Electronic Data Interchange

EDI - the inter-organization exchange of well-defined business transactions in standardized electronic form directly between computer applications. Focused on Business-To-Business community. Also, EDI can be stated as collection of standard message formats to exchange data between organizations computers via any electronic service.

Domains EDI covers: traditional business facets: inquires, planning, purchasing, acknowledgments, pricing, order status, scheduling, test results, shipping and receiving, invoices, payments, and financial and business reporting. Additional standards: interchange of data relating to security, administrative data, trading partner information, specifications, contracts, distribution..

EDI History

Electronic transmission started during 1960s.
Initially main focus was for road and rail transport industries.
In 1968, the United States Transportation Data Coordinating Committee (TDCC) was formed. This committee coordinated the development of translation rules among existing four sets of industry-specific standards.
Later, the X12 standards of the American National Standards Institute (ANSI) gradually extended and replaced industry-specific standards created by the TDCC.
U.K. Department of Customers and Excise also came up with standards for documents that need to be used in international trade. These were futher extended by the United Nations Economic Commission for Europe (UNECE) as GTDI (General-purpose Trade Data Interchange)
A United Nations Joint European and North American working party (UN-JEDI) addressed the harmonization between the two sets of standardized documents. They developed EDI and came up EIFACT, a document translation standards for administration, Commerce, and Transport. Today, EDI messages are coded in a standard data format based on X12 and EDIFACT specifications.

As we speak,

EDI technology has matured.
EDI has been growing in the past, although the penetration is still low.
In spite of its moderate success, EDI has failed to gain total acceptance and become ubiquitous in industry.
Although EDI technology works well, until now this technology has been expensive to implement.

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

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