DSS:

There are five functions of a DSS facilitating managerial decision making. They are:

1. Model Building

This allows decision makers to identify the most appropriate model for solving the problem on hand. It takes into account input variables, interrelationships among the variables, problem assumptions and constraints. For example, a marketing manager of a television manufacturing company is charged with the responsibility of developing a sales forecasting model for color TV sets. A model builder uses a structured framework to identify variables like demand, cost and profit, analyze the relationships among these variables, identify the assumptions, if any (e.g., assume the prices of raw materials will increase by 5% over the forecasting period), and identify the constraints like the production capacity of the plant. All this information is then integrated by a system into a decision making model, which can be updated and modified whenever required.

2. ‘What-if’ Analysis

This is the process of assessing the impact of changes to model variables, the value of the variables, or the interrelationships among variables. This helps managers to be proactive, rather than reactive, in their decision-making. This analysis is critical for semi-structured and unstructured problems because the data necessary to make such decisions are often either not available or incomplete. Hence, managers normally use their intuition and judgment in predicting the long-term implications of their decisions. Managers can prepare themselves to face a dynamic business environment by developing a group of scenarios (best-case scenario, worst case scenario and realistic scenario).

3. Goal Seeking:

It is the process of determining the input values required to achieve a certain goal. For example, house buyers determine the monthly payment they can afford (say for example, Rs. 5,000) and calculate the number of such payments required to pay the desired house.

4. Risk Analysis:

It is a function of DSS that allows managers to assess the risks associated with various alternatives. Decisions can be classified as low risk, medium risk, and high risk. A DSS is particularly useful in medium risk and high risk environments.

5. Graphical Analysis:

This helps managers to quickly digest large volumes of data and visualize the impacts of various courses of action. S L Jarvenpaa and G W Dickson studied the relative advantages and disadvantages of tabular and graphic output. They recommended the use of graphs when:

· Seeking a quick summary of data

· Detecting trends over time

· Comparing points and patterns at different variables.

· Forecasting activities

· Seeking relatively simple impressions from a vast amount of information.

The researchers suggested that a tabular presentation be used when it is necessary to read individual data values.

Jarvenpaa and Dickson has also offered the following tips when choosing between the various types of graphs:

· Line or bar charts are preferred for summarizing data.

· Grouped line or bar charts are good for showing trends over time.

· Grouped bar charts are better than pie charts for presenting parts of a whole.

· Use horizontal rather than vertical bars when comparing variables.

· Use single line or bar charts to compare individual data points between variables.

· Put data values on the top of the bars in a bar chart for easier reading.

Q. 3. Write Short notes on:

A) Decision Support System

Ans. Decision Support System (DSS) is an application of Herbert Simon model. In this mode, there are 3 phases i.e. Intelligence, Design and Choice. The DSS basically helps the information system in the intelligence phase where the objective is to identify the problem and then go to the design phase for solution. The choice of selection criterion varies from problem to problem. Therefore, it is required to go through these phases again and again till a satisfactory solution is found. These systems are helpful in making a decision and also its performance evaluation. These systems can be used to validate the decision by performing the sensitivity analysis on various parameters of the problem.

In Decision making, programmed decision, because of its rule structure, can be computerized, as inputs, processing methodology, analysis and choice of decision making are predetermined. DSS can be built around the rule in case of programmed decision situation, while in non programmed decisions, the rules are not fixed or predetermined and requires the user to go through the decision making cycle as indicated in the Herbert Simon Model every time.

B) System Testing and Implementation

Ans. Testing is one of the most difficult tasks in system development; it requires creativity, persistence, and a thorough understanding of the system. It involves thoroughly probing the system to ensure that its performance matches system requirements and meets the expectations of end users. There are three types of testing: Unit Testing, System Testing and Acceptance Testing.

