Skip to main content

MIS AND INFORMATION CONCEPTS

The goal of the MIS should be to provide the information which has a surprise value and which reduces the uncertainty. It should simultaneously build the knowledge base in the organization by processing the data obtained from different sources in different ways. The designer of the MIS should take care of the data problems knowing that it may contain bias and error by introduction of high level validations, checking and controlling the procedures in the manual and computerized systems. While designing the MIS, due regard should be given to the communication theory of transmitting the information the data obtained from different sources in different ways. The designer of the MIS should take care of the data problems knowing that it may contain bias and error by introduction of high level validations, checking and controlling the procedures in the manual and computerized systems. While designing the MIS, due regard should be given to the communication theory of transmitting the information from the source to the destination.

Special care should be taken to handle a noise and a distortion on the way to destination. The presentation of information plays a significant role in controlling the noise and distortion which might interrupt, while communicating information to the various destinations. The principles of summarization and classification should be carefully applied giving regard to the levels of management. Care should be taken in the process that no information is suppressed to over emphasize.

The utility of information increase if the MIS ensures that the information possesses the necessary attributes. The redundancy of the data and the information is inevitable on a limited scale. MIS should use the redundancy as a measure to control the error in communication.

The information is a quality product for the organization. The quality of information as an out going product can be measured on four dimensions, viz., the utility, the satisfaction, the error and the bias. The MIS should provide specific attention to these quality parameters. A failure to do so would result in a wasteful expenditure in the development of the MIS and poor usage of investment in the hardware and software.

The quality can be ensured if the inputs to the MIS are controlled on the factors of impartiality, validity, reliability, consistency and age.
Labels:

Comments

Post a Comment

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
1 comment
Read more

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
Post a Comment
Read more

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 ...
Post a Comment
Read more