Skip to main content

NEED FOR SYSTEM ANALYSIS

When you asked to computerise a system, as a requirement of the data processing or the information need, it is necessary to analyze the system from different angles. While satisfying such need, the analysis of the system is the basic necessity for an efficient system design. The need for analysis stems from the following point of view.

  1. System Objective: It is necessary to define the system objective(s). Many a times, it is observed that the systems are historically in operation and have lost their main purpose of achievement of the objectives. The users of the system and the personnel involved are not in a position to define the objective(s). Since you are going to develop a computer based system, it is necessary to redefine or reset the objective(s) as a reference point in the context of the current business requirement.
  2. System Boundaries: It is necessary to establish the system boundaries which would define the scope and the coverage of the system. This helps to sort out and understand the functional boundaries of the system, the department boundaries in the system, and the people involved in the system. It also helps to identify the inputs and the outputs of the various sub-systems covering the entire system.
  3. System Importance: It is necessary to understand the importance of the system in the organization. This would throw more light on its utility and would help the designer to decide the design features of the system. It would be possible then to position the system in relation to the other systems for deciding the design strategy and development.
  4. Nature of The System: The analysis of the system will help the system designer to conclude whether the system is the closed type or open, and a deterministic or probabilistic. Such an understanding of the system is necessary, prior to design the process to ensure the necessary design architecture.
  5. Role of the System as an Interface: The system, many a times, acts as an interface to the other systems. Hence through such an interface, it activates or promotes some changes in the other systems. It is necessary to understand the existing role of the system, as an interface, to safeguard the interests of the other systems. Any modifications or changes made should not affect the functioning or the objective of the other systems.
  6. Participation of Users: The strategic purpose of the analysis of the system is to seek the acceptance of the people to a new development. System analysis process provides a sense of participation to the people. This helps in breaking the resistance to the new development and it also ensure the commitment to the new system.
  7. Understanding of Resource Needs: The analysis of the system helps in defining the resource requirements in terms of hardware and software. Hence, if any additional resources are required, this would mean an investment. The management likes to evaluate the investment form the point of view of return on such investment. If the return on the investment is not attractive, the management may drop the project.
  8. Assessment of Feasibility: The analysis of the system helps to establish the feasibility from different angles. The system should satisfy the technical, economic and operational feasibility.

Many times, the systems are feasible from the technical and economic point of view: but they may be infeasible from the operational point of view.

The assessment of feasibility will save the investment and the system designer’s time. It would also save the embarrassment to the system designer as he is viewed as the key figure in such projects. One can approach the system analysis and design exercise in a systematic manner in steps, as shown in the Table below :

Steps

Elaboration

Explanation

Need for information

Define the nature of information. Also who wants and who uses.

Identify the users and application of the information for achieving the objectives.

Define the Systems

Decide the nature, type of the system and its scope

Helps to determine the system ownership, its benefits and complexity.

Feasibility

Technical success

Economic viability

Operational effectiveness

Hardware and software availability and capability, for implementation.

Study the investment and benefits. Assess the improvement in value of the information. Determine the return on investment.

Examine whether the system will perform as desired in terms of time and results. Are the users ready to use the system?

Detailing the requirements

Identify in precise terms, the strategic, functional and operational information needs.

Study the sources of generating the Information. Establish I/O linkages. Modify the existing system to satisfy the needs.

Conceptual system

Determine the inputs, process and outputs, and design a conceptual model.

Conceptualization is necessary to understand the system process.

Detailing the system

Draw the document flow charts and the data-flow diagrams, the data and system hierarchy diagrams, the data information versus its users mapping table.

Helps in bringing a clarity in the data-flow. The responsibility centres and the process centres are identified.

Structuring the system design

Break the system into its hierarchical structure.

Helps in understanding the data-flow from one level to the other and the processes carried out at each level.

Conceptual model of computer system

Define step by step the usage of files, processes and interface. Define the data structures and the validation procedures.

Helps to put down the data processing flow in the computerized system. Draw the computer system charts.

Break the system in programme modules

Make a physical conversion of the system into the programme structures in a logical order.

Modules will be data entry, data validation, data processing, reporting and storing.

Develop the test data for checking the system ability

Test the modules and the integrity of the system in terms of input versus output. Plan while box and black box testing.

Confirms whether the system design is satisfactory. Suggests the modifications.

Install the system

Install on the hardware.

Install, test and run the system before the user is exposed in alive mode.

Implementation

Train the personnel. Run the system in parallel. Prepare a system manual.

Help to identify the problems and provide solutions.

Review and maintenance

Review the system through audit trail and test data, also confirm whether the objective is fulfilled. Carry out the modifications, if any.

Helps to maintain the system quality and the quality of information through modification, if necessary.


Comments

Popular posts from this blog

Advantages and Disadvantages of EIS Advantages of EIS Easy for upper-level executives to use, extensive computer experience is not required in operations Provides timely delivery of company summary information Information that is provided is better understood Filters data for management Improves to tracking information Offers efficiency to decision makers Disadvantages of EIS System dependent Limited functionality, by design Information overload for some managers Benefits hard to quantify High implementation costs System may become slow, large, and hard to manage Need good internal processes for data management May lead to less reliable and less secure data

Inter-Organizational Value Chain

The value chain of   a company is part of over all value chain. The over all competitive advantage of an organization is not just dependent on the quality and efficiency of the company and quality of products but also upon the that of its suppliers and wholesalers and retailers it may use. The analysis of overall supply chain is called the value system. Different parts of the value chain 1.  Supplier     2.  Firm       3.   Channel 4 .   Buyer

Big-M Method and Two-Phase Method

Big-M Method The Big-M method of handling instances with artificial  variables is the “commonsense approach”. Essentially, the notion is to make the artificial variables, through their coefficients in the objective function, so costly or unprofitable that any feasible solution to the real problem would be preferred, unless the original instance possessed no feasible solutions at all. But this means that we need to assign, in the objective function, coefficients to the artificial variables that are either very small (maximization problem) or very large (minimization problem); whatever this value,let us call it Big M . In fact, this notion is an old trick in optimization in general; we  simply associate a penalty value with variables that we do not want to be part of an ultimate solution(unless such an outcome is unavoidable). Indeed, the penalty is so costly that unless any of the  respective variables' inclusion is warranted algorithmically, such variables will ...