In Unit Testing, a system is viewed as a collection of programs (units), and each program is individually tested, without any assurance that the system is free of errors. In system testing, testing is performed of the entire system to ensure that its component units will function effectively when brought together as a system. In Acceptance Testing, developers and users test the system under actual or simulated operating conditions to ensure that it is acceptable to users.

A good system prevails when it is implemented without affecting the routine operations of the organization. This requires careful planning and coordination. In case the system is new, implementation is quite straightforward. If the system is replacing an existing one, implementation becomes critical.

C) Rapid Application Development

Ans. A methodology that has the same objective of speedy response to user needs as does prototyping but is broader in scope is called Rapid Application Development (RAD). RAD is a term coined by James Martin, Computer consultant and author, for a development life cycle intended to produce systems quickly without sacrificing quality. It is an integrated set of strategies, methodologies, and tools that exists within an overall framework called Information Engineering (IE).

Information Engineering starts with the executive level, with strategic information resources planning applied to the entire enterprise. Thereafter, each business unit within the firm is subjected to business area analysis (BAA) to define the activities (or processes) and data that are necessary for the unit to function as intended. With the completion of BAA, RAD can proceed.

Q. 4. Explain the steps involved in the development of Operational Prototype and Discardable prototype.

Ans. Prototyping: Prototyping is a process whereby systems are developed swiftly, without having undergone a complete analysis and specification. The system that is developed is known as the prototype.

The process relies on the prototype system it self being an aid to the specification i.e. by consideration of the prototype and identification of its weaknesses an improved system can be developed. Prototyping also relies on the presence of software tools to produce prototypes quickly. The process is thus heavily user oriented.

Operational Prototype (Type 1 prototype): The figure below shows the steps involved in developing a Type 1 prototype. There are 4 steps and are as follows:

1. Identify the user needs: The system analyst interviews the user to obtain an idea of what is required from the system.

2. Develop a prototype: The system analyst, working with other information specialists, uses one or more prototyping tools to develop a prototype.

3. Determine if prototype is acceptable: The analyst educates the user in prototype use and provides an opportunity for becoming familiar with the system. The user advises the analyst whether the prototype is satisfactory. If so, then the next step, i.e. step 4 is taken, else the prototype is revised by repeating steps 1, 2, and 3 with a better understanding of the user needs.

4. Use the Prototype: The prototype becomes the operational system.

This approach is possible only when the prototyping tools enable the protype to contain all the essential elements of the new system.

Development of a Discardable Prototype (Type 2 prototype): The steps involved in discardable prototype are as follows:

1. Identify the user needs: The system analyst interviews the user to obtain an idea of what is required from the system.
2. Develop a prototype: The system analyst, working with other information specialists, uses one or more prototyping tools to develop a prototype.

3. Determine if prototype is acceptable: The analyst educates the user in prototype use and provides an opportunity for becoming familiar with the system. The user advises the analyst whether the prototype is satisfactory. If so, then the next step, i.e. step 4 is taken, else the prototype is revised by repeating steps 1, 2 and 3 with a better understanding of the user needs.

4. Code the operational system: The programmer uses the prototype as the basis for coding the operational system.

5. Test the Operational System: The programmer tests the system.

6. Determine if the Operational System is acceptable: The user advises the analyst as to whether the system is acceptable. If so a step 7 is taken else step 4 and step 5 is repeated.

7. Use the Operational System

This approach is followed when the prototype is intended only to have the appearance of an operational system but not when it is contain all of the essential elements.


Q. 5. Explain Expert System. Also briefly explain its components.

Ans. An expert system is a computer 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, which is comparable to an expert’s performance in that particular domain.

An expert system is very similar to a decision support system, i.e. both are intended to provide a high level of problem solving support to their users. But they differ in two major ways:

First, a DSS consists of routines that reflect as to how the manager believes a problem should be solved, as well as the manager’s style and capabilities. An expert system on the other hand, offers the opportunity to make decisions that exceed the manager’s capabilities.

