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Data e

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Data e

#1 Post by athomas »

The Data Envelopment Analysis (DEA) a popular management tool is increasingly becoming popular. This write-up is an introduction to the Data Envelopment Analysis (DEA) for people that are unfamiliar with this amazing technique. For an in depth discussion into the DEA, the interested reader may refer to Seiford and Thrall (1990) or the seminal work by Charnes, Cooper and Rhodes (1978). With the advent of the information technology tools and methodologies, major changes are now being witnessed in the way banks and other financing institutions are being managed.

The DEA is commonly used to evaluate the efficiency of any number of producers. A typical statistical approach is characterized as a central tendency approach and it evaluates the various producers in relation to the performance of an average producer. In sharp contrast, the DEA compares each producer with only the “best” producers.

By the way, in the DEA literature, a producer is usually referred to as a decision-making unit or DMU. However, the DEA is not the right tool for analyzing a problem always but it is appropriate in certain cases. In the DEA, there are a number of producers. The production process for each producer is to take a set of inputs and produce a set of outputs. Each producer has a varying level of inputs and gives a varying level of outputs.

This is much evident in sectors like banking and insurance. Almost all the major players in the insurance sector have annual and quarterly targets. They go all out to achieve their objectives, even if it is found to be difficult. The present financial crisis has affected scores of insurance firms also. Thus, the investors are now a worried lot since they never visualized that an insurance firm will go bust within a short span of time.

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