The Right Model for the Right Purpose: When Less Is Good Enough

Efficiency is usually defined in terms that involve maximizing output and minimizing input. In statistical analysis, the Efficiency Paradigm is expressed to define an efficient solution as one that has a relatively small variance. This approach to defining efficiency in terms of sufficiency is at the core of the current debate on the definition of sustainable agriculture. Data mining results may drive decision-making activities to design actions in remote parts of the organization. A very important system in the pathway leading to business action is represented by the business processes that are properly trained to turn the decision information into action. The concept of the business organism can be viewed in the context of a complex system. One of the most insightful approaches to modeling comes from the environment of Extreme Programming (XP) software development. The premise of XP is to deliver the software the customer needs when it is needed. The greatest challenge in data mining is not finding ways to analyze data, but deciding when less performance is good enough.