The second, but most important difference between DSS and ES is the ability of the expert system (ES) to explain its line of reasoning in reaching a particular solution. Very often, the explanation of how a solution was reached is more valuable than the solution itself.


a. User Interface: The user interface enables the user to enter instructions and information into the expert system and also to receive information from it. The instructions specify the parameters that guide the expert system through its reasoning process. The information is in the form of values assigned to certain values.

i. Expert System Inputs: The user can use 4 methods for input purposes: menus, commands, natural language and customized interfaces.

ii. Expert system Outputs: Expert systems are designed to recommend solutions. These solutions are supplemented by explanations. There are two types of explanations: Explanation of questions and Explanation of problem solution.

· Explanation of Questions: The manager may desire explanations while the expert system performs its reasoning. Perhaps the expert system will prompt the manager to enter some information. The manager asks why the information is needed, and the expert system provides an explanation.

· Explanation of problem solution: After the expert system provides a problem solution, the manager can ask for an explanation of how it was reached. The expert will display each of the reasoning steps leading to the solution.

b. Knowledge base: The knowledgebase contains both facts that describe the problem area and knowledge representation techniques that describe how the facts fit together in a logical manner. The term problem domain is used to describe the problem area. The popular knowledge representation techniques are rules and networks of rules.

The rules in the knowledge base are usually coded in the form, IF X THEN Y, where X is a condition; Y is an action to be taken if the condition is true. All the rules contained in an expert system are called the rule set.

The rules of a rule set are not physically linked, but their logical relationships can be established.

c. Inference Engine: The inference engine is the portion of the expert system that performs reasoning by using the contents of the knowledge base in a particular sequence. During the consultation, the inference engine examines the rules of the knowledge base one at a time, and when a rule’s condition is true, specified action is taken. In expert system terminology, the rule is fired when the action is taken.

Two main methods have been devised for the inference engine to use in examining the rules: forward reasoning and reverse reasoning.

In forward reasoning, also known as forward chaining, the rules are examined one after another in a certain order. The order might be the sequence in which the rules are entered in to the rule set, or it might be some other sequence specified by the user. As each rule is examined, the expert system attempts to evaluate whether the condition is true or false.

In reverse reasoning, also known as backward chaining, the inference engine selects a rule and regards it a problem to be solved.

Reverse reasoning is faster than forward reasoning because it does not have to consider all the rules and does not make multiple passes through the rule set. Reverse reasoning is appropriate when:

* There are multiple goal variables.
* There are many rules
* All or most of the rules do not have to be examined in the process of reaching a solution.

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

i. Programming languages: An expert system can be created using any programming language, however, two are especially well suited to the symbolic representation of the knowledge base, prolog and lisp.

ii. Expert System shells: An expert system shall is a ready-made processor that can be tailored to a specific problem domain through the addition of the appropriate knowledge base. In most cases, the shell can produce an expert system quicker and easier than by programming.

Q. 6. Explain the Neural Network Process with a neat figure.

Ans. A Neural Network is a program that models the pattern recognition capabilities of the human brain, thereby endowing machines with the ability to identify and classify faces, voices, pictures and written characters. Neural networks are programs that model the interconnections of human brain cells.

A generic neural network is shown below. It is made up of interconnected processing elements (PE), which are self-adjusting units that are firmly connected with other processing elements (PE) in the system. A processing element receives inputs from the user; each input has a certain weight assigned to it. The weights influence the way the input is processed by the processing element, and the processing element is capable of automatically adjusting the weights of the inputs based on its past experiences. Each processing element processes the input and generates a single output signal to other processing elements in the network. The system observes the overall pattern of outputs generated by the processing elements and this pattern forms the basis for information, analysis and retrieval. Thus, unlike other computers, which are programmed to perform a task, neural computers are trained to perform a task. By controlling and fine-tuning the type and flow of information among processing elements, the software gradually changes the connections betw4een them, and in this way new information is learned. For example, one neural network learned to pronounce 20,000 words.


