Skip to main content

Use of Information Management Systems [MIS]


Use of Information Management Systems

The management of Information is facilitated by the use of Information Technology and Information Sciences. The popular Information Management Systems can be listed as follows:

Document management system (DMS)

The DMS is focused primarily on the storage and retrieval of self-contained electronic data resources in the document form. Generally, The DMS is designed to help the organizations to manage the creation and flow of documents through the provision of a centralized repository. The workflow of the DMS encapsulates business rules and metadata.

Content management system (CMS)

The CMS assist in the creation, distribution, publishing, and management of the enterprise information. These systems are generally applicable on the online content which is dynamically managed as a website on the internet or intranet. The CMS system can also be called as ‘web content management’ (WCM).

Library management system (LMS)

Library management systems facilitate the library technical functions and services that include tracking of the library assets, managing CDs and books inventory and lending, supporting the daily administrative activities of the library and the record keeping.

Records management system (RMS)

The RMS are the recordkeeping systems which capture, maintain and provide access to the records including paper as well as electronic documents, efficiently and timely.

Digital imaging system (DIS)

The DIS assist in automation of the creation of electronic versions of the paper documents such as PDFs or Tiffs. So created Electronic documents are used as an input to the records management systems.

Learning management system (LMS)

Learning management systems are generally used to automate the e-learning process which includes the administrative process like registering students, managing training resources, creating courseware, recording results etc.

Geographic information system (GIS)

The GIS are special purpose, computer-based systems that facilitate the capture, storage, retrieval, display and analysis of the spatial data.

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 never be p