Q. 7. “MIS design is more dynamic with well defined authority and decision making structure”. Explain how client server Architecture serves this need?

Ans. MIS design is more dynamic with well-defined authority and decision-making structure. The client server architecture because of its capabilities serves well with this need of MIS. It provides comprehensive support to the decision makers. With the business growth, it allows easy expansion of any nature. The architecture is scalable on both sides and also cost performance effective.

The decision-making has shifted from data to information, to individual. The architecture of the system should therefore be, such that it is flexible and easy to change. It is required of the nature where business processes and rules governing them can be changed as suited to the decision maker and also they can coexists. Database should be stable and secured, and process management flexible. The architecture should meet local needs and serve corporate global needs. To meet this complex, architecture need, it was necessary to built a model where data business logic – its usage and presentation is on different hardware software platform.

The client server architecture helps this requirement very efficiently. It is user centric as each user can have his view of the business and its process. The user can evolve his own decision-making processes. The client server architecture offered such a platform due to its following important characteristics:

On the physical side, it is scalable, expandable and the distance between two locations for communication is no issue. The system components are divisible locally or at different platforms. For example, the user can distributed databases and distributed processing. It is platform independent where operating system, hardware, architecture; vendor specific differences are no longer serious limitations. It is possible to build the system suitable to user locations, data sources and application requirement.

Due to capabilities of data warehousing, data replication and distribution of application logic across the servers, it is possible to optimize the usage of hardware and software with full benefit to the users.

Client server architecture provides this environment where MIS is a flexible and dynamic model as compared to traditional model of MIS working on mainframe model.

MIS for competitive and strategic needs requires heavy transaction processing and using processed information to update the business status initiating a variety of actions. Client server architecture offers such functionality to perform.

Ability of client server architecture to store data and swift access, and processing capabilities helps to try and simulate variety of strategy before they are firmed up. Use of executive information system, data reverse engineering for evolving and analysis of strategies is easily possible because of client server architecture using frond end tools and packaged software on business modeling, risk analysis and forecasting.

MIS essentially revolves around mission critical applications designed for highest customer satisfaction. A majority of such applications are real time transaction processing at multiple locations. The resultant business status needs to be put together to infer the position of performance. Client server architecture essentially focuses this requirement of business across the organization. With second-generation multi-tier client server architecture, it is possible to build MIS, which is efficient to provide rich information for decision making at all levels. Once can conceptualize different models of MIS i.e.; corporate MIS, functional MIS, divisional MIS, personnel MIS etc.

Q. 8. Explain Value stream model of organization.

Ans. The organization is established to fulfill customer needs, having associated customer values. The value is a measure, an intangible measure, which is difficult to count in clear terms or specifications as different customers have different value priorities, value mix and buying decision criteria. However, if the value expectations are fulfilled, the customer satisfaction is automatic. The customer is satisfied when he believes that the price paid by him fulfills the value expectations. The value is an intangible concept and the customer has his own perceptions on the value. There are about twenty-one parameters on which the customer puts value and evaluates the product or the service. He may consider all the parameters or only a few of them for his buying decision.

The business organization, however, has to decide which customer segment it will like to serve and then evolve various business strategies. The organization is required to design such processes, which will satisfy the value perceptions of the customer. Depending upon the value choice of the customer, the processes of the organization become critical and relevant. Only these critical processes really matter for business succe3ss in terms of survival, growth, leadership and competitive advantage. The process model, therefore, can be seen as a value stream model, relevant to the organization. For example, an organization in food business will consider those processes critical and relevant, which produce food products fulfilling basic needs of appetite and taste and meets the value expectations on availability, perceived belief, packaging, price, and ease of access. Every organization must, therefore, identify value streams in the process model, consistent with the business, the goods manufactured and the nature of business and its objectives.